Harmonized geospatial data to support infrastructure siting feasibility planning for energy system transitions

Area of Science:

• Environmental science
• Energy systems analysis
• Geospatial data science

Background:

• Electricity demand is rising due to climate change, energy transitions, and socioeconomic shifts.
• While efficiency and distributed resources help, new utility-scale power generation is still needed in the U.S.
• Existing capacity expansion models lack the granularity for location- and technology-specific power plant siting challenges.

Purpose of the Study:

• To develop a high-resolution geospatial data package for evaluating power plant siting suitability.
• To support capacity expansion planning by addressing location- and technology-specific siting factors.
• To provide a customizable tool for assessing future energy infrastructure needs.

Main Methods:

• Creation of the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package.
• Inclusion of 264 suitability layers for 56 power plant technologies.
• Harmonization of data for easy ingestion into geospatially-enabled modeling software.

Main Results:

• GRIDCERF provides a comprehensive dataset for assessing siting suitability for various power plant types.
• The data package enables detailed, customized analysis for renewable and non-renewable energy resources.
• Facilitates robust evaluation of future energy infrastructure under varying conditions.

Conclusions:

• GRIDCERF enhances the capability to plan new utility-scale power generation resources in the U.S.
• The data package addresses limitations in current energy modeling for power plant siting.
• Enables more informed and adaptable energy infrastructure development decisions.