Stochastic Optimal Power Flow

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Program:
NODES
Award:
$4,354,566
Location:
Tempe, Arizona
Status:
ALUMNI
Project Term:
07/11/2016 - 03/31/2021
Website:

Technology Description:

Arizona State University (ASU) will develop a stochastic optimal power flow (SOPF) framework, which would integrate uncertainty from renewable resources, load, distributed storage, and demand response technologies into bulk power system management in a holistic manner. The team will develop SOPF algorithms for the security-constrained economic dispatch (SCED) problem used to manage variability in the electric grid. The algorithms will be implemented in a software tool to provide system operators with real-time guidance to help coordinate between bulk generation and large numbers of DERs and demand response. ASU’s project features unique data-analytics based short-term forecast for bulk and distributed wind and solar generation utilized by the advisory tool that generates real-time recommendations for market operators based on the SOPF algorithm outputs.

Potential Impact:

If successful, projects included in the NODES Program will develop innovative hardware and software solutions to integrate and coordinate generation, transmission, and end-use energy systems at various points on the electric grid. These control systems will enable real-time coordination between distributed generation, such as rooftop and community solar assets and bulk power generation, while proactively shaping electric load. This will alleviate periods of costly peak demand, reduce wasted energy, and increase renewables penetration on the grid.

Security:

Innovations from this program would help the U.S. grid assimilate at least 50% of renewable generation and provide system reliability and resiliency while managing emerging energy generation and consumption patterns.

Environment:

The addition of flexible loads and DERs into the U.S. grid could offset 3.3 quads of thermal generation and displace 290 million tons of CO2 emissions.

Economy:

Using the NODES approach to integrate flexible loads and DERs into the grid could replace 4.5 GW of spinning reserves (i.e. generation capacity on stand-by in case of outages and unforeseen intermittency), a value of $3.3 billion per year. A more efficient and reliable grid would help protect U.S. businesses from costly power outages and brownouts.

Contact

ARPA-E Program Director:
Dr. Mario Garcia-Sanz
Project Contact:
Junshan Zhang
Press and General Inquiries Email:
ARPA-E-Comms@hq.doe.gov
Project Contact Email:
junshan.zhang@asu.edu

Partners

National Renewable Energy Laboratory
PJM Interconnection
Nexant, Inc.
Sandia National Laboratory

Related Projects

• Arizona State University (ASU) - Stochastic Optimal Power Flow
• Det Norske Veritas (DNV GL) - Internet of Energy for Optimized Distributed Energy Resources
• Eaton Corporation - Cloud-Based DER Control
• General Electric (GE) Global Research - Synthetic Reserves from Distributed Flexible Resources
• National Renewable Energy Laboratory (NREL) - Real-time Distributed Energy Resource Optimization
• National Rural Electric Cooperative Association (NRECA) - Autonomous Load Control
• Northwestern University - Frequency-Based Load Control Architecture
• Pacific Northwest National Laboratory (PNNL) - Incentive-Based Control of Distributed Assets
• Stanford University - Distributed Energy Resource Networks
• University of California, San Diego (UC San Diego) - Distributed Grid Control of Flexible Loads
• University of Illinois, Urbana-Champaign (UIUC) - Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulating Reserves
• University of Minnesota (UMN) - Enabling the Grid of the Future
• University of Vermont (UVM) - Packetized Energy Management

Release Date:
02/04/2015