reV: The Renewable Energy Potential Model
The Renewable Energy Potential (reV) model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate renewable energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics.
NREL developed the reV model to help utility planners, regional and national agencies, project and land developers, and researchers assess renewable energy resource potential. Available as open source since February 2020, the reV model currently supports photovoltaic, concentrating solar power, and wind turbine technologies. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades.
By automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and renewable energy cost supply curves.
The reV model currently provides broad coverage across North America, South and Central Asia, the Middle East, South America, and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.
To access the reV model, you must first read NREL's disclaimer and agree to its terms.
How the Model Works
The reV model includes highly dynamic, user-defined modules that function at different spatial and temporal resolutions, allowing users to assess resource potential, technical potential, and supply curves at varying levels of detail. This modular architecture can execute all or parts of the project pipeline and allow for custom inputs to any of the modules. The modular approach allows for various useful products at the ends of each discrete module for different analyses, including interannual variability of solar and wind resources, impacts of varying land-use constraints on installable capacity, effects of regional cost multipliers on the levelized cost of electricity (LCOE), and more.
Modeling System Performance
Coupled with NREL's System Advisor Model, the reV model’s generation module estimates system performance based on user-defined parameters including solar panel tilt angle, azimuth, inverter load ratio, efficiency, and others. Wind systems are defined based on their hub height, rotor diameter, power curve, and other wind-specific configurations.
The reV model simultaneously reads tens of terabytes of time-series solar or wind data from state-of-art resource data sets—the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) Toolkit, both of which have recently been made available on the cloud—enabling the execution of reV beyond the confines of NREL’s high-performance computing capabilities.
Calculating Site-Based Levelized Cost of Energy
The reV model estimates the LCOE for a site, which represents the average revenue per unit of electricity generated needed to make up for the costs of building and operating a generating plant. Capacity generation from the reV model goes into the LCOE module and outputs cost data that provide insight into economic competitiveness, relative performance competitiveness, and regional differences driven by cost assumptions.
Considering Land Use Characteristics
The spatial module land exclusion in reV considers technical and sociopolitical limitations to land access for renewable energy projects. This includes technical barriers (e.g., water bodies, steep terrain), regulatory restrictions (e.g., federal, state, or local protected land, urban and suburban areas, protected wildlife species habitat), or stakeholder constraints (e.g., U.S. Forest Service lands, Department of Defense lands, and private conservation areas).
This analysis brings to light the land access limitations that can be experienced by renewable energy project developers, thereby helping developers to focus on areas that have a greater potential for successful deployment of new solar or wind capacity.
Cost and Capacity
The renewable energy supply curve module in reV applies a spatial optimization algorithm that sorts developable sites based on both LCOE and transmission access. Taking into account infrastructure modeling and tie-in-costs, the algorithm calculates the grid interconnection costs for all potential links from developable sites to nearby transmission assets. Each site is ranked relative to other sites to illuminate the varying costs related to where the sites fall across a geographic plane.
The reV Exchange Model (reVX), another open-source package, provides post-processing modules to couple reV with capacity expansion models (e.g., the Regional Energy Deployment System Model and the Resource Planning Model ) and production cost models (e.g., PLEXOS) used at NREL and by external collaborators. Model interoperability modules are custom designed to interface with the specific needs of each downstream model.
To access the reVX tool, you must first read NREL's disclaimer and agree to its terms.
Along with reV and reVX, the reV team has also open-sourced the Resource Extraction Tool (rex), a set of modules aimed at facilitating access to the state-of-art resource data sets used by reV (NSRDB and WIND Toolkit). The tool also provides a variety of computational and research tools (e.g., logging, parallel computation, HDF5 file formatting), that while developed for reV, are applicable more widely to users of NREL’s large resource data sets.
To access the rex tool, you must first read NREL’s disclaimer and agree to its terms.
Amazon Web Services Accessibility
The reV model currently runs on NREL’s high-performance computing system and now users can access the full power of reV from their own systems through Amazon Web Services (AWS), a cloud computing platform. NREL has migrated several web applications to the AWS environment to expand access and scalability, allowing users to perform detailed analysis with massive data sets from their desktop.
The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling, NREL Technical Report (2019)