Energy Access Explorer

Climate-Relevant Problem it Addresses:

Energy planning in many low- and middle-income countries is constrained by fragmented, inaccessible, and low-quality geospatial data. This limits countries' ability to:

• prioritise low-carbon electrification pathways
• align energy expansion with nationally determined contributions
• target vulnerable populations for climate-resilient infrastructure
• coordinate transparently across agencies and financiers

Developed by WRI in collaboration with over 300 partners, Energy Access Explorer supports climate-compatible energy transitions through a data-informed, integrated, and inclusive approach to universal energy access. It provides a transparent, interactive geospatial platform to visualise and analyse high-priority areas for energy interventions across Africa and South Asia.

Climate-Relevant Objectives:

• Mitigation
• Adaptation and resilience
• Climate monitoring
• Cross-cutting (data infrastructure, interoperability, digital MRV)

Sector Applications:

• Agriculture, forestry and other land use
• Energy

Common Deployment Settings:

• Community
• City/Municipal
• National

International Frameworks it Aligns With:

• IPCC methodological guidance
• UNFCCC guidelines
• NDC tracking and implementation
• National inventory systems / transparency frameworks
• National Adaptation Plans (NAPs)
• Long-term low-emission development strategies (LT-LEDS)

Measurable Outcomes it Can Help Facilitate:

• Improved data quality and reduced uncertainty
• Strengthened adaptation planning and resilience capacity
• More informed policy, regulatory, and investment decisions
• Enhanced inter-agency coordination and governance

Specific Decisions or Actions it Has Helped Facilitate:

Deployment Countries:

Ethiopia, India, Kenya, Nepal, Nigeria, Tanzania, Uganda, Zambia, Democratic Republic of Congo

Adopting Organisations:

Food and Agriculture Organization, United Nations Human Rights Council (UNHRC), United Nations Development Programme, United Nations Industrial Development Organization, World Health Organization (WHO), World Bank

Key Performance or Impact Indicators:

EAE's open-source nature has proven to be a scalable solution at both national and subnational levels. With over 40,000 users, 48% of whom are women, users can customise analyses and identify areas of interest based on their perspective. In Kenya, EAE has supported local governments in Makueni, Narok, and Kitui counties in developing County Energy Plans that contribute to Kenya's Integrated National Energy Plan. At the national level, EAE informs about least-cost electrification planning and clean cooking strategies. In Ethiopia, the Ministry of Water and Energy, in collaboration with the World Bank, used EAE to prioritise off-grid electrification for 19 million people across 145 woredas through a results-based financing programme. In Nigeria, where over 85 million people lack electricity, the Rural Electrification Agency (REA) is using EAE to support its Energising Agriculture Programme and the $0.5 billion Africa Mini Grids Programme, recognised among the top partnerships transforming Nigeria's renewable energy landscape. Across Ethiopia, Zambia, Uganda, Tanzania, and India, EAE is helping stakeholders identify electrification priorities for healthcare, education, agriculture, and livelihoods, enhancing energy access for millions.

Modular Design:

EAE is built using a modular architecture consisting of:

• The EAE frontend is an interactive, web-based geospatial interface for visualizing, overlaying, and analyzing multiple geospatial data layers (e.g., population, grid, health, agriculture, renewable resources). It allows users to dynamically combine layers to identify priority areas for electrification and clean energy, supporting customizable weighting and scenario-building (e.g., least-cost, healthcare access, productive use, climate resilience). Results are generated in real-time, displayed on maps, and provided as downloadable outputs for transparent comparison. Designed for accessibility, it prioritizes usability for non-technical users, functions in low-bandwidth settings, and lowers barriers to inclusive, data-informed energy planning.
• Backend services. EAE's backend infrastructure provides an essential, user-friendly data governance system for accessible, reliable, and actionable energy data. Designed for seamless data integration, standardization, and sharing, EAE offers a centralized, flexible platform for governments, utilities, and development partners to utilize high-quality geospatial energy data. The clear, shareable data format lowers access barriers, encouraging stakeholders to contribute and collaborate. Prioritizing interoperability and ease of use, the system reduces technical barriers, fostering an inclusive data-sharing ecosystem.

Data Processing:

Data Extraction Mechanism(s):

API

Interoperability, Integration, and Adapters*:

Level 3 Standardized: Adheres to domain-specific standards, but requires some configuration to link.

EAE can integrate with National electrification master plans, subnational planning portals, NDC implementation tracking systems, rural electrification monitoring dashboards, and investment planning tools, which can all be integrated with the system because data can be exported in standard formats, allowing it to easily integrate into MRV systems and GIS workflows.

Adoption Readiness**:

Level 4 Orchestrated / Cloud-Optimized: The solution is designed for modern infrastructure. It includes "Infrastructure as Code" that allows for automated deployment into cloud environments with built-in scaling and management.

Scalability, Performance, and Reliability:

• Supports 40,000+ users.
• Cloud-based deployment.
• Country instances are scalable independently.
• Modular replication reduces deployment cost.
• Used at the national scale across multiple countries.

Computing Power:

The solution is primarily a web-based GIS visualization tool with moderate server requirements for deployment and operation. Its design is explicitly optimized for low-bandwidth environments and focused on usability in low-resource contexts, implying a design that minimizes data transfer and client-side processing, which consequently keeps energy use at scale relatively efficient compared to more resource-intensive GIS platforms.