Renewable Energy Data and Analysis for Decision-Making
Accurate and up-to-date renewable energy resource data and other geographic information system (GIS) data sets can facilitate smart decision-making. Analysis then turns this data into useful information for decision makers. Data-driven decisions enable ambitious, cost-effective, and achievable outcomes for renewable energy deployment.
Data-Driven Renewable Energy Decisions
Renewable energy resource data and accompanying GIS data sets enable renewable energy goal setting, power sector planning, renewable energy policymaking, and investment decisions.
What data enable good decision-making?
Renewable Energy resource data and other geospatial data enable renewable energy decisions. These data sets vary in resolution, quality, and usefulness depending on the application. Renewable energy resource data sets can be measured or modeled and will vary in spatial and temporal resolution. Ultimately, data and analytical needs are dictated by the decisions being made.
In addition to renewable energy resource data, other modeled or measured GIS layers play an important role in decision-making. A few examples include land use, weather data, population density, and existing transmission lines. By combining data sets in different ways, decision makers can synthesize new information about renewable energy potential to guide planning, policy-making, and investment.
Who uses renewable energy resource data and analysis for decisions?
Policymakers, planners, investors, technicians, universities, and other supporting institutions all rely on renewable energy resource data to make meaningful and impactful decisions.
How do I use data to make decisions?
Geospatial data and analysis allows users get powerful information from data that can aid in decision making. Examples of the types of analysis that can be supported range from resource technical potential to system and grid integration modeling to support power sector planning.