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Title: Agent-Based Coordination Scheme For PV Integration (ABC4PV)
Funding Opportunity: Sustainable and Holistic Integration of Energy Storage and Solar PV
SunShot Subprogram: Systems Integration
Location: Pittsburgh, Pennsylvania
Amount Awarded: $1,036,963
Awardee Cost Share: $1,038,083
This project will develop and demonstrate a distributed, agent-based control system to integrate smart inverters, energy storage, and commercial off-the-shelf home automation controllers and smart thermostats. The system will optimize photovoltaic (PV) generation, storage, and load consumption behaviors using high-performance, distributed algorithms.
The hardware of the project will consist of “units,” each with PV, battery storage, and a load controller, which may be a smart thermostat or plug load controller. Each unit will have an overall controller that optimizes the operation of the units by, for example, determining when it is optimal to use power from the PV versus storing the power, to accumulate power in the battery versus using battery power, or to buy power from the grid versus delivering power from the grid. The project will develop, test, and demonstrate the hardware and software needed to run the agent-based control system, including the interfaces to the battery, storage, and load controller assets and secure communications. Mathematical analysis of the optimal distributed control methodology will be performed and operational characteristics of the feeder network such as the installed controllable components and the quality of load and solar forecasting will be employed in the decision-making process.
The Open Modeling Framework (OMF), based on DOE’s GridLAB-D high resolution dynamic power flow modelling tool, will be used to test the control algorithms and different strategies for deployment on a variety of real or taxonomic feeders. If successful, the project will not only demonstrate the value of integrated PV, storage, and load control, but the value of distributed, agent-based grid control. The OMF implementation of the distributed control methodology emulates scenarios very close to actual field operation and reduces the risk of differences between the simulation used in development and operation of the actual agents in the field. An open-source implementation of the developed agent-based control algorithms and related coordination software will be made available for researchers and industry.
Download the presentation from Carnegie Mellon University at the SHINES Technical Kickoff Meeting.