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Frequency-Based Load Control Architecture

Northwestern University

A Novel Hierarchical Frequency-Based Load Control Architecture 

ARPA-E Award: 
Evanston, IL
Project Term: 
06/15/2016 to 06/14/2019
Project Status: 
Technical Categories: 
Critical Need: 
The infrastructure that defines the U.S. electric grid is based largely on pre-digital technologies developed in the first part of the 20th century. In subsequent decades, grid development has evolved through emphasis on safety, accessibility, and reliability to security and resiliency. Throughout this evolution, the grid mainly relied on centralized power plants and developed protocols to provide system reliability based on that model. However, the increasing use of renewable generation and distributed energy resources (DER), such as residential solar and home energy storage, along with customers' changing energy usage patterns are leading to greater uncertainty and variability in the electric grid. New tools are required to create a flexible and modern electric grid that can meet this increase in renewable generation and DERs, while providing the quality of service, resiliency, and reliability that customers expect.
Project Innovation + Advantages: 
Northwestern University and its partners will develop a frequency-based load control architecture to provide additional frequency response capability and allow increased renewable generation on the grid. The work will focus on developing and demonstrating algorithms that adapt to rapid changes of loads, generation, and system configuration while taking into account various constraints arising from the transmission and distribution networks. The multi-layer control architecture makes it possible to simultaneously ensure system stability at the transmission network level, control frequency at the local distribution network level, and maintain the quality-of-service for individual customers at the building level, all under a single framework. At the transmission level, coordination among different areas will be achieved through a centralized scheme to ensure stable frequency synchronization, while the control decisions within a single area will be made based on local information. The efficiency of the centralized scheme will be ensured by decomposing the network into smaller components on which the control problem is solved individually. At the local distribution network level, the control scheme will be decentralized, in which control decisions are made based on the state of the neighboring nodes. At the building level, dynamic models for flexible appliances and DERs will be developed and used to design algorithms to optimally follow a given aggregated load profile.
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.
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.
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.
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.
ARPA-E Program Director: 
Dr. Sonja Glavaski
Project Contact: 
Dr. Adilson Motter
Argonne National Laboratory
OPAL-RT Technologies
Schneider Electric
Release Date: