Introduction
The IEA maintains the world’s most comprehensive database on energy and related statistics, including data on access to electricity. The IEA was the first international agency to start tracking global electricity access data in the early 2000s and since then also provides latest projections in the World Energy Outlook. The IEA is also one of the co-custodians of tracking progress on UN Sustainable Development Goal 7, or SDG7. As of 2022, The IEA estimates 775 million people worldwide are without access to electricity, of which 600 million live in Africa. Since 2014, Africa has made steady progress in reducing the number of people without access to electricity, but the Covid-19 pandemic and the 2022 energy crisis have now reversed this trend.

Access to electricity data workflow

The template on its own, however, cannot capture some of the nuanced challenges faced when validating and processing data, including making countryspecific determinations on how to manage issues of double-counting, adjusting to country definitions, and how to fill data gaps. The guidelines outlined in this report focus on these important details, as well as provide clear definitions and explanations of the key principles of a supply-side data approach.

Defining connection technology types Households can gain access to electricity through different sources or technologies, including a connection to the main grid, a mini-grid or the installation of a stand-alone system. Mini-grids and stand-alone systems are often referred to as off-grid solutions, however both can be operated in conjunction with the grid as backup or secondary power sources.

Connections by type of technology

Comparing minimum levels of energy services defined by different organisations

The IEA maintains a slightly higher threshold for the minimum level of service in its access definition than the World Bank, but, similar to the multi-tier framework, sets different thresholds to reflect the varying contexts. This is underpinned by the objective that access planning must aim at supporting rising levels of household energy use in the future, while balancing the consumers’ ability to pay. Harmonising access to electricity definitions used by organisations in the field and by countries is an important but elusive task, raising a challenge for standardising how countries report their data. Some countries, such as Zambia or Rwanda, have chosen to define electricity access at a specific MTF tier (Tier 2 and Tier 1, respectively). The use of metadata to clarify definitions in administrative data is a critical component of enabling transparency in order to improve comparability of access indicators (see Section 3.3, “Coherence, comparability, and transparency of released data: Metadata”).

Household sizes and population assumptions After tabulating the number of connections, household sizes are used to estimate the number of people benefitting from each connection, which then can be used to calculate total access rates (see figure below). However, using the national average household size can contribute to large differences between supply-side data estimates and survey-based approaches. Since household sizes can vary substantially, especially between rural and urban areas, we recommend using average household size by jurisdiction, when possible.

From counting connections to computing access to electricity rates

In the figure below an example of a time series issue (i.e. time-series break for rural connections) leading to an arithmetic check issue (i.e. national connections lower than the sum of rural plus urban) is illustrated. The arithmetic check in this specific case would reveal that there is an issue but not where it is coming from while the analysis of the time series suggests that the problem could be coming from rural connections data because of a sudden spike, which could be due to a revision in the way the data provider assessed off-grid connections. However, there is the possibility that the time series break is justified (e.g. an acceleration of an off-grid programme) and data providers need to be contacted to confirm. If the spike in rural connection is verified and confirmed, national connections must be recalculated, otherwise rural connections can be estimated as the difference.

Example of internal consistency checks on the number of grid connections

Developing and maintaining up-to-date geospatial datasets enables more countries to shift to GIS access planning tools, which are quickly becoming the standard for supporting electrification efforts. Many GIS modelling tools and datasets are available to support access planners, which the IEA maintains a list of on its website as a part of this programme. The IEA’s Africa Energy Outlook 2022 provides an example of how GIS tools can be used to determine a contextspecific, least-cost electrification plan. This is done by overlaying several layers of information and performing an optimisation that considers the location of nonelectrified settlements, their respective distance from the nearest national power grid and the renewable resources present on site, among other variables. This type of analysis is very useful for performing large-scale analyses to inform individual country policies and educate both the private sector and international organisations involved in energy access about opportunities in different markets.

New connections by type in the IEA Sustainable Africa Scenario

The IEA is working to improve geospatial data and tools for integrated electrification planning, in its Power Africa’s Data-Driven Electrification Planning programme. A newly constructed tool aims to better estimate demand by household in different countries and regions, both when first connected and several years after having electricity. This then allows for better estimates of electricity demand based on satellite images of buildings within a community, which helps companies better size grid extensions or mini-grids, saving costs and improving the investment case for such projects.

Mobile phone use as a proxy for access to electricity The high penetration of mobile telephone coverage has provided an alternate data source that can be used to understand access to electricity. In the past few years, studies have shown how this data can be turned into critical insights to support demand estimation and electrification planning. Mobile phone metadata – including app usage, location and charging patterns/characteristics – provides proxy indicators of population density, economic activity and social characteristics of a population. Moreover, this data, which is available in real-time, can be used to estimate electricity consumption per capita, permitting access rates to be assessed at a high level of spatial and temporal resolution, and at a considerably lower cost than survey data. Similar to issues with remote sensing, data from mobile phones must first be locally calibrated using ground-level survey data. One of the current stumbling blocks to using phone data to estimate electricity access is solving privacy concerns and ensure individuals can’t be identified in the datasets.

Source:http://IEA