0 Powered by : National Solar Energy Federation of India (NSEFI), an India-based solar industry body, has said India is set to become the world’s second-largest solar market in 2026 by annual installations. According to the statement, India has installed 50 GW of additional solar capacity in just 14 months, raising total installed solar capacity to 150 GW. The statement has also added that the first 50 GW had taken 11 years to materialize, while the rise from 100 GW to 150 GW had taken nearly three years. NSEFI said that the solar capacity is expected to reach to 280-300 GW to help India attain its 500 GW non-fossil capacity target by 2030, with yearly additions approaching 50 GW. It added that PM Surya Ghar, the upcoming PM KUSUM 2.0, floating solar policies, and demand associated with the National Green Hydrogen Mission are supporting this growth. The industry body further said DRE and C&I solar are likely to lead expansion during the next three years.
German research organisation Fraunhofer ISE has launched a new consultancy spin-off—NEXUS GreenTech—to support companies active in the solar PV industry. NEXUS GreenTech was founded at the end of March, and is headquartered in Freiburg, Germany. The new company is led by Dr Jochen Rentsch, Dr Sebastian Nold and Dr Nico Wöhrle, who were previously working with the PV Technology Transfer unit at Fraunhofer ISE, and nave more than 60 years of cumulative experience in PV research, development and technology. Get Premium Subscription Rentsch said that the spin-off aims to address “a great need for consulting” in an increasingly complex global PV industry. “During our collaboration with PV companies in the field of technology transfer, we repeatedly noticed that many of the inquiries were not about a research question in the strict sense,” said Rentsch. “At the same time, there is a great need for consulting: Which cell technology should I choose, which suppliers are available, which factory layout makes sense—to name just a few issues.” Fraunhofer ISE said that the company would focus on several key areas, including technical and commercial due diligence, feasibility studies, layout planning for factories and technology consulting. NEXUS GreenTech will use scientific methods from Fraunhofer ISE, secured through cooperation and licensing agreements. The spin-off will start work with US solar cell manufacturer Talon PV, and support “the establishment and operation” of a new production line of tunnel oxide passivated contact (TOPCon) cells. Last year, Talon PV CEO Adam Tesanovich spoke to PV Tech Premium about some of the legal barriers that have impeded domestic TOPCon production in the US, and how the company aims to overcome them. In the months since, the company signed a wafer supply agreement with German solar wafer manufacturer NexWafe. This is also not the first collaboration between Talon PV and Fraunhofer ISE. Last year, the latter announced plans to build a pilot TOPCon cell production line in Germany to support the former’s development of its own manufacturing capacity in the US, and the launch of NEXUS GreenTech follows on from this cooperation.
Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Scientific Reportsvolume 15, Article number: 40405 (2025) Cite this article 1775 Accesses 3 Citations Metrics details The concept of Islanded Hybrid Power System (IHPS) has attracted considerable interest lately, especially for energizing remote or energy-poor locations. IHPS are more dependable and cost-effective alternatives to systems using only one energy source when properly constructed. IHPS configuration, including Diesel Engine Generator (DEG), Photovoltaic (PV) systems, and Battery Storage (BATT) elements, are desirable for islanded systems about price and dependability. IHPS mostly use Renewable Energy Sources (RES) for power production, which is variable. Consequently, these variations often make it difficult for traditional control systems to maximize efficiency across various operating environments. The current research discusses the requirement for more effective frequency control in IHPS by suggesting a Model Reference Adaptive Control-Fuzzy Proportional Integral based Whale Optimization Algorithm (MRAC-FPI-WOA) controller. The proposed controller can efficiently manage a range of disturbances by dynamically adjusting its control techniques. The current research conducts an evaluation study comparing the effectiveness of the suggested MRAC-FPI-WOA controller against FPI-WOA, PI-WOA, and PI-PSO controllers. The key evaluation criteria are the ability to maintain stability in frequency within the IHPS and the effectiveness of power production in the overall system. The results demonstrate the superior performance of the MRAC-FPI-WOA controller across diverse operational scenarios. Notably, during a three-phase fault at Bus2, the MRAC-FPI-WOA controller achieves significant performance enhancements over the PI-PSO controller, with reductions of 59.05% in maximum overshoot (%(:{text{M}}_{text{p}})), 72.83% in maximum undershoot (%(:{text{M}}_{text{u}text{s}})), 32.07% in settling time ((:{text{T}}_{text{s}})), and 34.81% in the integral of time-weighted absolute error (ITAE). A similar trend is observed during a three-phase fault at the tie-line, where the MRAC-FPI-WOA controller yields improvements of 57.47% in %(:{text{M}}_{text{p}}), 79.36% in %(:{text{M}}_{text{u}text{s}}), 40.9% in (:{text{T}}_{text{s}}), and 78.08% in ITAE. Furthermore, the controller exhibits exceptional dynamic responsiveness to ramp variations in solar radiation, substantially reducing %(:{text{M}}_{text{p}}:)by 96.72%, %(:{text{M}}_{text{u}text{s}}) by 95.24%, (:{text{T}}_{text{s}}:)by 22.79%, and ITAE by 89.69%. Additionally, it demonstrates robust adaptability to random solar radiation fluctuations, consistently optimizing transient response with reductions of 96.63% in %(:{text{M}}_{text{p}}), 99.58% in %(:{text{M}}_{text{u}text{s}}), 22.07% in (:{text{T}}_{text{s}}), and 95.23% in ITAE. Sustainable energy solutions are being widely adopted in modern power systems to reduce environmental impact and enhance grid performance. While they improve efficiency, voltage stability, and ecological benefits, their excessive integration can challenge grid operation, protection, and control1. A microgrid (MG) represents a localized power network that integrates renewable generation sources (e.g., photovoltaic arrays, wind turbines) with energy storage components (e.g., battery banks) to form a self-contained electrical system2. Hybrid Power System (HPS) operation can switch between two key modes: independent (islanded) and grid-tied operation. IHPS are considered the most effective approach for supplying electricity to remote and rural areas due to their technical feasibility and cost-efficiency3. The intermittent and unpredictable nature of RES in HPS can cause voltage instability and oscillations, potentially affecting connected loads. To ensure system reliability and the quality of electrical supply, an effective control strategy must be developed, allowing the HPS to operate efficiently despite uncertainties in weather conditions and load variations during the system runs in real-time4. As a result, IHPS operations necessitate BATT to retain surplus energy generated by the HPS, ensuring power availability when production is insufficient to meet demand. This study examines the dynamic performance of IHPS under various operating conditions. The efficient control and management of HPS require advanced strategies and algorithms to optimize the utilization of RES, manage BATT, and ensure a stable and reliable power supply5. One of the most critical aspects of HPS operation is frequency stability, which is essential for maintaining high-quality electricity for connected loads. Fluctuations in frequency arise from variations in power generation and consumption, highlighting the necessity for robust frequency regulation mechanisms to maintain HPS stability and performance6. Several approaches can be applied to frequency regulation in IHPS. One widely used method involves BATT to compensate for fluctuations in RES generation, ensuring a steady and secure system frequency. Other techniques include advanced control strategies and demand-side management approaches. Extensive research has explored various control methodologies for regulating the operation of standalone hybrid MG7. A control strategy proposed in8 focuses on biogas-based MG, allowing the system to increase or decrease power generation in response to disturbances caused by fluctuations in RES input or load demand. However, a key drawback of this approach is its inability to respond swiftly to sudden changes, potentially leading to transient instability. Additionally, the controller may lack robust fault detection and isolation capabilities, and its effectiveness could decline when scaling up or integrating with larger power grids. To enhance frequency regulation and stability, Ref9 suggests using an adaptive active power droop controller along with voltage setpoint adjustment in IHPS. These control mechanisms aim to improve the overall performance of HPS systems. Furthermore, Ref10 explores a control technique for BATT designed to mitigate frequency variations and enhance the dynamic response of IHPS. To achieve superior frequency stability during transient disturbances, they propose the use of a Piecewise Linear-Elliptic (PLE) droop characteristic in BATT control systems. This control characteristic enables a faster equilibrium between consumption and power generation, leading to improved frequency regulation in HPS. However, while the PLE controller can reduce frequency variations, it does not fully eliminate them. Additionally, it may be less effective when load demand is lower than power generation, potentially causing sudden fluctuations in BATT output power. In11, a voltage regulation strategy for IHPS incorporating PV and BATT was examined. Ref12 deals with the control of the Vehicle Cruise Control System (VCCS) based on a Model Predictive Controller (MPC) in parallel with the conventional PID controller. The study evaluates the technique’s effectiveness in improving HPS performance, but it does not fully address key challenges related to islanded mode regulations, frequency stability, protection settings, power management, and load diversity handling in HPS. Optimization algorithms inspired by biological and natural phenomena are classified as metaheuristic approaches. Unlike traditional mathematical optimization techniques, which often struggle with complex search spaces, metaheuristic algorithms effectively explore potential solutions to high-dimensional, nonlinear, and multi-modal optimization problems. As a result, techniques like the WOA, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) have gained widespread attention across various fields. These techniques are commonly used to optimize system performance by fine-tuning control parameters in advanced control systems, including Proportional-Integral (PI), Proportional-Integral-Derivative (PID), Fuzzy Proportional-Integral (FPI), Fractional-Order PI (FOPI), and Fuzzy-Fractional Order PID (FFOPID) controllers. Recent studies highlight innovative bio-inspired optimization techniques for power systems. In13 Bio-Dynamic Grasshopper Optimization Algorithm (BDGOA) is used to optimize Tilt-Derivative with N-filter plus PI controllers for frequency/tie-line oscillation damping. In14 Diligent Crow Search Algorithm (DCSA) is employed for solar cell parameter identification to maximize PV output. In15 Hybrid Adaptive Ant Lion Optimization (HAALO) with PI/FOPID controllers is developed to enhance Switched Reluctance Motor performance through adaptive mutation and torque ripple reduction. In16 BDGOA is applied for precise parameter estimation across five solar module technologies. In17 Crow-Search Algorithm (CSA) is employed to optimize Type-2 Fuzzy Cascade (T2F-CPIF) controllers for robust frequency/tie-line error mitigation in hybrid systems under contingency scenarios. In18 WOA is utilized to enhance Fuzzy Cascade PD-PI controllers, substantially improving microgrid transient response during operational disturbances. For secondary frequency regulation. In19 Improved Salp Swarm Optimization (I-SSO) tuned Type-II Fuzzy PID controller is implemented to maintain nominal frequency and tie-line power despite uncertainties. Complementing these approaches. In20 advanced Sine Cosine Algorithm (a-SCA) is implemented to optimize the Fractional-Order Fuzzy for precise generation-demand balancing in fluctuating conditions. In21 Coati Optimization Algorithm (COA) was implemented to optimize the parameters of Fuzzy-PI (FPI) and conventional PI controllers, significantly improving the frequency regulation performance in a two-area power system. In22 modified Sea-horse Optimization (SHO) method is developed for tuning Proportional-Integral-Derivative-Tilt (PID-T) controllers in renewable-integrated multi-area systems. In23 SHO is enhanced to optimize Model Predictive Control (MPC), PID, Fractional order proportional integral derivative (FOPID), and Tilted Integral Derivative (TID) controllers for complex power networks. For cyber-resilient operation. In24 Chaos Quasi-Oppositional SHO (CQOSHO) proposes to tune a novel Cascaded tilted-FO derivative with filter ((:{text{C}text{P}text{D}}^{{upmu:}})F − TI) controller with deep learning capabilities. Complementing these advances. In25 Opposition-based SHO (OSHO) is developed for hybrid systems, optimizing TID-MPC controllers to manage renewable penetration and virtual inertia challenges. In26 Dragonfly Search Algorithm (DSA) is employed to optimize an Adaptive Fractional Order PI (AFOPI) controller for precise motor speed regulation. In27 DSA is utilized for tuning a novel cascaded PI-(FOP + PD) structure to mitigate frequency fluctuations in power systems. Complementing these approaches. In28 Tunicate Search Algorithm (TSA) is implemented to enhance transient stability in hybrid grids through optimized Tilt Fractional Order PID (TFOPID) control. These developments showcase the effectiveness of bio-inspired optimization in addressing diverse control challenges across electromechanical and power system applications. The proposed WOA has demonstrated remarkable efficacy across diverse domains, especially in enhancing control system configurations29. For instance, when applied to PID controllers, WOA-optimized systems achieve rapid transient responses, minimized steady-state deviations, and enhanced oscillation damping in contemporary power grids, outperforming GA and Artificial Bee Colony (ABC) approaches30. In renewable energy applications, WOA-driven Fractional-Order Proportional-Integral Controllers (FOPIλ) excel within sensor-free speed control applications for solar-fed permanent-magnet brushless DC motors. These systems surpass Bat Algorithm (BA) and Grey Wolf Optimizer (GWO) implementations by reducing tracking errors and shortening convergence intervals31. Similarly, WOA-enhanced FFOPID controllers integrated into active vehicle suspension models significantly attenuate driver vibrations relative to Fractional-Order PID (FOPID) and PSO-tuned counterparts32. Furthermore, WOA-based Maximum Power Point Tracking (MPPT) techniques applied to Proton Exchange Membrane Fuel Cells (PEMFC) dynamically adapt to electrolyte hydration fluctuations, securing optimal power extraction with greater efficiency than Perturb-and-Observe (P&O), Fuzzy Logic Controller (FLC), and PSO methodologies33. These advancements underscore WOA’s versatility in resolving nonlinear, multi-variable challenges across energy and mechanical systems. The Research gap of this study includes: Limitations of Traditional Controllers: Existing IHPS studies rely on PI, PID, FOPI, and FPI controllers, which face challenges in handling nonlinear system dynamics and severe grid disturbances. These controllers show slow transient recovery, increased frequency overshoot, and prolonged settling times, compromising system stability. Inadequate Handling of Diverse Disturbances: Prior research does not sufficiently address the combined impact of gradual fluctuations (e.g., solar irradiance) and severe grid anomalies (e.g., three-phase faults, load shedding), causing instability in IHPS. Lack of Adaptive Frequency Control: Many existing controllers do not adapt to varying renewable energy fluctuations and load changes, leading to poor frequency regulation and reduced system efficiency. Deficiencies in Power Coordination and Scalability: Conventional methods do not effectively coordinate power generation, storage, and demand, limiting overall system reliability and scalability for real-world applications. Underutilization of Intelligent Optimization in Control Tuning: Automated gain calibration for frequency controllers is underdeveloped, and no framework integrates nonlinear adaptive control with swarm-based optimization for dynamic tuning. Need for an Advanced Control Strategy: A novel approach is crucial for optimizing frequency regulation, transient stability, and operational robustness in IHPS. The integration of MRAC-FPI-WOA gives a promising answer by enabling adaptive tuning in real time and intelligent power coordination in IHPS. The contributions of this study include: Methodological innovations: Investigates the transient behavior and operational robustness of integrated PV-BATT-DEG power systems under both gradual environmental perturbations (e.g., incremental solar irradiance shifts) and severe grid anomalies (e.g., three-phase faults, abrupt load shedding). Proposes a load frequency control to synchronize power generation, storage, and demand in IHPS. This strategy strengthens inter-component coordination, adapts to real-time grid dynamics, and ensures voltage/frequency stability during fluctuating renewable outputs and load transitions. Develops a non-linear adaptive controller (MRAC-FPI-WOA). This innovation optimizes transient frequency recovery across diverse operating regimes, outperforming PI-PS0, PI-WOA and FPI-WOA controllers in damping oscillations and minimizing settling times. Enhances the technical feasibility of large-scale renewable adoption by mitigating frequency volatility in IHPS. This advancement aligns with global sustainability agendas, reducing fossil dependency while improving energy distribution reliability in decentralized grids. Algorithmic implementations: Proposes Beta-based MPPT technique, which enhances the tracking accuracy and dynamic performance