Data Standards for Integrated Energy Planning

This workshop report by Sustainable Energy for All (SEforALL) synthesizes discussions from July 2020 regarding the standardization of data for integrated energy planning. It focuses on the use of geospatial least-cost modelling to achieve universal energy access, identifying critical data gaps and quality standards for both electrification and clean cooking planning, and exploring the convergence of these two sectors through electric cooking.

• Geospatial least-cost modelling is increasingly used for energy prioritization, but its effectiveness is limited by significant data gaps and poor data quality. Models are only as reliable as the data and assumptions they utilize, making accurate and consistent data imperative for universal energy access strategies.
• Integrated energy planning must shift from a traditional supply-side focus to better incorporate demand-side considerations. This requires investments in detailed data regarding electricity growth, demand heterogeneity, and the ability and willingness of consumers to pay.
• Data for energy planning should be treated as dynamic rather than static. Technology costs evolve rapidly due to innovation and economies of scale, and planning horizons often span decades, necessitating the use of time series or historic data to project latent and future demand.
• There is no universal 'ideal' dataset; instead, planners should adopt a pragmatic approach by identifying the minimum data attributes and granularity required to generate necessary insights for specific stakeholders.
• Electrification planning faces specific data shortages regarding low-voltage (LV) line locations, transformers, substations, and the quality and reliability of grid electricity in rural areas. While high-voltage (HV) data is often public, MV and LV data are frequently scattered and inconsistent.
• Clean cooking planning lags behind electrification in the use of geospatial tools due to complex cultural preferences, the practice of 'fuel stacking' (using multiple fuels), and the low monetary cost of biomass. Geospatial tools for cooking can serve as a framework for stakeholder coordination and as a source of market intelligence for identifying attractive markets.
• Significant data gaps exist in the clean cooking sector regarding non-commercial fuel supply chains, consumer-level behavior, and the opportunity cost of time spent gathering fuelwood, which disproportionately affects women and children.
• Advances in remote sensing, AI, and cell phone-based surveys offer cost-effective ways to fill data gaps. Examples include using satellite imagery for building footprint maps and remote monitoring devices to track LPG or electric cooking usage.
• Coordinating electrification and clean cooking planning can create a 'virtuous cycle' where increased electric cookstove penetration drives higher electricity consumption, which in turn lowers unit costs through economies of scale. Research suggests this coordination can double the viability of electric cookstoves compared to independent planning.
• The viability of electric cooking is heavily influenced by national electricity prices and grid reliability. In countries like Ethiopia and Nepal, highly subsidized grid electricity makes e-cooking more viable, though voltage instability and blackouts remain barriers in urban settings.

APA

Sustainable Energy for All (2020). Data Standards for Integrated Energy Planning. https://www.seforall.org/system/files/2021-02/IEP-data-standards.pdf

Chicago

Sustainable Energy for All. Data Standards for Integrated Energy Planning. 2020. https://www.seforall.org/system/files/2021-02/IEP-data-standards.pdf.

Wikipedia

{{cite report |author=Sustainable Energy for All |title=Data Standards for Integrated Energy Planning |date=October 2020 |url=https://www.seforall.org/system/files/2021-02/IEP-data-standards.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{sustainableenergyforall2020data, author = {{Sustainable Energy for All}}, title = {{Data Standards for Integrated Energy Planning}}, institution = {Sustainable Energy for All}, year = {2020}, month = oct, url = {https://www.seforall.org/system/files/2021-02/IEP-data-standards.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }