Grid Data and Tools

NREL develops data sets and tools to support the integration of distributed and renewable energy into the electric power system.

Grid Tools


Autonomous Grids – Identification, Learning, and Estimation simplifies the management of large sensor datasets and offers a universal bridge to common analysis platforms.


ALSAT creates load profiles for individual customer nodes with realistic diversity and variability to support accurate time-series analysis for interconnection studies.


CYMEpy provides users with Hierarchical Engine for Large-scale Infrastructure Co-Simulation bindings for a popular distribution system simulator.


Flexible Energy Scheduling Tool for Integrating Variable Generation simulates the electric power system to help researchers understand the impacts of variability.


The Flexible Load Aggregator and Risk Estimator tool gives distributed energy resource aggregators a way to manage their fleet of flexible load resources.


The Object-Oriented Controllable High-Resolution Residential Energy Model allows researchers to study emerging technologies in residential buildings.


OptGrid autonomously optimizes power flow between distributed energy resources to bring real-time management to the grid edge.


PyDSS supports a distribution system simulator by expanding on its organizational, analytical, and visualization capabilities.


PyPSSE supports the Power System Simulator for Engineering by allowing users to perform time series power flow and dynamic simulation for power systems.


PREconfiguring and Controlling Inverter SEt-points helps utilities quickly establish optimal inverter settings for distributed solar energy.

Related Tools


The Distributed Generation Market Demand model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities through 2050.


The demand-side grid model creates comprehensive electricity load datasets at high temporal, geographic, sectoral, and end-use resolution, enabling detailed analyses of current and projected end-use loads.


Energy Management Information Systems aggregate facility data to optimize energy use for federal buildings and campuses.


The Hierarchical Engine for Large-Scale Infrastructure Co-Simulation framework links multiple off-the-shelf grid simulation tools as one unified model, exchanging data at each time step.


The Multi-Timescale Integrated Dynamic and Scheduling framework bridges modeling and analysis gaps of different timescales between economics, reliability, and stability of grid operation with extremely high renewable penetrations.


The Probabilistic Resource Adequacy Suite provides an open-source, research-oriented collection of tools for analyzing resource adequacy of bulk power systems.


The Regional Energy Deployment System—NREL's flagship capacity expansion planning model—simulates the evolution of the bulk power system through 2050 or later.


The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority.


The Scalable Integrated Infrastructure Planning model addresses the scheduling problems and dynamic simulations of quasi-static infrastructure systems.

Grid Datasets

Distribution Grid Atlas

The Distribution Grid Atlas is a set of statistical hosting capacity models and representative, geospatially relevant models for substations, feeders, and low-voltage networks.


The Reliability Test System—Grid Modernization Lab Consortium is a modernized, medium-scale test dataset with many features of modern electric power systems.


Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios offers high-quality distribution network models and advanced tools to generate model scenarios.

Test Case Repository for High Renewable Study

The Test Case Repository for High Renewable Study contains open-source test cases, models, and datasets to help researchers evaluate ideas for a high-renewable future.

Related Datasets


The Annual Technology Baseline provides a consistent set of U.S. technology cost and performance data to inform electric and transportation sector analyses.

Standard Scenarios

The Standard Scenarios are a suite of forward-looking scenarios of the U.S. power sector that are released annually to capture a range of possible futures and inform energy analysis.