of the PV system by adaptively controlling power extraction based on a novel intermediary variable (β), rather than relying solely on conventional power change methods. The WOA is integrated with the beta-based MPPT controller to enhance the total efficiency of the PV system. Leverages the PSO and WOA to automate gain calibration for proposed controllers. WOA effectively resolves nonlinearities and component interdependencies, ensuring the best dynamic response in variable operating conditions. Simulation/experimental findings: Demonstrates the MRAC-FPI-WOA’s superiority through rigorous metrics: lower maximum overshoot (%(:{text{M}}_{text{p}})), and trough undershoot (%(:{text{M}}_{text{u}text{s}})) at lower frequencies, faster settling time ((:{text{T}}_{text{s}})), and a decrease in the integral of time-weighted absolute error (ITAE) in contrast to benchmarks. These results validate its capability to sustain grid stability during both minor and catastrophic disturbances. This paper’s remaining sections are arranged as follows: This paper systematically explores the design and control of IHPS components PV systems, DEG, and BATT in “Modeling of islanded hybrid power system“, proceeding to evaluate four frequency control strategies, including MRAC-FPI-WOA, FPI-WOA, PI-WOA, and PI-PSO controllers in “Frequency Control“. A detailed simulation-based analysis in “Results and discussion” compares controller performance under seven scenarios, including three-phase faults, step/ramp/random solar irradiance fluctuations, as well as abrupt load changes and composite disturbances. Cases 3 (step irradiance) and 6 (sudden load shift) are tested concurrently to assess robustness under hybrid stresses. The study concludes in “Conclusions” that the MRAC-FPI-WOA controller, enhanced by metaheuristic tuning, outperforms conventional methods in maintaining frequency stability and power quality across all disturbances, underscoring its potential to enhance HPS resilience in real-world applications characterized by renewable intermittency and operational uncertainties. This research undertaking centers its analytical scope on the architectural design and functional dynamics of Alternating current (AC) IHPS, integrating multiple distributed energy resources, including DEG, PV, AC consumer loads, and advanced BATT solutions. Figure 1 delivers a refined schematic overview of the IHPS infrastructure, emphasizing the interconnection of the DEG to the primary AC distribution backbone through sophisticated power electronic interfaces. These components perform dual critical functions: harmonizing the phase and frequency characteristics of disparate AC power sources while enabling efficient conversion of Direct Current (DC) electricity harvested from solar panels into HPS-compatible alternating current waveforms. The BATT incorporates a bidirectional power conversion apparatus, engineered to transition seamlessly between AC-to-DC operational modes during energy accumulation cycles and DC-to-AC modes during discharge phases. This dual functionality not only stabilizes the HPS against voltage fluctuations and transient load imbalances but also enhances operational flexibility during system upkeep or component servicing. This comprehensive framework underscores HPS’s resilience in maintaining uninterrupted power delivery while accommodating diverse energy inputs and dynamic load profiles. Block diagram of the proposed IHPS. This section introduces a detailed and robust simulation framework designed to be a high-performance PV system. The system architecture encompasses several critical elements: a 100-kilowatt solar panel array, a step-up DC-DC converter, a power inversion unit, and a voltage adjustment transformer. A methodically structured schematic diagram and computational model, illustrated in Fig. 2, offer a comprehensive and logically organized visualization of the entire configuration. Sunlight is harvested by a solar array and converted into DC electricity. To enable compatibility with standard power distribution networks, this DC output must undergo conversion to AC. This critical transition is eased by the inverter module, which transforms the unidirectional electrical flow into a three-phase AC output synchronized with grid specifications. Subsequently, a voltage-elevating transformer amplifies the AC voltage to match the grid’s operational requirements, ensuring seamless energy transfer. Each component operates synergistically: the Boost converter optimizes the DC voltage from the solar panels to maximize efficiency, the inverter ensures waveform compatibility with HPS standards, and the transformer bridges voltage disparities to enable stable power injection. This integrated approach highlights the system’s capability to efficiently harness, process, and deliver renewable energy while adhering to technical and operational benchmarks for grid integration34,35. Schematic of a Solar PV System. Various mathematical representations describing the functionality and efficiency of solar panels have been extensively documented in previous studies. For real-time simulation, it is necessary to develop an equivalent circuit model of PV cells. Among the different approaches, the single-diode model is the most widely adopted by researchers. This circuit configuration comprises, at a minimum, four key elements: a photocurrent source ((:{I}_{ph})), a diode (D), a shunt resistance ((:{R}_{sh})), and a series of resistance ((:{R}_{ser})). Based on the equivalent single-diode model of a PV cell depicted in Fig. 3, the output current ((:{I}_{out})) can be expressed mathematically in the following way36,37. Where(::left({N}_{P}right)) is the number of PV cells arranged in parallel, ((:{I}_{rs})) is The PV cell’s reverse leakage current, (q) is the electric charge of an electron,(:{(V}_{out})) is the cell’s output voltage, (A) is the diode ideality factor, (K) is the Boltzmann constant, (T) is the temperature measured in Kelvin, (:{(N}_{S})) is the total PV cells wired in a series connection,(:{:(text{I}}_{text{s}text{c}})) is the short-circuit current, (:{(k}_{i})) is the short circuit current factor, (:left({T}_{r}right)) is the cell reference temperature and (E) is the solar irradiance. Schematic representation of a basic diode-based model used for PV solar cells. Figure 4(a) and Fig. 4(b) depict the I-V and P-V characteristics of the PV cell, derived from a MATLAB-based computational model. These findings provide critical insights into the operational dynamics of the solar module under fluctuating irradiance scenarios, revealing how variations in solar intensity influence electrical output characteristics such as Maximum Power Point (MPP), open-circuit voltage (:{(V}_{oc}), and (:{I}_{sc})). The simulations show the nonlinear relationship between irradiance levels and energy conversion efficiency, emphasizing the importance of adaptive control strategies for optimizing solar harvesting in real-world environmental conditions. (a) I-V curve and (b) P-V characteristics of solar cells at varying irradiation levels. A basic DC-DC boost converter is employed to deliver power from the PV to the DC link and the inverter once the matching condition between them is met. This matching is achieved by applying a suitable duty cycle (ranging between 0 and 1). The converter’s switching element, typically an IGBT, is regulated using a PWM signal. Figure 5 displays the Simulink model layout of the boost converter. The mathematical relationships governing the converter’s input and output parameters are expressed through the following Eqs35,36. Here, the input and output voltages, along with the duty cycle, are represented as(:{::(V}_{o:}), (:{V}_{in}), and D), respectively. The roles of the boost converter’s inductor (L) and capacitor (C) elements are specified as follows35,36: Where ((:f)) is the frequency, (:(varDelta:I) and (:varDelta:V)) are the current and voltage ripple. Circuit diagram of a boost converter. The β-MPPT method involves observing an intermediate variable called ((:beta:)), rather than directly tracking power variations, as outlined in Eqs. (7) and (8)36,37. Here, (:left({I}_{pv}right)) is the output current, (C) is the diode constant, and (N) is the total count of solar cells contained in the module. This method uses a hybrid step-size strategy, applying a variable step during dynamic changes and a fixed step during stable operating conditions. As outlined in Fig. 6, the algorithm begins by continuously observing voltage and current values to compute the intermediary beta parameter. If the calculated beta lies within a designated threshold range ((:{beta:}_{min}) to (:{beta:}_{max})), the system is in a steady state, and a fixed step is applied. If beta falls outside this range, the algorithm identifies a transient phase and switches to a P&O approach. In this stage, the variable step size, denoted as ΔD, is adjusted based on a reference parameter called (:{(beta:}_{g})), which is defined mathematically in Eq. (9)36,37. Where (F) is the scaling factor. Flow chart of β-MPPT. The WOA discussed in Sect. 4 is integrated with the beta-based MPPT controller to enhance the total efficiency of the PV system. Within this hybrid framework, the scaling factor (F) is essential for adaptively regulating the step size (∆D) during the dynamic response phase of the Beta MPPT method. Selecting the perfect value for (F) is key to achieving: Rapid tracking of the Maximum PowerPoint (MPP). Minimized fluctuations during steady-state operation. Enhanced performance across various levels of sunlight and temperature conditions. Since the scaling factor (F) significantly affects MPPT efficiency but does not have an exact analytical expression, a metaheuristic optimization method can be applied to find its best value. The WOA offers a reliable control mechanism across various load scenarios and system parameters. This enhances both the flexibility and resilience of the control framework, ensuring that the Beta MPPT method consistently performs at its best under changing operational conditions. The objective function aims to find the ideal value of the scaling factor in a way that enhances power extraction efficiency (η) while simultaneously reducing both convergence time (CT) and Steady-State Oscillations (SSO). The goal is to minimize J(F) and obtain the best value of the scaling factor as outlined in Fig. 7. Where: MPPT Efficiency (η) is expressed as the ratio of the power obtained using the MPPT method ((:{P}_{MPPT})) to the ideal power ((:{P}_{ideal})). (SSO) is the Root Mean Square (RMS) value of the power fluctuations in the steady state. CT refers to the duration needed for the system to reach 98% of the (:{text{P}}_{text{i}text{d}text{e}text{a}text{l}}). (W₁, W₂, and W₃ ) are the weighting coefficients assigned to balance the impact of each parameter in the optimization process. Flow chart of the WOA to calculate the best value of the scaling factor (F). As illustrated in Fig. 8, the control framework of the voltage source inverter (VSI) includes two inner loops for managing current and two outer loops for managing voltage. The d-axis current ((:{text{I}}_{text{d}})) controls active power, which directly influences the DC bus voltage. On the other hand, controlling the q-axis current ((:{text{I}}_{text{q}})) allows for the regulation of reactive power, thus stabilizing the AC load voltage. The PI controller is employed to evaluate and enhance the dynamic response of the external voltage regulation loops on the DC and AC sides3,21. The mathematical expressions governing the VSI voltage are outlined in Eq. (11). To operate in the (dq) rotating reference frame (synchronous frame), the original three-phase (abc) signals are converted using transformation matrices, as described in Eq. (12). Assume that (:({V}_{as}), (:{V}_{bs}), (:{V}_{cs})) are the phase voltages produced by the VSI, and (:{(I}_{as}), (:{I}_{bs}), (:{I}_{cs})) correspond to its output currents. The filter’s resistance and inductance are denoted by (:{(R}_{f}) and (:{L}_{f})) respectively. (:{(V}_{aL}), (:{V}_{bL}), (:{V}_{cL})) are the voltages across the connected load. In the synchronous dq reference frame, (:({V}_{dqs}), (:{V}_{dqL}), (:{I}_{dqs})) are the inverter’s output voltages, the load-side voltages, and the inverter output currents, respectively. According to the described approach, the control of reactive power is managed through the q-axis current component, as detailed in Eq. (13), while the regulation of active power is managed through the d-axis current, as specified in Eq. (14)3,21. Here, (:{(text{Q}}_{s}) and (:{text{P}}_{s}):)are the delivered reactive and active power, respectively. The responses generated by the current controllers aligned with the d-axis and q-axis are computed using the expressions provided in Eqs. (15) and (16)3,21. VSI control. The integration of electrochemical storage units, such as lithium-ion battery banks, plays a pivotal role in HPS incorporating variable RES like PV arrays. These storage systems address imbalances between electricity production and consumption that arise from rapid fluctuations in solar insolation. During periods of diminished solar generation, when PV output falls short of the inverter’s target power level, the battery discharges to supplement load requirements38,39. Conversely, when PV generation exceeds demand, surplus energy is stored within the battery for next use. Solar installations inherently cease operation during nocturnal intervals due to the absence of sunlight40,41. Here, BATT synergizes with DEG to enhance system reliability and cost-effectiveness compared to standalone DEG configurations, reducing fuel consumption and operational expenses. The operational framework of the BATT, illustrated in Fig. 9, is governed by critical performance metrics including terminal voltage, energy capacity, and charge retention level State of Charge (SOC). The battery is mathematically represented as a tunable voltage source paired with an internal impedance component. Where (:{(text{C}}_{text{R}}) ) is the rated capacity and (:left({text{I}}_{text{B}text{A}text{T}text{T}}right)) is terminal current flow. Additional governing equations account for electrochemical reactions, gas evolution phenomena, thermal dynamics, and voltage-current relationships. Key variables include (:{text{V}}_{text{B}text{A}text{T}text{T}}) (battery terminal potential), (:{text{I}}_{text{R}}) (internal reaction current), (:{text{I}}_{text{G}}) (parasitic gassing current), and (:{text{T}}_{text{B}text{A}text{T}text{T}}) (operating temperature). Battery Model. The battery management strategy enforces specific operational constraints to ensure safe and efficient usage. Firstly, it restricts both the charging and discharging power levels, ensuring they do not exceed the maximum threshold specified by Eq. (17). Secondly, as outlined in Eq. (18), it regulates the battery’s SOC, keeping it within acceptable boundaries to avoid risks associated with overcharging or excessive depletion38,39,40,41. In the proposed system, batteries are utilized to mitigate the effects of the intermittent nature associated with PV sources. Due to their high energy density, batteries can deliver power at nearly constant voltage when their charging and discharging cycles are appropriately managed. The modeled battery is integrated into the DC link through a bi-directional DC-DC converter, as illustrated in Fig. 10. This converter facilitates the charging and discharging of the battery while maintaining the DC link voltage at 500 volts. When the battery supplies power to the microgrid, the converter operates in boost mode; conversely, when it absorbs power from the grid or PV panels, it operates in buck mode. The control loop regulates the DC link voltage by adjusting the duty cycle of the bi-directional DC-DC converter. It continuously measures the DC link voltage, compares it to a reference value, and processes the error through a voltage mode compensator to determine the necessary duty ratio. This control approach is agnostic to the direction of power flow and generates appropriate switching signals for the buck and boost operations. As shown in Fig. 11, an intelligent controller determines the operational mode and transmits the control pulses to a designated semiconductor switch. The decision to operate the converter in a buck or boost mode is based on the command signal received from the HPS. In the absence of a regulation signal, the battery’s SOC determines whether the converter should operate in buck mode to facilitate charging. Bi-directional DC-DC converter. Battery controller. The DEG assumes a crucial role as a backup power solution, particularly in scenarios where RES such as PV is insufficient due to intermittent availability or environmental factors. Additionally, the system activates in island mode when the main grid experiences instability, such as voltage sags, frequency deviations, or unforeseen disconnections. In this isolated operational state, the DEG autonomously sustains power supply to critical loads, preventing blackouts and enabling seamless transitions until grid conditions stabilize or renewable generation resumes. This dual functionality underscores the DEG’s importance in hybrid energy systems, bridging gaps between renewable intermittency and grid reliability while ensuring uninterrupted electricity access during emergencies42,43. The DEG system illustrated in Fig. 12 is composed of multiple interconnected elements designed to ensure reliable power generation and grid stability. At its core, the system includes a governor mechanism for the diesel engine, an excitation system, and a synchronous machine integrated with the engine. The governor operates through a closed-loop feedback control strategy, which continuously monitors and adjusts the engine’s rotational speed. By dynamically aligning the engine’s output with a predefined reference speed, the governor guarantees the stabilization of the electrical grid’s frequency, even under fluctuating load demands. This precision in speed regulation is critical for maintaining synchronization between the generator and the grid, thereby preventing disruptions in power quality. Diesel Engine Generator model. The primary objective of stabilizing an islanded AC HPS lies in regulating the electrical supply to preserve system frequency at its predefined operational standard. This process hinges on frequency stability management, which entails dynamically modulating generator output levels to equilibrate power consumption needs while sustaining consistent grid oscillations. Within such systems, the cumulative energy contribution from distributed resources—comprising DEG, PV, and BATT—must collectively satisfy load requirements, as expressed by the relationship: Given the inherent variability of PV generation due to weather-dependent intermittency, this analysis prioritizes DEG as the primary actuator for frequency correction. The control framework compensates for deviations caused by fluctuating loads and PV generation by adaptively scaling DEG output. Conventional PI regulators remain widely adopted for such stabilization tasks, while FPI systems introduce rule-based adaptability, enhancing responsiveness to dynamic operational shifts. To address limitations in existing hybrid energy systems, this work proposes an MRAC-FPI-WOA framework, which synergizes adaptive reference tracking with fuzzy logic to optimize disturbance rejection across diverse instability scenarios. PI-PSO, PI-WOA, and FPI-WOA architectures have proved efficacy in grid frequency management, yet the MRAC-FPI-WOA hybrid appears as a superior solution, using real-time parameter adaptation to maintain precision under abrupt load transitions, resource volatility, and compound disruptions. This innovation underscores the critical need for advanced control paradigms in modernizing HPS resilience against the uncertainties of renewable integration. The study specifically examines the PI controller’s effectiveness in maintaining system frequency stability and enhancing proposed IHPS operational performance, utilizing a control law expressed as (Eq. 20), with particular focus on its PI controller dynamic response characteristics and stabilization capabilities under varying load conditions4. This equilibrium enables accelerated convergence and superior precision compared to conventional optimization frameworks. By defining frequency control as an optimization problem, the ITAE performance metric can be minimized44,45. Where (t) is time, while e(t) is the deviation between (:{F}_{m}:)and (:{F}_{ref}). The system configuration depicted in Fig. 13 presents the closed-loop control structure employing the PI-PSO controller. PSO is popular for its simplicity and fitness-based approach, effective for diverse optimization problems. However, it risks premature convergence due to declining swarm diversity. The methodology incorporates three fundamental components46: Individual Best ((:{:P}_{pest:})): The optimal solution encountered by particle (i) during its search history. Global Best ((:{:g}_{pest:})): The most favorable solution discovered by the entire particle collective. Dynamical Update Rules: Governing equations directing particle movement through the solution space. The particle’s velocity vector is modified following Eq. (22), while its positional coordinates are recomputed via Eq. (23) through vectorial addition of the updated velocity to its prior location47. The PSO algorithm updates each particle’s velocity and position through three key components: (1) an inertia term ((:{:wv}_{id})) that preserves momentum from previous movements, (2) a cognitive component ((:{:r}_{1}{C}_{1}left({:P}_{pest,id}left(tright)-:{:X}_{iid}left(tright):right)))) that attracts particles toward their personal best positions ((:{P}_{pest,id})), and (3) a social component ((:{:r}_{2}{C}_{2}left({:g}_{pest,id}left(tright)-:{:X}_{id}left(tright):right)))) that guides particles toward the swarm’s global best solution ((:{g}_{pest,id})), where (w) represents the inertia weight, C₁ and C₂ are cognitive and social learning rates, respectively, and (r1,r2) are random numbers that maintain stochastic exploration. This balanced combination of individual experience (cognitive) and collective knowledge (social) enables effective search-space exploration while progressively converging toward optimal solutions. Figure 14 illustrates the algorithm’s operational flowchart48. PI-PSO Controller-Based Control System Structure. PSO flowchart. PI-WOA controller illustrated in Fig. 15, for frequency stabilization. By framing the controller tuning process as an optimization problem, WOA dynamically minimizes frequency deviations through iterative adjustments to the gain values, ensuring robust adaptability to grid disturbances. This hybrid approach synergizes the simplicity of PI control with the intelligence of bio-inspired optimization, enabling enhanced precision in frequency regulation for modern power networks characterized by intermittent renewable integration and complex load dynamics. The methodology aims to elevate grid resilience, reduce oscillations, and maintain nominal frequency stability under heterogeneous operating conditions. PI-WOA Controller-Based Control System Structure. WOA technique is a robust nature-inspired computational method modeled after the foraging strategies of humpback whales. It shows exceptional ability in addressing intricate optimization problems by harmonizing the search for novel solutions (exploration) with the refinement of existing ones (exploitation)49,50. Figure 16 illustrates the flowchart of the WOA, which can be mathematically expressed using the following Eqs49,50. The symbols X(t), (:{X}_{p}left(tright)), and (:{X}_{r}left(tright)), correspond to the position vectors of the whale, prey, and random whale, respectively. (t) is the current iteration. (A and C) are the coefficient vectors. Over the number of rounds, (a) constantly decreases linearly from 2 to 0. The random integer (l) is between − 1 and 1, the random vector (r) is between 0 and 1, the (p) is the probability number ε [0, 1], and the constant that determines the spiral logarithmic form is represented by (b). Figure 17 demonstrates the convergence behavior of the objective function for both optimization methods, with Table 1 detailing the corresponding algorithmic parameters and optimized PI controller gains obtained through WOA and PSO implementations. WOA flow chart. Convergence of the objective function. This research explores the FPI-WOA controller, illustrated in Fig. 18, as a hybrid control strategy that merges essential aspects of both FLC and PI-WOA control frameworks, aiming to enhance the capabilities of the PI controller by incorporating the advantages of FPI control. FLC outperforms classical methods in complex power systems due to its adaptability to nonlinearities and uncertainties without precise modeling. They maintain robust performance amid variable conditions like renewable generation fluctuations and load changes. Their rule-based heuristic approach enables intuitive tuning using operational expertise rather than complex math. Additionally, they are less sensitive to parameter variations than PID controllers, making them ideal for real-world applications with drifting system parameters2,20,21. As outlined in51,52 the fuzzy inference process consists of three main phases. The first step, fuzzification, transforms precise input values into fuzzy variables within their respective fuzzy sets. In this study, two input Errors (E), depicted in Fig. 19(a), and a Change in Error (CE), illustrated in Fig. 19(b), along with one output, shown in Fig. 19(c), are represented through triangular membership functions. Each input and output is characterized through a set of seven linguistic levels: NB (Negative Big), NM (Negative Medium), PB (Positive Big), PM (Positive Medium), PS (Positive Small), NS (Negative Small), and ZO (Zero). At the fuzzy logic rule inference stage, decisions are formulated through the integration of aggregation and implication techniques within the framework of fuzzy inference rules. The fuzzy rules, detailed in Table 2, can be linguistically described as follows: If both error (E) and (CE) are categorized as (PB), then the corresponding output is also classified as (PB). The parameters of PI-PSO, PI-WOA, and FPI-WOA controllers are displayed in Table 3. FPI-WOA Controller-Based Control System Structure. The MFs (a) E, (b) CE, (c) ΔD. To enhance the accuracy of the FPI-WOA controller, it has been integrated with MRAC to enhance its efficiency and adaptability. Implementing MRAC in IHPS offers significant benefits, particularly in managing the unpredictable nature of RES. By dynamically adjusting to changes in generation and load variations, MRAC strengthens frequency stability and voltage regulation, optimizing system performance through continuous tuning of control variables adjusted during real-time operating conditions. This integration results in a more robust and dependable energy system, enabling seamless RES integration while improving the overall efficiency and reliability of IHPS. Significant applications include maintaining stable output voltage in DC-DC converters used in IHPS53, implementing a tailored MIT-rule-driven MRAC for boost-type DC-DC converters54, and improving conventional droop-based regulation in marine power systems55. Additionally, MRAC has been applied in HPS to regulate the unified interphase power controller (UIPC)56, and develop a fractional-order MRAC control strategy to stabilize voltage and current in multi-source power configurations using DC-DC converters57. As depicted in Fig. 20, the MRAC-FPI-WOA controller consists of three main components: the FPI controller, the reference model, and the adjustment mechanism. MRAC-FPI-WOA Controller-Based Control System Structure. In this study, simulations were conducted using MATLAB Simulink as shown in Fig. 21 to introduce an MRAC-FPI-WOA controller designed to ensure frequency stability within the system while facilitating fundamental control processes. A comparative analysis was performed between the MRAC-FPI-WOA, FPI-WOA, PI-WOA, and PI-PSO controllers across various scenarios to analyze the controllers’ effectiveness. These scenarios are essential for a thorough assessment of performance. For example, Case 1, which focuses on a three-phase fault at Bus 2, offers insights into the system’s robustness across different network configurations. Case 2 analyzes a three-phase fault occurring at the center of the tie-line, further evaluating the system’s capacity to manage faults that impact multiple components at once. Additionally, Cases 3, 4, and 5 address fluctuations in solar radiation, including step changes, ramp changes, and random variations, respectively. These scenarios are crucial for understanding how dynamic solar input influences overall system performance, given the inherent variability of solar energy due to environmental factors. Case 6 introduces a rapid load change, testing the system’s responsiveness to sudden alterations in energy demand, a frequent challenge in practical applications. Finally, Case 7 merges Cases 3 and 6, running them simultaneously to evaluate how the system performs under various conditions of concurrent changes in solar radiation and load demands. This integrated approach offers a comprehensive understanding of how various disturbances interact and impact frequency regulation, ultimately informing more efficient design and control strategies for the proposed IHPS. This section presents an in-depth analysis that includes a variety of responses and numerical results, demonstrating the findings and implications of our research. The nominal specifications for the PV, DEG, BATT, and loads are detailed in Table 4. MATLAB/Simulink model. In this situation, a fault involving a three-phase short circuit at BUS 2 occurs, lasting 0.1 s. This fault starts at the terminals of the AC load after a time interval of 1 s and is identified by a fault resistance of 0.001 ohms. Figure 22(a) visually illustrates the output power generated by both the PV and DEG sources. Additionally, Table 5; Fig. 22(b) assess the overall efficiency of the system’s frequency by analyzing various control strategies, including the MRAC-FPI-WOA, FPI-WOA, PI-WOA and PI-PSO controllers. This evaluation considers several Key performance indicators like ITAE, (:{text{T}}_{text{s}}), %(:{text{M}}_{text{p}}), and %(:{text{M}}_{text{u}text{s}}:)during instances of three-phase faults. The findings from this case prove that the MRAC-FPI-WOA controller surpasses the PI-WOA, PI-PSO and FPI-WOA controllers in every evaluated aspect. Furthermore, Fig. 22(c) shows the voltage values existing in the system. System behavior in case 1. (a) Output power of the sources, (b) System Frequency, (c) System Voltage. In this case, a three-phase short circuit starts at the central point of the tie, lasting for a total duration of 0.11 s. This fault event starts at the terminals of the AC load after 2 s and shows fault resistance as low as 0.001 ohms. Figure 23(a) visually depicts the output power generated by both the PV and DEG sources. Meanwhile, Table 5; Fig. 23(b) provide an assessment of the system’s efficiency by examining various control methodologies, including the MRAC-FPI-WOA, FPI-WOA, PI-WOA and PI-PSO controllers. The evaluation process considers several important performance metrics, such as ITAE, %(:{text{M}}_{text{u}text{s}}), %(:{text{M}}_{text{p}}), and (:{text{T}}_{text{s}}), specifically during instances of three-phase faults. The results from this analysis confirm the enhanced effectiveness of the MRAC-FPI-WOA controller over other controllers in all evaluated performance aspects. Additionally, Fig. 23(c) illustrates the voltage values existing in the system. System behavior in case 2. (a) Output power of the sources, (b) System Frequency, (c) System Voltage. Figure 24(a) illustrates the stepped variation in solar irradiance over time. One must note that changes in solar radiation levels can significantly affect the frequency within the system. The implementation of the MRAC-FPI-WOA controller plays a vital role in ensuring effective frequency regulation under these varying conditions. When compared to PI-PSO, PI-WOA and FPI-WOA controllers, the MRAC-FPI-WOA controller demonstrates a higher level of accuracy in responding to abrupt changes in solar radiation, notably when efficiency is high and weather conditions shift rapidly. The performance efficiency is assessed using the control strategies, taking into account several key parameters, including %(:{text{M}}_{text{u}text{s}}), ITAE, (:{text{T}}_{text{s}}), %(:{text{M}}_{text{p}}). Table 5; Fig. 24(b) present an in-depth analysis of the IHPS frequency’s behavior in response to a step change. Furthermore, Fig. 24(c) visually represents the output power produced by both the PV and DEG sources. In this scenario, when solar radiation diminishes from 1000 to 800 W/m² after two seconds, the PV power decreases from 94 kW to 73 kW. This reduction in PV power generation prompts an increase in the power output from the DEG, which grows from 56 kW to roughly 70 kW to meet the energy demand. Conversely, when solar radiation declines further to 600 W/m² after an additional four seconds, while maintaining a constant ambient temperature, the PV power output declines from 73 kW to about 54 kW. In response, the DEG power generation escalates from 70 kW to approximately 84 kW to satisfy the demand. Additionally, when solar radiation increases from 600 to 900 W/m² at the six-second mark, PV power rises from 54 kW to about 82 kW, causing the DEG output to decline from 84 kW to roughly 63 kW. The proposed controller successfully stabilizes the system frequency, even amidst fluctuations in solar radiation levels. Lastly, Fig. 24(d) provides further insight by presenting the distribution of voltage across the system. System behavior in case 3. (a) Radiation is a step-changed profile, (b) Output power of the sources, (c) System Frequency, (d) System Voltage. Figure 25(a) illustrates the ramp-shaped trend of solar irradiance over a specific period. The MRAC-FPI-WOA controller plays a crucial role in ensuring efficient frequency control. Compared to other controllers, the MRAC-FPI-WOA controller proves a significantly higher level of accuracy and responsiveness to ramp variations in solar irradiance levels. Figure 25(b) depicts the output power of the sources. As solar radiation decreases, there is a corresponding increase in the DEG power. Alternatively, as the solar radiation increases, the DEG power also rises to accommodate the changing power consumption needs. To evaluate the efficiency of the system, A comparative analysis is performed on the MRAC-FPI-WOA, PI-WOA, PI-PSO and FPI-WOA controllers. Table 5, along with Fig. 25(c), provides a comprehensive overview of the controlled response of the system frequency under ramp shifts in solar irradiance. The MRAC-FPI-WOA controller ensures stable control of system frequency, even in the face of ramp variations in solar radiation. This proves the controller’s ability to sustain stable performance across different conditions. Moreover, Fig. 25(d) presents additional further by illustrating the voltage levels across the system, further contributing to the general comprehension of the system’s performance. System behavior in case 4. (a) Radiation is a ramp-changed profile, (b) Output power of the sources, (c) System Frequency, (d) System Voltage. Figure 26(a) shows the erratic behavior of solar irradiance levels over a defined time. In these situations, the MRAC-FPI-WOA controller is crucial for ensuring effective frequency control. When contrasted with other controllers, the MRAC-FPI-WOA controller shows a notably greater degree of precision and responsiveness to unpredictable fluctuations in solar irradiance levels. Figure 26(b) illustrates the output power of the sources. As the intensity of solar irradiance declines, the DEG power grows proportionally. However, when solar radiation increases, the DEG power rises to match the fluctuating energy requirements. Table 5, along with Fig. 26(c), offers an in-depth examination of the system frequency behavior throughout instances of random fluctuations in solar irradiance. The MRAC-FPI-WOA controller successfully maintains the stability of the system frequency, even amidst unpredictable fluctuations in solar irradiance. This highlights the controller’s ability to offer consistent functionality across a range of conditions. Additionally, Fig. 26(d) offers additional insights by illustrating the system’s voltage levels, improving the overall comprehension of system’s operational performance. System behavior in case 5. (a) Radiation is a random-changed profile, (b) Output power of the sources, (c) System Frequency, (d) System Voltage. Figure 27(a) illustrates the power output from both the PV and DEG sources during instances of abrupt load changes. At the 2-second mark, there is a notable decrease of 18.3% in the demand for the AC load within the system, dropping from 120 kW to 98 kW. During this period, the power output from the PV systems remains unchanged at 94 kW, while the output from the DEG declines from 56 kW to 35 kW. At the 4-second mark, as depicted in Fig. 27(a), there is an increase of 11.2% in the AC load demand, rising from 98 kW to 109 kW. Throughout this time, the PV power continues to hold steady at 94 kW, while the DEG power rises from 35 kW to 44 kW to satisfy the additional energy requirements. Figure 27(b) and Table 5 present a detailed comparison of the performance of the MRAC-FPI-WOA, FPI-WOA, PI-WOA, and PI-PSO controllers in managing sudden changes in load, emphasizing the MRAC-FPI-WOA controller’s effectiveness in ensuring effective frequency regulation under these conditions. Furthermore, Fig. 27(c) provides a sequential representation of the system’s voltage measurements, offering additional insights into its operational dynamics. System behavior in case 6. (a) Output power of the sources, (b) System Frequency, (c) System Voltage. In this case, scenarios (3) and (6) are interconnected and run simultaneously. Figure 28(a) visually depicts the output power of the sources. When solar irradiance reduces from 1000 to 800 W/m² after two seconds, there is also a concurrent 18.3% reduction in the demand for AC load within the system, which drops from 120 kW to 98 kW. At precisely 2 s, the output from the PV systems reduces from 94 kW to 73 kW. This decline in PV power output, combined with the reduced load, leads to a decrease in power generation from the DEG, which falls from 56 kW to about 48 kW to meet the adjusted energy requirements. Subsequently, when solar radiation further decreases to 600 W/m² after an additional four seconds, there is an 11.2% increase in the AC load demand, rising from 98 kW to 109 kW. At this 4-second mark, the PV power drops from 73 kW to 54 kW. In response to this change, DEG’s power generation rises from 48 kW to 72 kW to fulfill the new demand. Additionally, when solar radiation increases from 600 to 900 W/m² at the six-second mark, the AC load demand within the system remains constant at 109 kW. The PV power rises from 54 kW to about 82 kW, resulting in decreased production from the DEG, which reduces from 72 kW to 62 kW. Table 5; Fig. 28(b) provide a comprehensive overview of the system frequency response. The system’s performance efficiency is assessed based on the MRAC-FPI-WOA, PI-WOA, PI-PSO and FPI-WOA controllers, considering several critical parameters, including (:{text{T}}_{text{s}}), ITAE, %(:{text{M}}_{text{p}}), and %(:{text{M}}_{text{u}text{s}}). Finally, Fig. 28(c) gives deeper insights into displaying the system’s voltage levels. System behavior in case 7. (a) Output power of the sources, (b) System Frequency, (c) System Voltage. This study proposes a robust technique for controlling the frequency of an IHPS, utilizing MRAC-FPI-WOA, FPI-WOA, PI-WOA, and PI-PSO controllers to maintain system stability amid disturbances. The findings highlight the substantial benefits of the MRAC-FPI-WOA controller compared to the FPI-WOA, PI-WOA, and PI-PSO controllers across multiple scenarios. For instance, in Case 1, during a three-phase fault for 100 ms at Bus2, the MRAC-FPI-WOA controller lowers %(:{text{M}}_{text{p}}) by 59.05%, %(:{text{M}}_{text{u}text{s}}) by 72.83%, (:{text{T}}_{text{s}}) by 32.07%, and ITAE by 34.81% compared to the PI-PSO controller. In Case 2, with a three-phase fault at the tie-line lasting 110 ms, similar improvements are observed, including lowering %(:{text{M}}_{text{p}}) by 57.47%, %(:{text{M}}_{text{u}text{s}}:)by 79.36%, (:{text{T}}_{text{s}}) by 40.9%, and ITAE by 78.08%, reinforcing the MRAC-FPI-WOA controller’s superior performance in dynamic situations when compared to the PI-PSO controller. In Case 3, MRAC-FPI-WOA showcases its superior adaptability under varying solar irradiance conditions. When irradiance drops from 1000 to 800 W/m², the controller significantly enhances performance by reducing overshoot by 100%, undershoot by 94.12%, settling time by 75.14%, and ITAE by 82.8%. A further decrease from 800 to 600 W/m² yields even better results, undershoot improved by 94.06%, overshoot cut by 100%, settling time improved by 78.05%, and ITAE reduced by 89.47%. Conversely, when solar radiation increases from 600 to 900 W/m², MRAC-FPI-WOA maintains strong performance, decreasing overshoot by 95.38%, undershoot by 100%, settling time by 83.96%, and ITAE by 92.24%. Furthermore, the MRAC-FPI-WOA controller proves improved dynamic responsiveness to ramp changes in solar radiation in Case 4, achieving reductions in %(:{text{M}}_{text{p}}), %(:{text{M}}_{text{u}text{s}}), (:{text{T}}_{text{s}}), and ITAE by 96.72%, 95.24%, 22.79%, and 89.69%, respectively. In addition, it also shows enhanced adaptability to random fluctuations in solar radiation in Case 5, consistently lowering %(:{text{M}}_{text{p}}), %(:{text{M}}_{text{u}text{s}}), (:{text{T}}_{text{s}}), and ITAE by 96.63%, 99.58%, 22.07%, and 95.23%, respectively. The MRAC-FPI-WOA controller also proves effective during load variations in Case 6, significantly improving dynamic performance when the load decreases by 18.3% from 120 kW to 98 kW, with reductions in %(:{text{M}}_{text{p}}) by 93.38%, %(:{text{M}}_{text{u}text{s}}) by 100%, (:{text{T}}_{text{s}}) by 55.19%, and ITAE by 83.08%. Likewise, with a load increase of 11.2% from 98 kW to 109 kW, the MRAC-FPI-WOA controller enhances performance by cutting %(:{text{M}}_{text{p}}) by 33.33%, %(:{text{M}}_{text{u}text{s}}) by 93.48%, (:{text{T}}_{text{s}}) by 77.24%, and ITAE by 86.79%. In Case 7, MRAC-FPI-WOA exhibits exceptional adaptability under varying operating conditions: when solar irradiance decreases from 1000 to 800 W/m² alongside an 18.3% load reduction (120 kW to 98 kW), it reduces overshoot by 92.45%, undershoot by 100%, settling time by 69.81%, and ITAE by 87.46%; during a further irradiance drop to 600 W/m² with an 11.2% load increase (98 kW to 109 kW), it achieves even better performance with 100% overshoot reduction, 93.94% undershoot reduction, 75.3% settling time improvement, and 88.22% ITAE reduction; and finally, when irradiance rebounds to 900 W/m² at a steady 109 kW load, it maintains superior control with 95.4% overshoot reduction, 100% undershoot suppression, 72.9% faster settling, and 90.4% lower ITAE, demonstrating consistent excellence across all test scenarios. The simulation results confirm that the MRAC-FPI-WOA controller effectively sustains system stability and quality by balancing generation and consumption across diverse operating conditions. While the current study demonstrates the controller’s effectiveness through comprehensive MATLAB/Simulink simulations, we acknowledge that real-time hardware validation, such as HIL (Hardware-in-the-Loop) and Processor-in-the-Loop (PIL) validation, would be necessary to fully verify its performance in practical implementations. Future work will focus on experimental validation using microgrid testbeds with actual power electronics interfaces, robustness testing under real-world communication delays and measurement noise, and comparative analysis with physical benchmark controllers. Additionally, we plan to integrate advanced control techniques, such as machine learning, to further improve adaptability and explore hybrid energy systems that incorporate additional renewable sources, with parallel development of hardware prototypes for field testing. All data generated or analyzed during this study are included in this published article. Artificial bee colony Alternating current Adaptive fractional order PI advanced sine cosine algorithm Battery storage Bat algorithm Bio-dynamic grasshopper optimization algorithm Coati optimization algorithm Cascaded tilted-FO derivative with filter Chaos quasi-oppositional SHO Crow-search algorithm Direct current Diligent crow search algorithm Diesel engine generator Dragonfly search algorithm Fuzzy-fractional order PID Logic Controller Model reference adaptive control-fuzzy proportional integral based whale optimization algorithm Proportional-integral-derivative-Tilt Piecewise Linear-Elliptic Particle swarm optimization Perturb and observe Photovoltaic Renewable energy sources Sea-horse optimization State of Charge Type-2 Fuzzy Cascade Tunicate search algorithm Tilt fractional order PID Whale optimization algorithm P-N junction ideality factor Solar irradiance Battery rated capacity Short-circuit current Battery internal reaction current Parasitic gassing current Battery current PV cell’s Reverse leakage current Fractional-Order PID Fractional-Order PI Fuzzy Proportional-Integral Genetic Algorithm Grey Wolf Optimizer Hybrid Adaptive Ant Lion Optimization Fractional-Order Proportional-Integral Islanded Hybrid Power System Improved Salp Swarm Optimization Model Predictive Control Maximum Power Point Tracking Maximum Power Point Model Reference Adaptive Control Opposition-based SHO Proton Exchange Membrane Fuel Cells Proportional-Integral Proportional-Integral-Derivative PV cell’s output current Photocurrent source Boltzmann constant Short-circuit current coefficient Number of PV cells connected in series Number of PV cells arranged in parallel Load power Diesel engine generator power Photovoltaic power Electron charge Series resistance Shunt resistance P-N junction temperature Battery operating temperature Cell reference temperature Settling time Battery terminal voltage PV cell’s terminal voltage Open-circuit voltage Maximum overshoot Maximum undershoot Elborlsy, M. 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Elborlsy, M. S., Hussien, A. E. A. & Ebied, M. A. An Intelligent MPPT Technique based on Fuzzy Controller Applied to Grid-Connected PV Systems in Temperature Fluctuations, 2023 3rd International Conference on Electronic Engineering (ICEEM), Menouf, Egypt, pp. 1–6, https://doi.org/10.1109/ICEEM58740.2023.10319534 (2023). Hamad, S. A., Ghalib, M. A., Munshi, A., Alotaibi, M. & Ebied, M. A. Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems. Sci. Rep.15 (1). https://doi.org/10.1038/s41598-025-91044-6 (2025). Bakundukize, A., Twizerimana, M., Bernadette, D., Pierre, B. J. & Theoneste, N. Design and modeling of PV power plant for rural electrification in Kayonza, Rwanda. J. Energy Res. Reviews. 7 (4), 31–55. https://doi.org/10.9734/JENRR/2021/v7i430197 (2021). Article Google Scholar Kanouni, B., Badoud, A. E., Mekhilef, S., Bajaj, M. & Zaitsev, I. 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Djebbri, S., Ladaci, S., Metatla, A. & Balaska, H. Fractional-order model reference adaptive control of a multi-source renewable energy system with coupled DC/DC converters power compensation. Energ. Syst.11 (2), 315–355. https://doi.org/10.1007/s12667-018-0317-5 (2018). Download references Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB). Process Control Technology Department, Faculty of Technology and Education, Beni-Suef University, Beni-Suef, Egypt Mohamed A. Ghalib, M. S. Elbrolsy & R. M. Mostafa Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Benha, Egypt H.E. Keshta Search author on:PubMedGoogle Scholar Search author on:PubMedGoogle Scholar Search author on:PubMedGoogle Scholar Search author on:PubMedGoogle Scholar Author Contributions: M. A: Validation, For-mal analysis, Writing – review & editing. M. S: original draft, Writing – review & editing. R.M: Formal analysis, Software, Supervision. H.E: Investigation, Formal analysis, Software. All authors reviewed the manuscript. Correspondence to Mohamed A. Ghalib. The authors declare no competing interests. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Reprints and permissions Ghalib, M.A., Elbrolsy, M., Mostafa, R. et al. Adaptive Control-based frequency control strategy for PV/ DEG/ battery power system during islanding conditions. Sci Rep15, 40405 (2025). https://doi.org/10.1038/s41598-025-19341-8 Download citation Received: Accepted: Published: Version of record: DOI: https://doi.org/10.1038/s41598-025-19341-8 Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article.
Suniva Inc., a U.S.-owned and -operated solar cell manufacturer, will invest $350 million to establish its first South Carolina manufacturing facility in Laurens, the company announced April 14. The investment at 1200 Commerce Blvd. is expected to create 564 jobs and Suniva’s 620,000-square-foot building will be used to produce advanced solar cells. “Since its founding in 2007, Suniva has championed U.S. leadership in solar energy manufacturing,” said Suniva CEO Tony Etnyre. “Solar is the fastest and most economical way to grow our nation’s energy supply — and at this critical juncture, access to energy will determine how America competes for generations to come. Our expansion in South Carolina means that renewable energy, made right here at home, will now do more than ever to secure that future.” Operations in Laurens are expected to be online in 2027.
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Partly cloudy early with increasing clouds overnight. Low 59F. Winds WSW at 5 to 10 mph.. Partly cloudy early with increasing clouds overnight. Low 59F. Winds WSW at 5 to 10 mph. Updated: April 14, 2026 @ 6:35 pm
LEWISBURG — The East Buffalo Township supervisors approved a feasibility study to determine the economic benefits of installing solar panels on the roof of the township garage. At Monday night’s public meeting, the supervisors said the study from the Pennsylvania Solar Center, a Pittsburgh-based nonprofit organization, will be at no cost to the township. The study is expected to take 15 days. Javascript is required for you to be able to read premium content. Please enable it in your browser settings. {{description}} Email notifications are only sent once a day, and only if there are new matching items. Sign up now to get our FREE breaking news coverage delivered right to your inbox. First Amendment: Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof; or abridging the freedom of speech, or of the press; or the right of the people peaceably to assemble, and to petition the Government for a redress of grievances. Your browser is out of date and potentially vulnerable to security risks. We recommend switching to one of the following browsers:
A map of the Clean Air Solar Farm proposals(Image: Clean Air Solar Farm) Fresh proposals for a 500MW solar farm near Beverley have been announced by renewable energy specialists and joint partners, PS Renewables and Ørsted Onshore. The proposed 'Clean Air Solar Farm' represents a revised version of the Kingfisher Solar Farm, which was first announced in January 2025. The new scheme features a revised site boundary and would generate sufficient electricity to power approximately 160,000 UK homes. It would make it one of the biggest planned, coming just a week after the Government gave the green light to what is set to become the UK's largest solar farm, rated at 800MW. The project would be spread across two sites near Beverley. A northern site would sit roughly three miles north of Beverley, to the east of the A164. Plans for this land were put before the public during a consultation in February 2025 under the Kingfisher Solar Farm name. The southern site would be positioned to the southwest of the A1079. The project would tie into the planned Wanlass Beck substation, which forms an extension of the existing Creyke Beck substation. Given the volume of electricity the Clean Air Solar Farm would produce, it is classified as a Nationally Significant Infrastructure Project (NSIP). This means the decision on whether to grant final consent for the development would rest with the Secretary of State for Energy Security and Net Zero, rather than the local council, as would ordinarily be the case with planning matters. A planning ruling is anticipated in 2028. Should consent be granted, the Clean Air Solar Farm is projected to be operational by 2033, reports Hull Live. Randall Linfoot from the Clean Air Solar Farm team said: "Since we first introduced Kingfisher Solar Farm, there have been significant changes. The project was originally developed to make use of spare grid capacity associated with Ørsted's Hornsea 4 offshore wind project. Since then, Hornsea 4 has returned to development, and we have been following the statutory National Energy System Operator (NESO) Gate 2 process to secure a new grid connection. The project would include two sites near Beverley(Image: Clean Air Solar Farm) "New project partners PS Renewables are a highly experienced, UK renewable energy developer. Together with Ørsted Onshore, the project proposals and site boundary have since evolved. To reflect these collective changes and a fresh start to our proposal, we took the decision to rename to Clean Air Solar Farm. "Clean Air Solar Farm will be able to power approximately 160,000 UK homes, making a significant contribution toward meeting the country's ambitious plans to achieve net-zero carbon emissions by 2050. We are committed to making a long-term, positive impact with these proposals and feedback from the community is critical. We would like to thank everyone for the time taken to engage with Kingfisher Solar Farm. All the feedback received to date has been carefully reviewed and fed into our plans." A series of Public Information Days regarding the scheme will take place in the local area during June 2026. These drop-in sessions will give local communities near the site an opportunity to discover more about the proposals, speak directly with the project team and share their views on the developing design. This will be followed by a consultation period in Autumn 2026. Drop in sessions take place in June in Lockington, Beverley and Walkington. To find all the planning applications, traffic diversions, road layout changes, alcohol licence applications and more in your community, visit the Public Notices Portal. At Reach and across our entities we and our partners use information collected through cookies and other identifiers from your device to improve experience on our site, analyse how it is used and to show personalised advertising. You can opt out of the sale or sharing of your data, at any time clicking the "Do Not Sell or Share my Data" button at the bottom of the webpage. Please note that your preferences are browser specific. Use of our website and any of our services represents your acceptance of the use of cookies and consent to the practices described in our Privacy Notice and Terms and Conditions.
Advertisement Plug-in solar panels are a cheaper, simpler alternative to professionally installed panels. But can they really reduce energy bills and are they safe? Matthew Sparkes investigates By Matthew Sparkes 1 April 2026
Plug-in solar panels can easily be installed on balconies
imageBROKER.com / Alamy Stock Photo
Plug-in solar panels can easily be installed on balconies imageBROKER.com / Alamy Stock Photo The global surge in solar power is nothing short of extraordinary. Over the past 15 years, the cost of installing a solar system has dropped by 90 per cent and the technology now accounts for over 80 per cent of the world’s new electricity capacity each year. So when oil and gas prices soared as a result of the ongoing conflict in the Middle East, solar was the obvious place to look for relief for many countries. But in the UK, it wasn’t just a case of advocating for more of the same – the UK government has said that it will legalise a currently illegal form of solar. So-called plug-in kits will be available “within months” from high-street shops and supermarkets. These kits are DIY in nature, you simply bring home some panels, place them in a sunny spot and plug them in. There’s no cost of installation and you can start using the sun’s energy to power your home immediately. If you move, just pack up your panels and bring them with you. Solar energy has seemingly been made even cheaper and available to even more people. Many countries have already taken to plug-in solar and there are reasons to be excited about it on a global scale, but can it really help alleviate energy price rises? How cheap is it? And is it actually safe? Despite the rapid decreases in cost, installing a traditional solar system isn’t cheap. For an average UK home, estimates for a 4-kilowatt system to cover most energy needs is around £7000. In the US, the average home uses roughly double the energy and the cost of installing a solar system to cover it is around $20,000. These costs include having the panels professionally mounted and a registered electrician installing the system and making alterations to the electricity meter so that excess power can be sold back to the grid – lowering bills or perhaps even generating profit.
Read more Why solar power is the only viable power source in the long run Free newsletter The best of New Scientist, including long-reads, culture, podcasts and news, each week. Plug-in solar is a simpler proposition. The kits are smaller than a full-scale install, so you might expect to purchase an 800-watt system for around £400 and hope for it to cover something like 20 per cent of an average UK home’s energy needs. Installation is free because it is nothing more than tying the panel to balcony railings, a garden fence or a garage roof and plugging a cable into a wall socket. Once you’re plugged in, you can start using any energy that is generated. With plug-in solar, excess energy ends up back in the grid but without a professional installation you can’t earn money from it. “Ultimately that energy just gets used by the next-door neighbour,” says Mark Golding at UK solar panel installer Spirit Energy. Plug-in solar is already an established technology outside the UK. More than a million plug-in solar systems were registered in Germany as of July last year, for instance. Estimates suggest that they cumulatively have capacity of between 1.6 and 2.4 gigawatts there – enough to simultaneously boil half a million kettles. Germany is the only country attempting to track plug-in solar in any meaningful way, so statistics are hard to come by. But one estimate says that there could be as many as 5 million kits in use across Europe. Plug-in solar is only a small fraction of the overall energy mix, but for individuals, it could take the sting out of bills and cumulatively boost a country’s renewable-generation ability. Jan Rosenow at the University of Oxford says that uptake could soar if governments keep legislating to allow people to install their own panels. “While individual systems are small, their aggregate impact is becoming meaningful, both in terms of distributed generation and consumer engagement in the energy transition,” says Rosenow. Plug-in panels are mostly outlawed in the US at present, but Utah became the first state to legalise them last year and many states have similar legislation in the works. Cora Stryker at Bright Saver, a pro-solar non-profit in the US, says that outside of Utah, people have to go through the same amount of admin to install a few solar panels at home as somebody would to construct a 20-megawatt solar farm – a situation that she says is “patently ridiculous”. Stryker hopes that plug-in solar can alleviate financial hardship, help slow climate change and act as the thin end of the wedge to bring the US up to speed on renewable power. “This is the watershed moment, the tipping point toward a world where the dirt-cheap cost of renewables is actually passed on to the consumer,” she says. Bright Saver estimates that 24 million US households will use a plug-in solar system by 2035. But, despite the already widespread use, there is worry among some experts about the safety of plug-in kits. Mark Coles, the head of technical regulations at the UK Institution of Engineering and Technology (IET), recommends that before anyone buys a plug-in solar kit they have the wiring in their house checked for safety first. And, even after that, the organisation has identified areas of concern. One issue surrounds residual current devices (RCDs), the safety devices found in fuse boxes that sense when current is leaking to ground – a sign of electrocution or a short circuit – and almost instantaneously cut power. Most RCDs used in the UK aren’t suitable for current flowing in both directions and so could malfunction. In the US, the set-up is different but there are similar problems. One reason why Germany has managed to move so quickly is that by coincidence it standardised bi-directional RCDs in the 1980s. Another worry of the IET’s is what happens if there are multiple kits and a power cut. In theory the plug-in kits should also shut down in order to prevent “islanding” where one house’s power stays live. But if they’re still generating power then they could deceive each other into thinking the grid is live and keep running. The problem then is that power can jump past the fuse box and electrocute maintenance workers in the area fixing the outage. “That’s putting those people in danger,” says Coles. “It kind of goes against the concept of ‘just buy this and plug it in’, but in reality we are concerned that there’s a public safety risk here.” Coles agrees that plug-in solar could bring enormous benefits but wants to ensure manufacturers can prove their systems will behave safely, even in unusual scenarios. New Scientist put the IET’s safety concerns to the UK Department for Energy Security and Net Zero and a spokesperson said: “Our tests have shown plug-in solar is safe to use on UK domestic circuits. All products will need to meet UK product safety standards, and we have commissioned an independent study to inform further regulations ahead of their sale.” Stryker says that, given the catastrophic impact of climate change and soaring energy costs placing many into fuel poverty, the greatest risk to consumers is inaction. She argues that people will adopt technologies like this regardless of whether they are officially sanctioned and regulated, so the pragmatic approach is to help people do it as safely as possible. “Solar is the cheapest energy on the planet, full stop. It’s actually the cheapest energy humanity’s ever produced,” she says. Topics: Advertisement Receive a weekly dose of discovery in your inbox. We’ll also keep you up to date with New Scientist events and special offers. Explore the latest news, articles and features News Features Analysis News Trending New Scientist articles Advertisement Download the app
As global solar demand surges, LONGi’s leadership in high-efficiency panels positions it for growth that could benefit your portfolio. Here’s why it matters for investors in the United States and across English-speaking markets worldwide. ISIN: CNE100001FR6 You might be wondering if LONGi Green Energy Technology stock (CNE100001FR6) offers a compelling play on the renewable energy boom, especially as solar power gains traction worldwide. This Chinese leader in photovoltaic manufacturing dominates with cutting-edge silicon wafers, cells, and modules, powering installations from rooftops to massive utility-scale farms. For you as an investor in the United States and English-speaking markets, LONGi’s scale and technology edge make it a key name to watch amid the push for clean energy independence. Updated: 14.04.2026 By Elena Vasquez, Senior Markets Editor – Exploring how global solar giants shape investor opportunities in renewables. LONGi Green Energy Technology builds its business around a fully vertically integrated model in the solar supply chain, from polysilicon production to finished modules. This approach allows the company to control costs, ensure quality, and scale efficiently as demand rises. You benefit from this structure because it translates to competitive pricing that accelerates solar adoption globally. The model emphasizes monocrystalline silicon technology, which delivers higher efficiency rates than alternatives like polycrystalline. LONGi invests heavily in R&D to push cell efficiencies beyond 25%, setting industry benchmarks. This focus on technological leadership supports steady margin expansion even in commoditized segments. Revenue streams diversify across modules, wafers, and cells sold to project developers, utilities, and distributors. Overseas sales, particularly to Europe and emerging markets, now form a growing portion, reducing reliance on domestic demand. For your portfolio, this global footprint hedges against regional policy shifts. Official source All current information about LONGi Green Energy Technology from the company’s official website. LONGi’s flagship products include high-efficiency PERC, HJT, and TOPCon solar cells and modules, tailored for residential, commercial, and utility applications. These innovations capture more sunlight per square meter, lowering levelized cost of energy (LCOE) for end-users. You see this edge in markets where space-constrained installations demand top performance. Key markets span China, Europe, the Americas, and Asia-Pacific, with modules powering gigawatt-scale projects. The company’s Hi-MO series modules lead in bifacial designs, reflecting ground light for extra yield. This product superiority helps LONGi secure long-term supply contracts with major EPC firms. Competitively, LONGi holds the largest market share in silicon wafers and modules, outpacing rivals through capacity expansions and cost discipline. Unlike less integrated peers, its upstream control buffers against raw material volatility. For you, this moat supports sustained profitability in a price-sensitive industry. Market mood and reactions The solar industry benefits from plunging costs, policy incentives, and net-zero commitments driving installations past terawatt milestones annually. Technological advances like larger wafers (210mm format) further cut BOS costs, where LONGi leads. You can expect these tailwinds to propel demand for its high-end products. Energy storage pairings and green hydrogen projects expand addressable markets beyond pure PV. Supply chain localization efforts in Europe and the US create opportunities for LONGi partnerships. This dynamic positions the company to capture value as renewables integrate into grids. Global capacity auctions and corporate PPAs underscore the shift to utility-scale solar, LONGi’s sweet spot. Rising electricity prices amplify ROI for solar assets, benefiting module suppliers. For your investments, these drivers signal multi-year upside. In the United States, LONGi’s modules support the IRA-fueled solar surge, with domestic projects increasingly sourcing efficient imports despite tariffs. You gain indirect exposure to America’s 30%+ annual PV growth without pure-play US firm risks. English-speaking markets like Australia, with world-leading rooftop penetration, rely on LONGi tech for affordability. UK and Canadian investors benefit from LONGi’s role in offshore wind-solar hybrids and community energy schemes. The company’s ESG credentials align with mandatory disclosures in these regions. This makes LONGi a diversified renewable bet for your portfolio amid energy transition policies. Supply agreements with US developers highlight LONGi’s navigation of trade barriers via third-country manufacturing. For you tracking global clean energy, it offers scale unmatched by smaller players. Watch how US content rules evolve to impact sourcing. Read more More developments, headlines, and context on the stock can be explored quickly through the linked overview pages. Reputable analysts from banks like Goldman Sachs and JPMorgan highlight LONGi’s market leadership and cost advantages as key strengths, with recent notes emphasizing its resilience amid industry consolidation. Coverage often points to robust demand forecasts supporting capacity utilization above 90%. However, some caution on pricing pressures in oversupplied segments, recommending focus on premium products. Consensus leans toward positive outlooks tied to global solar deployment targets, though valuations reflect execution risks. Institutions track LONGi’s expansion into n-type cells as a margin catalyst. For you, these views underscore the stock’s role in renewable portfolios, balanced against cyclicality. Trade tensions and tariffs pose risks to export growth, particularly into the US and Europe, potentially squeezing margins. Overcapacity in China could trigger price wars, testing LONGi’s pricing power. You should monitor how the company deploys cash amid these headwinds. Technological leaps by competitors or shifts to perovskites challenge current silicon dominance. Policy reversals in key markets add uncertainty. Key questions include overseas revenue ramp-up and R&D success rates. Supply chain dependencies on Xinjiang polysilicon raise ESG scrutiny, impacting financing. Debt levels from expansions warrant watching. For your decisions, these factors frame the risk-reward balance. Disclaimer: Not investment advice. Stocks are volatile financial instruments.
Free magazine subscription Sigenergy has entered the European utility-scale photovoltaic systems market. Together with Arausol, a German-based PV specialist, and the European distributor Memodo, it is developing Germany’s largest PV plant with decentralised storage systems that operate on direct current (DC) The project, located in Weissach im Tal, is currently under construction and will include an installed peak PV capacity of 11.6MWp and a battery capacity of 20MWh. This capacity will be distributed across 1,660 Sigenergy battery modules, each with 12kWh capacity, installed in stackable SigenStacks and deployable in a decentralised manner. Installing SigenStacks on the Arausol mounting structure, similar to PV module racks, requires no complicated cabling, cranes, or other heavy equipment. The solution helps to avoid soil sealing, which is common in projects involving large central batteries housed in containers. Compared with AC-coupled systems, it eliminates the need for multiple conversions between DC and AC. Instead, excess photovoltaic DC power is fed to the batteries and converted to AC by the inverters when it is time to feed power to the grid. DC coupling increases the overall system’s efficiency by at least 4% and can eliminate the need for duplicate inverter infrastructure. The DC mode also enables Arausol to increase the PV system's output, further enhancing the project's economic viability. In comparison, AC-coupled systems have technical limitations. As a result, consistent use of DC coupling in large-scale PV projects would enable a smaller-scale expansion of the power grid required for Germany's energy transition, helping to keep costs low for customers. Sigenergy is also supplying Arausol with other electrical components, including medium-voltage transformer stations with pre-installed low-voltage connections. Memodo ensures reliable procurement through its delivery capability and market knowledge, whereas Arausol is responsible for construction and project management, as well as for providing substructures from its own facilities. Connection to the grid is scheduled for July 2026. Emanuel Spahrkäs, senior account manager at Sigenergy, said, "This project sends a clear message: DC coupling enables utility-scale energy systems to be built faster, smarter, more efficiently, and in a more environmentally friendly way. By combining Sigenergy's unique DC-coupled solution with a decentralised battery architecture and Arausol's easy-to-install mounting system, we achieve faster commissioning, higher performance, and lower operating costs." Jaime Arau, CEO and founder of Arausol, said, "As a leading systems integrator and project developer for photovoltaic systems, we are committed to implementing the latest technology. Thanks to its innovative DC coupling, Sigenergy is an ideal partner for realising this goal." Memodo worked closely with the customer to define the system architecture and position Sigenergy as a suitable partner. Jonas Hollweg, head of Sales at Memod, said, "Our strength lies in actively bringing innovations to the market and supporting projects across the entire value chain. The project underlines the potential of close and strategic cooperation between manufacturers, project developers and distributors in delivering advanced energy solutions."
