Data for Renewable Energy Planning, Policy, and Investment

The Renewable Energy (RE) Explorer was developed to support data-driven renewable energy analysis and decision making globally. This platform provides access to various types of geospatial and other data essential for renewable energy analysis and decision making. Geospatial data describe the relative position of something on the earth's surface, including the location of roads, cities, protected lands, and transmission infrastructure. Temporal data describe the time characteristics of data, such as the amount of solar irradiance at a given place on the earth's surface during different hours of the day. Renewable energy data are characterized temporally and spatially, making them critical for informed decision making. The RE Data Explorer, developed by the National Renewable Energy Laboratory, is an innovative web-based platform that allows users to assess and visualize renewable energy potential. This platform informs prospecting, integrated planning, and policymaking to enable clean energy scale-up. The RE Data Explorer provides access to various types of data, including renewable energy resource data, administrative data, environmental data, infrastructure data, grid data, development data, and natural hazards data. Renewable energy resource data provide information on the availability of a particular renewable energy source, such as the quantity of feedstocks or the characteristics of solar energy, for a particular location. Examples of renewable energy resource data include wind, solar, biomass, hydro, geothermal, and marine hydrokinetic data. Administrative data, including census data, can be useful for understanding if renewable energy resources are situated within, near, or far from population centers. Environmental data, such as topographic limitations, environmental attributes, and land-use constraints, can affect the achievable energy capacity and generation of a particular technology. Infrastructure data, including the location of non-electricity-related infrastructure, such as roads, can also affect the achievable energy capacity and generation of a particular technology. Grid data, including transmission infrastructure and other grid attributes, can help decision makers understand the relationship between resources and the infrastructure that will transport those resources. Development data, including electrification rates, poverty rates, and vulnerable communities, can align with key development goals. Natural hazards data, including extreme weather events and other natural hazards, can affect achievable energy generation and feed into resilience planning and decisions. The RE Explorer provides renewable energy data, analytical tools, guidance resources, and technical assistance to developers, policymakers, and decision makers in developing countries. The RE Explorer and the RE Data Explorer are developed by the National Renewable Energy Laboratory and supported by the U.S. Agency for International Development. Energy demand and costs, including electricity and/or heating demand, electricity and/or heating price, building inventory, critical loads, technology cost, incentives, and other data sets that allow for the characterization of energy usage/demand in a given region, inform economic potential, which is one measure of renewable capacity and generation potential. The RE Explorer data gap assessment tool can be used to assess the availability of geospatial data to support decisions in a country or jurisdiction. This tool provides a comprehensive assessment of the data available and identifies gaps in data coverage, quality, and resolution. The RE Explorer data gap assessment tool is an essential resource for developers, policymakers, and decision makers seeking to inform renewable energy decisions with reliable, robust, and validated data.