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SMARTDATA Grid Models

National Renewable Energy Laboratory (NREL)

SMARtDaTa: Standardized multi-scale Models of Anonymized Realistic Distribution and Transmission data

Program: 
ARPA-E Award: 
$2,472,666
Location: 
Golden, CO
Project Term: 
08/24/2016 to 11/30/2019
Project Status: 
ACTIVE
Technical Categories: 
Critical Need: 

Several emerging issues, including the resiliency of electric power delivery during extreme weather events, expanding use of distributed generation, the rapid growth of renewable generation and the economic benefits of improved grid efficiency and flexibility, are challenging the way electricity is delivered from suppliers to consumers. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed on the grid. However, the development of these systems has been hindered because the research community lacks high-fidelity, public, large-scale power system models that realistically represent current and evolving grid characteristics. Due to security and privacy concerns, much of the real data needed to test and validate new tools and techniques is restricted. To help drive additional innovation in the electric power industry, there is a need for grid models that mimic the characteristics of the actual grid, but do not disclose sensitive information.

Project Innovation + Advantages: 

The National Renewable Energy Laboratory (NREL), with partner MIT-Comillas-IIT, will develop combined distribution-transmission power grid models. The team will create distribution models using a version of Comillas' Reference Network Model (RNM) that will be adapted to U.S. utilities and based on real data from a broad range of utility partners. The models will be complemented by the development of customizable scenarios that can be used for accurate algorithm comparisons. These scenarios will take into account unknown factors that affect the grid, such as future power generation technologies, increasing distributed energy resources, varying electrical load, disruptions due to weather events, and repeatable contingency sequences. These enhanced datasets and associated data building tools are intended to provide large-scale test cases that realistically describe potential future grid systems and enable the nation's research community to more accurately test advanced algorithms and control architectures. MIT-Comillas-IIT will assist NREL with the distribution model creation. Alstom Grid will assist in validating the distribution models.

Potential Impact: 

If successful, NREL's project will accelerate the development of new power system optimization algorithms by enabling more comprehensive and transparent testing. New grid optimization algorithms could increase the grid's resiliency and flexibility, improving its security during extreme weather and other threats. Moreover, the team's technology could enable greater integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. Finally, the project could lead to greater efficiencies for grid operators and power generators and therefore help reduce operating costs.

Contacts
ARPA-E Program Director: 
Dr. Kory Hedman
Project Contact: 
Dr. Bri-Mathias Hodge
Partners
Alstom Grid
Massachusetts Institute of Technology
Release Date: 
1/15/2016