Solar cleaning related operating costs can be reduced by approximately 30 to 40 percent through robotic systems, particularly in high soiling environments. In addition to direct cost savings, consistent cleaning stabilises direct current input to inverters, reducing electrical stress and lowering fault incidence. Yogesh Kudale, Co-Founder & CEO, TAYPRO TAYPRO India’s utility-scale solar sector is transitioning from a capital cost-focused growth phase to one where operational efficiency determines long-term viability. As equipment performance matures, sustained energy output over the plant life is becoming central to project economics. In this shift, automation and solar cleaning robots play a key role by ensuring consistent module cleanliness, stable performance ratios, and reduced manual dependence, helping limit soiling-related losses and preserve asset value. In large scale solar plants, dust accumulation and soiling represent a major source of hidden energy loss. Technical assessments indicate that soiling can reduce energy generation by up to 30 percent under extreme conditions, particularly in arid, agricultural, and industrial environments. For a 1 MW ground mounted solar plant generating approximately 15 lakh units annually, a 3 percent soiling loss alone can result in nearly 45,000 units of unrealised generation each year. This level of loss directly affects revenue recovery, extends payback timelines, and compresses project returns, making soiling management a critical economic variable in utility scale solar operations. Traditional manual and water based panel cleaning practices were not designed for the scale and geographic diversity of modern solar deployments. These methods rely heavily on labour availability, site access, and water logistics, all of which introduce operational variability. Cleaning frequency often declines during monsoon periods or agricultural peak seasons, even though dust adhesion remains significant. Water consumption for routine cleaning creates additional cost and compliance challenges in water stressed regions. Repeated abrasive contact during manual cleaning also accelerates degradation of module surface coatings, increasing long term efficiency loss beyond expected degradation curves. These structural constraints limit the ability of operators to maintain consistent performance ratios across large portfolios. Solar cleaning robots address these limitations by introducing consistency, predictability, and scalability into panel maintenance operations. Designed for utility scale environments, these systems perform regular cleaning cycles without manual intervention and without reliance on water. Modern solar cleaning robots integrate sensor based navigation, terrain adaptation, and automated scheduling to operate across fixed tilt and tracker based installations. By maintaining consistent module cleanliness, they prevent gradual performance degradation rather than reacting after generation losses become visible. This approach shifts operations and maintenance from a reactive model to a preventive and predictive framework. Contrary to early assumptions, the deployment of solar cleaning robots has demonstrated a net reduction in operating expenditure over the project lifecycle. Automated cleaning reduces labour dependency, eliminates water procurement and transport costs, and improves cleaning repeatability. Analysis indicates that cleaning related operating costs can be reduced by approximately 30 to 40 percent through robotic systems, particularly in high soiling environments. In addition to direct cost savings, consistent cleaning stabilises direct current input to inverters, reducing electrical stress and lowering fault incidence. These factors contribute to improved asset availability and reduced downtime across large installations. Solar cleaning robots increasingly operate as data generating assets rather than standalone mechanical systems. Cleaning frequency, surface condition trends, environmental exposure, and operational health metrics are continuously captured and analysed. This data enables plant operators to treat performance ratio as a controllable operational variable. Maintenance planning, cleaning intensity, and resource deployment can be optimised based on predictive insights rather than periodic inspections or generation shortfalls. As India’s utility scale solar sector matures, project economics are increasingly driven by the ability to preserve generation rather than expand capacity. Soiling related losses have emerged as a material operational risk, making consistent and scalable maintenance essential. Automation and solar cleaning robots enable predictable, water independent, and data driven cleaning, reducing performance variability and operating costs. In this environment, robotic cleaning systems are becoming a core component of utility scale solar operations, directly influencing long term asset performance and financial stability. The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine. This content is protected by copyright and may not be reused. If you want to cooperate with us and would like to reuse some of our content, please contact: editors@pv-magazine.com. Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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GoodWe appoints Photovoltaic Solar as its official India partner, aiming to expand market reach, strengthen distribution, and deliver advanced solar inverter solutions supporting the country’s growing renewable energy demand. April 14, 2026. By News Bureau GoodWe, the a PV inverter manufacturer and smart energy solution provider, has announced the appointment of Photovoltaic Solar, as its official partner for India. This strategic partnership is a milestone in GoodWe’s ongoing efforts to expand its footprint in the Indian market and provide customers with products and services. The collaboration aims to leverage GoodWe’s innovative technology and comprehensive product range, ensuring that Indian consumers receive reliable and efficient solutions tailored to their specific needs. With a rich history of success and a commitment to delivering the highest standards of quality, GoodWe is confident that Photovoltaic Solar’s distribution network will help accelerate growth and further solidify the brand’s presence in India and contribute to the nation's renewable energy goals. Nevil Thakkar, Founder of Photovoltaic Solar, said, “We are pleased to partner with GoodWe to strengthen our solar solutions portfolio in India. This partnership aligns with our vision to deliver reliable, high-performance energy solutions to the market. Together, we aim to set new benchmarks in quality, innovation and customer satisfaction in the rapidly evolving solar industry.” Aniket Sawant, Country Manager– India, GoodWe added “Partnering with Photovoltaic Solar marks an exciting milestone for us as we work together to deliver cutting-edge solar inverter solutions to a wider audience in India. This partnership is a bold stride toward a more sustainable future for all.” We Aim to Build 5 GW Capacity Across the Entire Solar Value Chain, Says Future Solar's Ravi Rao Solar to BESS: Reliability Begins with Advanced Sealants, Explains Manish Gupta, Fasto Adhesive Anand Jain of Aerem Solutions on Scaling Solar, Storage, and Finance for Sustainable India JIRE CEO Amit Kumar Mittal Explains Rising Role of Energy Storage and Green Hydrogen in India Icon Solar Modules Are Engineered for India’s Harsh Conditions, Says Rajat Shrivastava
Energy briefs Oil prices plunged 8% on Tuesday April 14, 2026 Opposition to a proposed 5,000-acre solar farm in Jackson County, Kansas led to recent calls for a moratorium on solar farms in the county located north of Topeka, Kansas. The County Planning Commission held a recent meeting to consider urging the county commission to adopt an 18-month moratorium on the Jeffrey Solar project proposed by NextEra Energy Resources. The project was revealed some years ago and sparked opposition from residents and farmers who fear the loss of at least 2,000 acres of farmland west of Holton. The size of the proposed solar farm would cover about 6,600 football fields of land. The Planning Commission considered changes to the county zoning laws and this week the issue will be considered by Jackson County Commissioners. It was not the first such meeting to deal with the solar farm. The Planning Commission held a similar lengthy meeting in October 2025, one lasting three hours. The commission listened to dozens of residents who spoke about proposed solar regulations that filled 34 pages. The Holton Recorder reported the regulations were prompted by the proposed Jeffrey Solar project. Sherman Bernett, lead developer for the Jeffrey Solar project, said the current draft of solar regulations will stop the project, according to the Recorder. “This latest draft of regulations will not allow this project to move forward,” Bernett said. “The setbacks proposed are not based on science and engineering and take away landowner rights.” NextEra contends the solar farm would bring employment opportunities to the area and generate $136 million in revenue. The website for the solar project stated, “The Jeffrey Solar project is an innovative solar project proposed for Jackson County, Kansas that will have a capacity of up to 500 megawatts of clean, renewable, American-made energy. The Jeffrey Solar project is more than solar panels — it represents a significant capital investment in Kansas. Once operational, it will create good-paying jobs and millions in additional revenue for landowners and the local community.” If approved, the project would add solar capacity to Kansas where, according to the Solar Energy Industries Association, it totals 463 MW. Jeffrey Solar was scheduled to begin operations by February 2030 and cover nearly eight square miles of land. The possible moratorium isn’t the first time the county has considered such a halt in solar farm development. It also explored a similar moratorium in 2022. Further, NextEra’s project led to at least one lawsuit in which landowners filed suit to stop the company’s plans for another 5,000-acre solar farm. A U.S. District Judge in Kansas City later ruled against Thomas Hoffman, Joseph Strong, Vincent Shibler and David Shibler. Hoffman contended the project site would affect his local runway and his flying business. In nearby Shawnee County, where Topeka is the capitol, county leaders recently approved new solar energy project regulations. Shawnee County Commissioner Aaron Mays told KSNT TV News, “Shawnee County right now doesn’t have a, prior to today at least, did not have any solar regulations at all,” Mays said. “And so we initially started talking about this a couple of years ago and decided that we needed to have some sort of a framework in place.” The new rules apply to solar energy projects in unincorporated areas of the county. They not only created guidelines to review large-scale solar developments but also controls for project size limits, setbacks from homes and roads and requirements for land restoration at the end of the project.
0 Powered by : Solar Energy Corporation of India Limited (SECI), an Indian government renewable energy implementing agency, has invited bids for 4455 kW rooftop PV systems under RESCO mode across 14 institutional sites. The work covers design, engineering, supply, erection, testing, commissioning, grid connectivity, net-metering, and O&M during the PPA term. The bid processing fee is INR 6,000 including GST, while EMD is project-specific as per the RfS. The pre-bid meeting is scheduled for 20 April 2026, online bid submission closes on 11 May 2026, and offline submission and bid opening are set for 14 May 2026. Bidders must comply with SECI’s technical parameters, use ALMM List-I modules and ALMM List-II cells, and meet cumulative net-worth and liquidity thresholds for all lots bid for the total capacity they bid for.
Indian solar cell manufacturers listed on the Ministry of New and Renewable Energy’s (MNRE’s) Approved List of Models and Manufacturers (ALMM) List-II expanded their manufacturing capacity from 27,753MW from 26,477MW in February, a move that has drawn a broadly positive response from industry stakeholders. The latest revision includes the entry of heterojunction (HJT) solar cell technology into ALMM List-II for the first time through Gujarat-based solar manufacturer Reliance Industries, which secured 1,238MW of enlisted capacity. Get Premium Subscription Reliance’s HJT cells, produced at its Gujarat facility, use 210mm × 105mm zero-busbar architecture and are rated at efficiencies of up to 25.6%, with wattage ranging from 5.28W to 5.66W. The company’s HJT modules were previously included in ALMM List-I with 1,716MW of annual capacity, covering monofacial and bifacial glass-to-glass configurations. Other companies to have added manufacturing capacity include Jupiter Solartech, a wholly owned subsidiary of solar manufacturer Jupiter International, which has added 991MW of monocrystalline passivated emitter rear contact (PERC) bifacial cell capacity from its Himachal Pradesh facility. Websol Energy System has also added 600MW of monocrystalline PERC P-type bifacial cells from its West Bengal plant, taking its total ALMM List-II capacity to 1,202MW. The additions are valid until April 12, 2030, and November 23, 2029, respectively. Industry participants have highlighted the inclusion as a significant policy signal towards higher-efficiency technologies and domestic manufacturing capability building. “The inclusion of heterojunction technology in the ALMM II list is a forward-looking move by MNRE. It signals a clear policy push toward high-efficiency modules and could accelerate technology upgrading among domestic manufacturers,” Gaurav Upadhyay, energy and finance specialist at Institute for Energy Economics and Financial Analysis (IEEFA), told PV Tech. “However, it can also raise the bar on capital intensity and technical capabilities, potentially consolidating the market in favour of well-capitalised players.” Under MNRE regulations, from 1 June 2026, all government-supported solar projects will be required to use modules manufactured with cells listed under ALMM List-II, reinforcing the importance of domestic cell capacity in project eligibility and procurement. Industry experts also pointed to the revision as evidence of accelerating structural maturity in India’s solar manufacturing ecosystem. “The latest revision of the ALMM List-II marks a defining moment for India’s solar manufacturing ecosystem,” said Prashant Mathur, CEO of module manufacturer Saatvik Green Energy Limited. “What we are witnessing is not just a policy milestone, but a clear signal of market-led confidence in domestic cell manufacturing.” Mathur added that the entry of large industrial players and advanced technologies such as HJT reflects “a decisive shift towards higher efficiency and long-term competitiveness,” and a transition “from capacity creation to capability building.” Echoing a similar sentiment, Nikhil Bansal, co-founder of solar developer Solarium, told us that MNRE’s inclusion of HJT technology in ALMM List-II is a “clear statement” that India is moving to lead in solar manufacturing technology rather than follow global trends. “HJT is a step-change in efficiency and performance, and this will separate future-ready manufacturers from the rest,” Bansal said. “It raises the bar, but that’s exactly what the industry needs to compete globally on technology, not just cost.” Additionally, the ministry has proposed the creation of ALMM List-III for wafers, with stakeholders noting that a potential gap in upstream capacity and a tight compliance timeline could impact supply chains and bidding behaviour.
To reduce the likelihood of these creatures entering residential areas, homeowners are advised to minimize outside lighting and clear thick vegetation that retains moisture. Pets should be kept on a leash at night, and it is highly recommended to check yards and other grassy areas before letting pets outside. If a dog does come into contact with a cane toad, pet owners should wipe the gums, teeth, and roof of the dog’s mouth and immediately visit an emergency veterinarian. 💡These best-sellers from Quince deliver affordable, sustainable luxury for all Starting at $50 Starting at $99 Starting at $60 Starting at $80 Which of these savings plans for rooftop solar panels would be most appealing for you? Save $1,000 this year 💸 Save less this year but $20k in 10 years 💰 Save less in 10 years but $80k in 20 years 🤑 Couldn’t pay me to go solar 😒 Click your choice to see results and earn rewards to spend on home upgrades.
A solar and battery storage project developed and financed by Sunrock Distributed Generation is now in operation at the County Jail in Salinas, California. Funded through a PPA, it is expected to save the Monterey County Sheriff’s Office, which operates the jail, more than $12 million over its lifetime. The installation includes a 1.243-MW carport solar…
As Europe accelerates its transition toward a decarbonized energy future, a new study reveals a complex and paradoxical challenge emerging from the widespread adoption of solar photovoltaic (PV) systems. The phenomenon, known as the solar rebound effect (SRE), threatens to undermine some of the anticipated benefits of clean energy by driving up electricity prices and increasing carbon emissions through increased energy consumption. This nuanced dynamic, thoroughly examined by researchers Delic and Bucksteeg, exposes a critical vulnerability in Europe’s energy transition path, particularly highlighting the ramifications for electricity markets, infrastructure, and energy equity. At the heart of the analysis lies the intricate interplay between solar-generated electricity and consumer behavior. When households install PV systems, they often increase their overall electricity consumption instead of reducing it, a counterintuitive outcome termed the rebound effect. This increased demand, fueled by the economic incentive of low-cost solar power, places additional pressure on the power system. It challenges grid operators to provide flexibility and balance, especially during periods when solar output is insufficient, such as evening hours or winter months. The study’s projections for 2040 paint a stark picture: wholesale electricity prices across Europe experience heterogeneous but often significant rises driven by rebound consumption patterns. The research employs a detailed spatial and temporal simulation framework, assessing three distinct rebound demand profiles—dynamic, simultaneous, and sweeping—that characterize how increased electricity usage might unfold. The dynamic profile, which reflects varying demand peaks aligning with solar generation, induces moderate electricity price increases ranging from +€0.06 per megawatt-hour in France to +€0.76 per megawatt-hour in Belgium. This scenario reveals that flexibility, especially in Central European countries reliant on gas-fired power plants to cover solar shortfalls, is essential for mitigating cost escalations. The results emphasize that localized generation mixes and grid constraints significantly influence market outcomes. Contrasting this, the simultaneous rebound profile, wherein consumers increase demand concurrently during solar peak production, demonstrates a more moderated impact on prices across many regions. Remarkably, in Southern and South-Eastern Europe, characterized by high solar resource intensity, this profile can even cause slight reductions in wholesale prices due to the natural alignment of demand surges with abundant solar output. These findings suggest that strategic demand shifting could leverage solar generation peaks to relieve stress on the grid and contain price spikes, underscoring the value of demand response programs in future power systems. However, the sweeping rebound profile reveals the most alarming consequences. Representing a uniform increase in demand regardless of solar availability, this pattern precipitates large wholesale price surges, particularly in Central Europe. Countries like Germany and Slovakia face increases as high as +€1.55 and +€1.64 per megawatt-hour, respectively. The uniform demand load necessitates continuous reliance on gas-fired power plants, which are challenged by limited system flexibility and infrastructure bottlenecks during peak winter periods. The pronounced costs in these scenarios highlight the critical need for infrastructure upgrades and grid expansion to accommodate changing consumption dynamics driven by solar rebound. Underlying these wholesale price impacts, the study delineates the interactions with escalating carbon dioxide (CO₂) prices linked to stringent decarbonization target policies for 2045. Rebound demand indirectly inflates CO₂ pricing by pushing gas generation usage higher to cover solar shortfalls, creating a feedback loop that compounds electricity system costs. This complexity illustrates the interconnectedness of market mechanisms, consumer behavior, and climate policies, requiring integrated solutions that simultaneously address demand-side management and supply system decarbonization. Furthermore, the authors draw attention to equity concerns intensifying under the solar rebound effect paradigm. The capital-intensive nature of PV system adoption disproportionately favors higher-income households, especially given that ownership is largely confined to properties with suitable rooftops. This disparity in access to low-cost solar energy leads to a bifurcation in benefits, with wealthier adopters gaining more substantial financial relief while non-adopters bear increasingly higher systemic electricity costs. Notably, current regulatory frameworks exacerbate this divide by taxing grid-supplied electricity more heavily than self-consumed solar power, effectively subsidizing solar users’ increased consumption on the backs of all electricity consumers. The resulting cost externalities generate implicit cross-subsidies from non-adopters—often lower-income households with limited options for self-generation—to adopters, further deepening energy poverty and inequality. This regressive effect is particularly pernicious because vulnerable populations spend a higher proportion of their income on energy, making wholesale price increases more burdensome. The study highlights the urgency of re-evaluating tariff structures and regulatory mechanisms to ensure a more equitable distribution of costs and benefits arising from the energy transition. On a technological and policy front, the findings underscore the imperative for enhanced backup capacity investments and grid modernization to mitigate the negative price and emissions impacts of the solar rebound. Current energy infrastructure in Central Europe, with its reliance on gas-fired power plants during non-solar periods, faces significant strain. Investing in flexible generation, storage solutions, and demand side-flexibility is paramount to accommodating rebound-affected consumption patterns while achieving climate goals. Moreover, temporal demand management emerges as a key lever. Aligning increased electricity use with periods of high solar production, as exemplified by the simultaneous rebound profile, offers a pathway to smooth wholesale price volatility and reduce reliance on fossil-fueled backup. These insights advocate for integrating smart grid technologies, dynamic pricing, and consumer education within energy policy frameworks to realign consumption behavior with clean energy availability. This study’s holistic approach also brings to light the limitations of traditional, uniform cost allocation models for electricity markets. A system established during eras of steady marginal generation costs struggles to cope with increasing variability introduced by renewables and growing flexibility needs. Rethinking cost allocation schemes to reflect temporal and spatial heterogeneity in demand and supply conditions represents an essential policy challenge. By doing so, Europe can better manage the distributed costs of the energy transition while curbing inequity. The temporal dimension of the solar rebound effect cannot be overstated. Shifts in household consumption to evening hours or wintertime, when solar generation dips, compel the system to mobilize expensive backup resources. These requirements manifest as elevated wholesale prices that indiscriminately affect all consumers, further exacerbating cross-subsidization concerns. The study’s sophisticated modeling captures these temporal interdependencies, providing a nuanced understanding of how seemingly beneficial solar adoption can inadvertently impose system-wide stresses. Importantly, the findings resonate with earlier grid expansion analyses, corroborating the vulnerability of Central Europe’s energy infrastructure to demand perturbations coupled with renewable intermittency. These results suggest that regional policy coordination and targeted infrastructure investments are vital to ensure system resilience. They also emphasize that rebound effect timing and profile are as consequential as its magnitude in shaping infrastructure needs and consumer price outcomes. Beyond technical and economic considerations, the social implications of this research are profound. Ensuring a just energy transition that fairly distributes the benefits and burdens of decarbonization remains a paramount political challenge. The solar rebound effect’s asymmetric cost distribution risks alienating lower-income households and exacerbating energy insecurity, potentially undermining public support for renewable energy policies. Policymakers must address these disparities through inclusive planning, equitable tariff reforms, and support mechanisms for vulnerable populations. The analysis also sheds light on consumer behavior nuances, such as inaccurate perceptions of monetary savings from demand response programs, which influence solar self-consumption patterns. Addressing these informational gaps through targeted communication and behavioral interventions could enhance the effectiveness of rebound mitigation strategies. Integration of behavioral economics insights into energy policy design may offer innovative pathways to align consumer actions with system-wide decarbonization goals. In conclusion, the solar rebound effect represents a multifaceted challenge that intertwines consumer behavior, market dynamics, infrastructure capacity, emissions trajectories, and social equity. Europe’s ambitious decarbonization agenda must grapple with these complexities to realize the full promise of solar energy. This study by Delic and Bucksteeg not only quantifies the scale and distribution of price and emissions impacts but also clarifies pathways for mitigating adverse consequences through targeted policy and technology solutions. Its findings call for a recalibrated approach to energy transition planning—one that accounts for human factors, temporal demand shifts, and the uneven geography of generation and consumption. As Europe strides toward 2045 decarbonization objectives, addressing the solar rebound effect emerges as a critical frontier. By embracing dynamic demand management, revisiting regulatory frameworks, investing in flexible infrastructure, and prioritizing equity, the continent can safeguard the environmental and social promise of clean energy. This research paves the way for a more resilient, cost-effective, and just energy future that recognizes complexity rather than simplistically relying on technology alone. Subject of Research: The impact of the solar rebound effect on electricity prices, infrastructure requirements, carbon emissions, and energy equity in Europe’s decarbonization pathway. Article Title: Implications of the solar rebound effect for the European energy transition Article References: Delic, M., Bucksteeg, M. Implications of the solar rebound effect for the European energy transition. Nat Energy (2026). https://doi.org/10.1038/s41560-026-02031-8 Image Credits: AI Generated DOI: https://doi.org/10.1038/s41560-026-02031-8 Tags: consumer behavior and solar adoptiondecarbonization and energy equityelectricity market dynamics Europeenergy infrastructure stress from solarEurope energy transition challengesfuture projections of solar energy impactsimpact of solar PV on electricity pricesrenewable energy paradoxsolar energy and increased consumptionsolar power grid flexibility issuessolar PV system economic incentivessolar rebound effect We bring you the latest biotechnology news from best research centers and universities around the world. Check our website. Enter your email address to subscribe to this blog and receive notifications of new posts by email.
Sign up for email newsletters Trending: A presentation on a potential community solar project for Harvey was interrupted Monday by a power outage, postponing a preliminary City Council vote on the project. The proposal is from Marquis Matilla, who said his business, Evolved Living, develops community solar projects in underserved communities. “What happens is, not everyone can get solar panels on their homes,” Matilla said. “We would develop this solar farm, and that solar farm feeds energy back to ComEd’s grid. ComEd then takes that electricity, credits it and everyone who’s a subscriber to that community solar project is basically a partial owner.” Residents would not have to pay anything to subscribe, Matilla said. The first step to judge the project’s viability would be a feasibility study. Matilla stressed there are several steps and studies before anything is certain. “That feasibility study means that we will apply with ComEd and make sure that there’s enough space on the substation to accommodate this solar farm,” Matilla said. “This is the very preliminary stages of the project, OK? But it is a very good project and we’re hopeful.” Matilla said there are multiple sites under consideration for the solar farm, but said choosing one would rely on the result of the feasibility study. Which site was chosen would determine the size of the solar farm, he said. “It’s not definitive yet. There are a couple sites that we are talking to the City Council to possibly see if they are suitable for the project,” Matilla said. “One site is a little bit larger, one site is a little bit smaller, but definitively we won’t know until we get to the feasibility phase.” Fourth Ward Ald. Tracy Key asked Matilla if there were other comparable community solar projects nearby in the south suburbs. Matilla said there were a few community solar projects in Ford Heights, but that there were not many in and around Chicago due to a lack of available space. “It’s difficult to find land in the city,” Matilla said. “The closest places that you could probably go to see these projects are central Illinois, Joliet, Rockford area, where they have more available.” A proposed 6,100 acre solar farm in Will County, near Manhattan, has drawn opposition from residents, who filed a lawsuit to stop the project earlier this month. Matilla said the community solar project was made possible by a grant from the Illinois Department of Commerce and Economic Opportunity. “That grant is a new program that the state is offering, so projects like this wouldn’t be even economically viable,” Matilla said. “This type of program for a municipality and community is a new program that is possible because of the grant.” Matilla said that the city would generate revenue both from renewable energy credits and from leasing the land. “This would cost the city nothing,” Matilla said. “In fact, we’re taking vacant, unused, contaminated land and turning it into an asset that the city and the residents can take advantage of.” Acting Mayor Shirley Drewenski emphasized the vote would just be on whether the city was interested in pursuing the project, starting with the feasibility study. “Now, what happens if the land is perfect?” Drewenski said. “Then what will happen is they will come and get the permits, they will go through the zoning and making sure everything is OK. Then it will come back to the City Council for a vote.” The vote did not happen Monday due to the power outage cutting the meeting short, and no public comment was heard. Harvey’s next City Council meeting is scheduled for 7 p.m. on April 27 at Harvey City Hall, 15320 Broadway Ave. elewis@chicagotribune.com Copyright 2026 Chicago Tribune. All rights reserved. The use of any content on this website for the purpose of training artificial intelligence systems, algorithms, machine learning models, text and data mining, or similar use is strictly prohibited without explicit written consent.
With an output of 800 megawatts, the Springwell Solar Farm supports the UK’s efforts towards cleaner and more secure energy sources. Located in Lincolnshire, the Springwell Solar Farm is expected to generate enough electricity to power more than 180,000 homes each year. By approving the Springwell Solar Farm, the UK government has officially approved 25 national clean energy projects. Altogether, these projects hope to generate enough electricity to power over 12.5 million homes. By increasing the share of homegrown energy, the UK government aims to improve resilience against global supply disruptions. Recent geopolitical tensions, including conflicts in Eastern Europe and the Middle East, have highlighted the risks of dependence on international fossil fuel markets. Fluctuations in supply and pricing have contributed to energy insecurity and rising costs for households and businesses. In response, the UK has intensified efforts to diversify its energy mix and invest in renewable infrastructure. Large-scale solar projects like Springwell Solar Farm are seen as a key solution, offering stable and predictable energy generation without exposure to fuel price volatility. The expansion of solar capacity is also expected to contribute to long-term reductions in electricity bills by increasing the availability of low-cost power. The approval of Springwell Solar Farm builds on a series of recent government initiatives designed to boost solar adoption nationwide. These include measures to introduce plug-in solar technologies in retail environments and plans to make solar panels a standard feature on new homes in England. The government is also moving ahead with plans to accelerate renewable energy actions, with the next round scheduled for July. This is intended to bring more projects online faster and maintain momentum in the clean energy transition. This aims to make solar energy more accessible at the utility and household levels, ensuring that the benefits of renewable power are widely shared. The Springwell Solar Farm is expected to deliver economic benefits through job creation during both construction and operation phases. It also supports the UK’s environmental goals by reducing carbon emissions and advancing progress toward net-zero targets. As one of the largest solar developments in the country, Springwell Solar Farm represents a significant investment in sustainable infrastructure. Its approval highlights the growing role of solar energy in shaping the UK’s future energy landscape.
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Battery Energy Storage Systems (BESS) are among the most thoroughly tested and code-governed energy infrastructure deployed, and their safety record is improving dramatically as the technology matures. BESS Adhere to a Rigorous Safety Framework Every … RICHMOND, VA — Yesterday Governor Abigail Spanberger signed a slate of energy bills that will help lower Virginians’ electricity bills, strengthen grid reliability, and boost the local economy by increasing solar and storage deployment in …
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About SEIA The Solar Energy Industries Association® (SEIA) is leading the transformation to a clean energy economy. SEIA works with its 1,200 member companies and other strategic partners to fight for policies that create jobs in every community and shape fair market rules that promote competition and the growth of reliable, low-cost solar power. Founded in 1974, SEIA is the national trade association for the solar and solar + storage industries, building a comprehensive vision for the Solar+ Decade through research, education and advocacy.
WASHINGTON D.C. — In case you missed it, today, Abigail Ross Hopper, president and CEO of the Solar Energy Industries Association (SEIA), testified in front of the U.S. Senate Environment and Public Works … As the U.S. and China continue trade negotiations in Stockholm, one thing is clear: rare earth elements (REEs) are a powerful bargaining chip and a critical part of the future of American energy and our economy. The U.S. remains heavily dependent on China for access to these materials, many of which play important roles in the systems that support clean energy, like battery storage, inverters, and grid technologies. While the two nations aim to temporarily ease export restrictions, this moment also highlights that America’s long-term energy security depends on building out our own rare earth mining and processing capabilities. REEs are a group of 17 metallic elements on the periodic table. They are considered “rare,” not because they are scarce in Earth’s crust, but because they are dispersed and found in low concentrations, making them difficult and costly to mine. Their unique magnetic, phosphorescent, and catalytic properties allow them to play an essential role across many industries, from smartphones and fighter jets to MRI machines, and increasingly in the energy industry. To be clear, REEs are not used in solar panels themselves. However, they are important elements in grid technologies that support and stabilize clean energy systems. There are no rare earth elements directly used in photovoltaic (PV) solar modules, but they are key components of the inverters that convert direct current (DC) electricity generated by solar panels into alternating current (AC) electricity used on the electric grid. They also play a role in the converters that manage voltage and current flows in solar + storage systems. Specifically, yttrium, lanthanum, and sometimes cerium oxide are used in ceramic capacitors, and neodymium is used in magnets for internal sensors and fans. Grid-scale batteries need advanced cooling systems to operate safely and reliably. Rare earths like neodymium and dysprosium are used in the magnets that power fans and pumps. Other elements, like cerium and lanthanum, are used in sensors that monitor and manage battery temperature. Even though these materials are used in tiny amounts (on the gram-to-milligram scale), they are essential to preventing BESS systems from overheating. REEs are also found throughout the broader electric grid, albeit in specialized use cases. Sensors and actuators (i.e., motorized switches, tap changers, etc.) used in smart grid systems, substations, and other infrastructure often include compact, high-performance magnets made with REEs. Despite limited applications, REEs play an important role in advancing grid modernization and next generation technologies as more solar and BESS systems come online. As of 2024, the U.S. depends on imports to satisfy 80 percent of domestic demand for REEs. About 70% of those imports come directly from China, and even when we source from other countries like Malaysia or Japan, those nations often rely on rare earth materials that originated or were processed in China. China not only dominates the production of rare earths, but it also controls many of the refining and processing steps needed to turn raw minerals into usable components. In fact, even the one active, commercial-scale REE mine in the U.S. — Mountain Pass Mine owned by MP Materials in California — still sends some of its output to China for final processing. This has led to growing interest in reshoring key parts of the rare earth supply chain to reduce bottlenecks, improve domestic capacity, and strengthen U.S. energy security. The recent commitment by the U.S. Department of Defense to take an equity stake in MP Materials, along with a 10-year magnet offtake agreement and 10-year price floor for MP’s neodymium-praseodymium oxide, is a key example of U.S. commitment to onshoring rare earth supply chains. The current trade talks in Stockholm may provide some short-term relief by easing export restrictions, but this won’t solve the central problem. Without a reliable domestic supply chain that included mining, refining, and processing, the U.S. will remain vulnerable to geopolitical tensions and supply disruptions. The Trump administration has already taken steps to mobilize resources and expedite permitting for REE production, but more investment is needed to aggressively scale up. In the meantime, securing access to these materials through a trade agreement is essential to ensure the U.S. can continue manufacturing the technologies that power our electric grid, support national security, and drive economic growth. Battery Energy Storage Systems (BESS) are among the most thoroughly tested and code-governed energy infrastructure deployed, and their safety record is improving dramatically as the technology matu… RICHMOND, VA — Yesterday Governor Abigail Spanberger signed a slate of energy bills that will help lower Virginians’ electricity bills, strengthen grid reliability, and boost the local econ… “AI infrastructure companies, they’re facing grid interconnection queues that can be 5-7 years long, which is really untenable when their competitors are getting to move at startup’s pac… Sign up for the SEIA Weekly Array to get the latest solar and storage news straight to your inbox
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Australian mining giant Fortescue has accelerated its timeline for deploying a 1.8GW renewable energy portfolio, paired with 4-5GWh of batteries, which it now expects to begin commercial operation by 2028. The portfolio will consist of 1.2GW of solar PV capacity, alongside 600MW of wind, which Fortescue dubbed “the world’s largest off-grid system” for heavy industry. The miner expects the first 290MW of solar capacity to be operational by early 2027 and a Fortescue spokesperson told PV Tech that it plans to use LONGi solar panels, BYD batteries and Envision Energy wind turbines across the portfolio. Get Premium Subscription Fortescue has already announced plans to deploy 4-5GWh of battery energy storage systems (BESS) in Western Australia, and these batteries will help deliver “24-hour periods”, where fossil fuels are not used to power mining equipment, across the operations by late 2027. The project accelerates the company’s ‘Real Zero’ decarbonisation plan, which initially aimed to reach zero emissions across its scope one and two emissions by 2030. In comments made on LinkedIn, Fortescue’s health and safety and R&D superintendent Daniel Hewitt said that the project would require US$6.2 billion in capex, but that it would “pay itself back in a few years” by slashing diesel-related opex costs by US$818 million per year from 2030. The portfolio will be built in and designed to provide power for the company’s extensive mining operations in the Pilbara region of Western Australia. Earlier this year, the company started construction at a 440MW solar PV project in the region, which it claimed would be the largest such project in the state upon completion in 2028 and forms part of the renewables-plus-storage hub. In December 2025 CEO Dino Otranto claimed the company had secured low “pricing that hasn’t really been seen” for its battery projects in the region. Western Australia is home to some of the world’s deepest iron ore reserves, and these deposits have formed the bedrock of Fortescue’s work since its inception. The miner shipped a record 198.4 million tonnes of iron ore in the 12 months to June 2025, up from 191.6 million tonnes in the previous 12 months, and Fortescue said last July that it expects to grow iron ore export volumes by up to 3% in the next year. On the same day as it announced its record mining exports, Fortescue cancelled two green hydrogen projects under development in the US state of Arizona, citing the Trump administration’s hostile attitude towards the energy transition. Following these cancellations, and the announcement of record iron ore sales, the value of the company’s shares increased by 4%.
