As these regions develop, energy infrastructure must be deployed intelligently to enable economic growth, improve health and education outcomes, enhance climate resilience for the world’s most vulnerable populations, and mitigate climate change.
In order to achieve these goals in accordance with timelines set forth by the Paris Agreement and United Nations Sustainable Development Goals, a significant scaling of investment will be required. The IEA and IFC together estimate that private sector annual financing for clean energy in LMICs outside of China will need to increase from $135B today to $0.9-1.1T by the early 2030s, with an additional $80-100B of concessional support per year required to catalyze this influx.
We partner with developers, utilities, and universities to train these systems using sparse metered consumption data and leverage a variety of remote sensing datasets. This novel approach enables us to develop and update accessible, detailed electricity consumption datasets year over year, and ultimately track progress and inform stakeholder decision-making.
Ensuring that system planners worldwide are working with high-resolution electricity access and demand data will expedite the realization of universal access for all by enabling the efficient allocation of resources. Considering both the magnitude of the scale-up in investment and the ambitious execution timeline required to meet international climate goals, we feel that unrestricted access to this data is essential to achieving maximum social benefit. We are therefore committed to ensuring this platform is accessible to all. The results made available through the OEMaps platform will remain open access (OdBL License) and the code will remain open source (MIT License).
Select applications include:
Industry standard demand assessment involves direct community engagement, typically in the form of survey administration. This is costly in terms of both time and manpower, and produces results with limited reliability due to the consumer tendency to declare aspirational consumption values exceeding their ability-to-pay.
Accurate, high-resolution demand datasets including estimation uncertainties aid in the projection of renewable energy project ROIs during the due diligence process.
Having an accurate depiction of access and demand distributions enables the design of efficient tariff subsidies so the social benefit from state financial resources is maximized and energy efficiency is appropriately incentivized.
Use as inputs to techno-economic electricity system planning tools to make cost-optimal technology selections (standalone, minigrid, or grid-connected) and design efficient grid extension.
Determining the appropriate type and level of programmatic support to crowd in private investment requires accurate and up-to-date information reflecting consumer access and ability-to-pay.
Up-to-date consumer demand profiles provide regulators valuable insight into where economic growth is lagging supply, thus serving as the basis for demand stimulation programs.