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Effective power management starts at the power source, and for solar panels that means capturing as many impinging photons as possible, according to EE Times. In open settings with a full or nearly full view of the sky, pointing panels toward maximum sun exposure and using mechanical tracking where feasible is relatively straightforward in principle.
Dense urban settings present a different and harder problem, EE Times reports, because nearby buildings, shadows, reflections from glass and structures, and other local conditions directly affect the light path. The challenge is especially acute for smaller fixed panels used in localized, non-grid-connected applications such as small charging stations, signage and kiosks, where simply aiming at the sun’s maximum is often not the best real-world solution.
Tools exist to assess an intended setting and maximize solar collection there, but illumination, or irradiance, is typically evaluated using 3D models that fail to capture small nearby structures affecting the light path and net irradiance. Alongside efforts to improve panel efficiency, power conversion and management electronics, and the overall power path, improving up-front energy capture is therefore seen as worthwhile.
A research team in the Engineering School at Columbia University in New York has devised a system in which a single spherical photograph taken at a target site can determine the year-round optimal orientation and angling of a panel, according to EE Times. The approach accounts for the sun’s angle, nearby shading, diffuse light from a partially visible sky, reflection off windows and building facades, and other characteristics of the urban canyon.
The researchers claimed the system can boost solar capture by 10% to as high as 30%, a meaningful gain that comes at no cost. The technology uses shadows and lines in the image to determine camera orientation, then segments the image to assess how various elements in the frame will contribute to overall power generation.
Standard methods can produce large errors because they fail to account for variations in the brightness of the sky section visible to a panel throughout the day and year, as well as light reflected off surrounding buildings. The team found that such reflections account for roughly 12% of a panel’s total annual energy on average.
The research showed that a single spherical image can identify the best fixed orientation for a panel. The underlying insight is that a photograph taken from a panel’s location encodes substantial information: shadows reveal the sun’s direction, and straight architectural lines indicate the direction of gravity.
That information is used to establish the image’s orientation relative to the planet. A segmentation algorithm identifies the portion of sky visible to the panel, while the appearance of surrounding buildings provides cues about their spatial layout and construction materials.
The laptop-based system then forecasts how the sun will move through the visible sky across the day and year, estimates how much light will bounce off surrounding buildings onto the panel, and draws on historical weather data to extend the forecast to cloudy and overcast conditions rather than only clear days.
The team used a physically based renderer to simulate scene irradiance as a function of the sun’s position. At one simulated location over the course of a day, scene irradiance varied smoothly with time despite the many objects casting shadows and producing reflections within the canyon.
Based on those observations, the researchers developed a neural network to predict a panel’s scene irradiance from a single image. The network contains a vision transformer backbone and a multilayer perceptron head that outputs scene irradiance for any sun position.
A common rule of thumb holds that the best fixed panel orientation points toward the equator with a zenith angle equal to the panel’s latitude, assuming a clear view of the sky, which is rarely the case in urban settings. The researchers instead showed that a single spherical image taken near an existing panel can identify the best fixed orientation, which may differ substantially from that rule. They also validated the approach using actual irradiance measurements in urban canyons.
The work is detailed in a 23-page paper titled Forecasting solar energy using a single image, published in Solar Energy, according to EE Times. The paper covers the problem, solution concept, alternatives, situation analysis, discussion of 3D geometries, urban canyon realities and optical considerations, among other topics. The formal posting is behind a paywall, while an open version is posted at arXiv, a free, open-access, non-profit repository that hosts scholarly preprints before formal peer review and journal publication.
Interactive table based on the Store Companies dataset for this report.
This report provides an in-depth analysis of the Solar Panels market in the United States, covering market size, growth trajectory, demand structure, supply capability, trade flows, pricing, competitive landscape, and forecast to 2035.
The study is designed for manufacturers, distributors, importers, exporters, investors, procurement teams, advisors, and strategy teams that need a consistent, data-driven view of market dynamics and a transparent analytical definition of the product scope.
This report covers photovoltaic (PV) solar panels, which are devices that convert sunlight directly into electricity. It encompasses the global market for finished modules, including all major product technologies and form factors designed for a wide range of end-use applications.
The report combines the standard market-statistics backbone with strategic chapters that are useful for commercial planning, sourcing decisions, market entry, competitor monitoring, and portfolio prioritization.
The market is segmented into decision-relevant buckets so that demand drivers, pricing logic, supply constraints, and competitive positions can be compared across the same analytical frame.
The market data is classified and analyzed according to international trade codes, primarily under the Harmonized System (HS) headings for photovoltaic cells and electric generating sets. This ensures consistent tracking of trade flows for assembled solar modules and relevant apparatus across global markets.
Coverage focuses on United States and includes demand, supply capability where present, trade flows, pricing, competition, and outlook.
The report combines official statistics, trade records, company disclosures, product-level evidence, and analyst validation. Data are standardized, reconciled, and cross-checked to keep market sizing, trade flows, pricing, and forecasts comparable across countries and time periods.
All indicators are mapped to a consistent product definition and reviewed against the segmentation framework used in the Table of Contents.
Report Scope and Analytical Framing
Concise View of Market Direction
Market Size, Growth and Scenario Framing
Commercial and Technical Scope
How the Market Splits Into Decision-Relevant Buckets
Where Demand Comes From and How It Behaves
Supply Footprint and Value Capture
Trade Flows and External Dependence
Price Formation and Revenue Logic
Who Wins and Why
How the Domestic Market Works
Commercial Entry and Scaling Priorities
Where the Best Expansion Logic Sits
Leading Players and Strategic Archetypes
How the Report Was Built
Specializes in cadmium telluride thin-film module technology
Operates a major U.S. solar module manufacturing facility in Georgia
Markets its back-contact panel technology under the SunPower brand
Operates the G1_Dallas solar module manufacturing facility
Manufactures its solar panels in San Antonio, Texas
Operates U.S. module manufacturing facilities in Washington and South Carolina
Produces modules at its U.S. facility in Minnesota
Offers bifacial and monofacial module product lines
Offers bifacial modules for utility-scale and commercial projects
U.S. solar module manufacturer with production in California
Provides solar modules under its proprietary Lumio brand
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