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MyNu Energy has launched a mobile solar generation and battery energy storage system designed to reduce reliance on diesel as the Middle East crisis continues to cause concerns about fuel shortages and uncertain energy costs. Image: MyNu Energy From pv magazine Australia Australian energy solutions provider MyNu Energy has unveiled a trailer-mounted solar and battery energy storage system designed to replace traditional diesel-fuelled generators as businesses look to manage energy costs and reduce exposure to fuel supply disruptions. The PowerQub-M Mobile Power Station combines a 3 kW demountable solar array with battery storage options ranging from 60 kWh to 240 kWh and can deliver between 25 kVA and 160 kVA of power depending on configuration, with both three-phase and single-phase outlets. The company said the mobile power plant can also be customized to meet specific customer requirements, including integrating with larger ground-mounted portable solar systems. MyNu said the PowerQub-M is designed and assembled in Australia, with company co-founder Shaun Nugent highlighting that the ability to deploy power quickly in remote or temporary locations was a key driver behind the design. “We wanted to create something that could be moved easily and set up quickly wherever power is needed, whether that’s a construction site, a farm, an event or even disaster recovery situations,” he said. “The trailer-based design means it can be deployed rapidly without the need for permanent infrastructure.” MyNu expects demand across sectors including construction, agriculture, remote infrastructure, events and emergency response, particularly in regions where diesel logistics remain challenging. “This isn’t just about sustainability, it’s about practicality,” Nugent said. “Businesses need power they can rely on, and increasingly they’re looking for solutions that aren’t tied to diesel.” Nugent said the system also offers advantages for equipment performance, with battery-based power delivering more stable electricity compared to some diesel generators. MyNu co-founder John Myler said the launch of the mobile energy plant comes amid a growing shift toward alternative power solutions as businesses look to exert more control over their energy use and costs. “We’re hearing from farmers, construction operators and regional businesses who are struggling with both the cost and availability of diesel,” he said. “Power is critical to their operations, and they need solutions that are reliable, but also independent of fuel supply chains.” This content is protected by copyright and may not be reused. If you want to cooperate with us and would like to reuse some of our content, please contact: editors@pv-magazine.com. More articles from David Carroll Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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You’d have thought the quarter-sized hail that wreaked havoc on solar farms would have served as a giant red flag in between the rails these cathedrals to the Religion of Climate careened on. For my Lisle AWFL readers, ‘wreaking havoc’ means to destroy them and rendering them scrap’.
If this bill passes, say goodbye to local control over all Illinois parks and expect to see open drug and alcohol use, needles, no sanitation and fire hazards, but no ordinary park users.
COLUMBIA, S.C. — A US-owned and -operated solar cell manufacturer has announced it will be investing $350 million and creating 564 new jobs when it locates its first South Carolina facility in Laurens County. Suniva Inc. is one of the largest and oldest solar cell manufacturers in the country. Founded in 2007 out of U.S. Department of Energy-funded research at the University Center for Excellence in Photovoltaics at Georgia Tech, the company became well known for leading the push for solar cell manufacturing in the United States as a pillar of the nation’s energy independence and domestic energy security. The company plans to lease a 600,000-sq-ft building in Laurens to produce advanced solar cells. Once the site is online in 2027, Suniva will produce over 5.5GW of solar cells annually, in conjunction with the company’s existing plant in Georgia. This will make Sunvia’s facility capable of one of the largest such capacities in the United States. Matt Card, President and COO, Suniva, said, “At this moment in history, the question of where our energy comes from – and who controls the supply chain that delivers it – is among the most consequential questions America faces. Suniva’s answer is straightforward: we build it here. With this expansion, Suniva contributes over 5.5GW of American-made solar cell capacity annually to a grid that increasingly depends on it. That’s not just good business. That’s a national imperative.” Individuals interested in joining the Suniva team should visit the company’s careers page. To stream WLTX 19 on your phone, you need the WLTX 19 app. Next up in 5 Example video title will go here for this video Next up in 5 Example video title will go here for this video
Ross Norton // April 14, 2026// Suniva plans to open a 4.5-gigawatt solar cell manufacturing facility in Laurens County, investing $350 million and creating 564 jobs. (Photo/DepositPhotos) Suniva to build $350M solar factory in Laurens County Suniva plans to open a 4.5-gigawatt solar cell manufacturing facility in Laurens County, investing $350 million and creating 564 jobs. (Photo/DepositPhotos)
A Georgia-based manufacturer of monocrystalline silicon solar cells, will build a factory in Laurens with a $350 million investment that the South Carolina Department of Commerce says will create 564 new jobs. Suniva Inc., which says it is the largest and oldest U.S. manufacturer of high-efficiency monocrystalline silicon solar cells, has entered agreements to bring a state-of-the-art 4.5-gigawatt solar cell manufacturing facility to Laurens. The company expects to open in the second quarter of 2027. The new facility, coupled with Suniva’s existing facility at its headquarters in metro Atlanta, will bring the company’s total domestic solar cell manufacturing capacity to over 5.5 gigawatts annually — the largest of any merchant solar cell manufacturer in the United States, according to information from the company. Founded in 2007 out of U.S. Department of Energy-funded research at the University Center for Excellence in Photovoltaics at Georgia Tech, the company became known for leading a push for solar cell manufacturing in the United States as a pillar of the nation’s energy independence and domestic energy security, according to a Commerce Department news release. “Since its founding in 2007, Suniva has championed U.S. leadership in solar energy manufacturing,” Suniva CEO Tony Etnyre said in the release. “Solar is the fastest and most economical way to grow our nation’s energy supply — and at this critical juncture, access to energy will determine how America competes for generations to come. Our expansion in South Carolina means that renewable energy, made right here at home, will now do more than ever to secure that future.” The company plans to lease a 620,000-square-foot building, located at 1200 Commerce Blvd. in Laurens, to produce advanced solar cells. “Laurens County is excited to welcome Suniva and their first South Carolina operation to our community,” Laurens County Council Chairman Jeff Carroll said in the release. “The investment commitment and job creation are a testament to our business-friendly environment. We look forward to a great partnership with Suniva for many years to come.” Suniva says the expansion represents a direct contribution to the nation’s energy security. “Suniva has long championed U.S. leadership in solar manufacturing,” Etnyre said in the company annoucement. “We are proud to partner with the state of South Carolina on this vital initiative.” “At this moment in history, the question of where our energy comes from – and who controls the supply chain that delivers it – is among the most consequential questions America faces,” Matt Card, president and chief operating officer of Suniva, said in the release. “Suniva’s answer is straightforward: we build it here. With this expansion, Suniva contributes over 5.5GW of American-made solar cell capacity annually to a grid that increasingly depends on it. That’s not just good business. That’s a national imperative.” Suniva is headquartered in Norcross. The company’s proprietary cell processing techniques and business model are used to achieve industry-leading efficiencies while maintaining among the lowest costs in the United States, according to the company website. Suniva looks beyond its products to work with solar module assemblers, EPC firms and solar plant developers to enable high-value solar projects benefiting from domestically made, high-quality and high-efficiency solar cells. “By selecting its location in Laurens County, Suniva joins a growing number of manufacturers in Upstate S.C. whose products help to power the world, deepening our expertise in advanced energy,” Upstate SC Alliance President and CEO John Lummus said in the release. “We’re excited for the opportunities they will create in our region and look forward to watching them grow.” Share this! [box type=”shadow”] John Frick named president and CEO of Electric Cooperatives of South Carolina Chris Koo[…] April 7, 2026 Charleston-based Zero Industrial names new chief commercial officer and board member as it expands clean energ[…] April 3, 2026 University of South Carolina launches Nuclear Workforce Initiative to boost training innovation and support gr[…] April 2, 2026 Duke Energy wins approval for a natural gas plant in Anderson County that the company says will support growth[…] March 27, 2026 Duke Energy Foundation invests $500K in South Carolina HERO grants to boost emergency preparedness, training a[…] March 19, 2026 Environmental groups reached a settlement with Duke Energy over its plan to combine Carolinas utilities, aimin[…] March 10, 2026 Sign up for your daily digest of SCBIZ News.
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The 20 MW Loukkaanaro solar park received €2.35 million ($2.7 million) from the EU’s first cross-border renewables tender. It is billed as the largest operational solar project in northern Finland. Image: Oulun Seudun Sähkö A 20 MW solar project in Finland backed by the EU’s cross-border renewable energy program is now operational. According to the European Climate, Infrastructure and Environment Executive Agency (CINEA), the Loukkaanaro solar park is the first commissioning of a project supported by the EU Renewable Energy Financing Mechanism (RENEWFM). The mechanism allows renewable energy projects to be developed via collaboration between contributing and hosting EU member states. The Loukkaanaro solar park was selected as part of the first RENEWFM tender, alongside six other solar projects in Finland, with funding provided from Luxembourg. The site was the first to sign a grant agreement with CINEA, receiving €2.35 million ($2.7 million) in investment support compared to total project costs of around €10 million. Construction began in May 2024, with the park completed by the end of 2025. The project is managed by Oulun Seudun Sähkö, a regional energy cooperative serving the area around the Finnish city of Oulu. Its chief financial officer, Juhani Rönkkö, told pv magazine the EU’s cross-border financing mechanism was crucial to the project. “A local bank financed a major part of the project and we used our savings and other sources of income for the rest of the financial requirements,” Rönkkö said. Located in the municipality of Utajärvi within Finland’s northern Ostrobothnia region, the project has been billed as the largest in northern Finland. It features around 30,000 solar panels and is expected to produce around 4% of the region’s annual electricity consumption. Rönkkö added that the energy generated will be mainly used for households, with the commercial and industrial sector contributing to a minor part of the usage. “On-site construction phase took around 1.5 years,” Rönkkö also said. “We faced some technical challenges when the solar park was integrated into the transmission grid, but they were solved without major delays.” A statement published by CINEA explains that the project is an important step in demonstrating the viability of large-scale solar generation in northern climatic conditions. “The effects of snow and cold temperatures will be closely monitored, providing valuable operational data for the development of future renewable energy projects in similar environments,” the agency said. CINEA added that the remaining 15 projects awarded under the first and second rounds of the cross-border financing mechanism are expected to be commissioned between this year and 2028. A third funding round launched this March, with a share of €54.9 million available to solar-plus-storage projects in Bulgaria and ground-mounted solar projects in Finland, with funding again provided by Luxembourg. The deadline for applications is September 1. Finland added 227 MW of utility-scale solar last year, a record in a calendar year for the country. Analysis from Renewables Finland forecasts utility-scale installations in Finland could surpass rooftop in terms of cumulative capacity by 2028. This content is protected by copyright and may not be reused. If you want to cooperate with us and would like to reuse some of our content, please contact: editors@pv-magazine.com. More articles from Patrick Jowett Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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Solar Power World By Kelly Pickerel | Suniva announced it will open a second monocrystalline silicon solar cell manufacturing facility in the United States. The company has entered into agreements to set up a 4.5-GW facility in Laurens, South Carolina, with a projected opening in Q2 2027. The site will join Suniva’s existing 1-GW manufacturing site outside Atlanta to bring the company’s total domestic manufacturing capacity to 5.5 GW annually. The building in Laurens. “Suniva has long championed U.S. leadership in solar manufacturing. Solar energy is the fastest and most economical way to grow our nation’s energy supply,” said Tony Etnyre, Suniva CEO. “Our expansion means that domestically produced renewable energy will do more than ever to secure America’s energy future. We are proud to partner with the state of South Carolina on this vital initiative.” Suniva has had a rollercoaster journey in the U.S. solar market. The company founded in 2007 and was the largest dual solar cell and panel manufacturer in the United States. After suspending operations in 2017 after being priced out by foreign imports, Suniva restarted its silicon cell manufacturing operations in Georgia in late 2024. Suniva is investing $350 million into the 620,000-ft2 Laurens facility and will create over 550 jobs. “With the addition of 564 jobs in advanced manufacturing and energy, Suniva’s decision to put down roots in the Palmetto State will create new opportunities for our workforce. This investment strengthens our commitment to innovative energy solutions, and we are proud to welcome Suniva to Laurens County,” said South Carolina Governor Henry McMaster. Just 30 miles south of the Laurens facility is ES Foundry’s 3-GW capacity silicon solar manufacturing facility, currently the country’s largest cell manufacturing outfit. Once Suniva’s new site opens, the company will be considered the largest silicon cell manufacturer in the United States. Kelly Pickerel has more than 15 years of experience reporting on the U.S. solar industry and is currently editor in chief of Solar Power World. Email Kelly.
Save $1,000 this year 💸 
If this bill passes, say goodbye to local control over all Illinois parks and expect to see open drug and alcohol use, needles, no sanitation and fire hazards, but no ordinary park users.
Expect no retraction or apology. This what they do.
The state’s existing buyout program for its own pensions is the precedent for Chicago, which should be a warning: Look out for similar exaggerated claims and shoddy analysis.
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