Architecture for Future Distribution Systems Including Active Consumers with Rooftop Solar Generation
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This project aims to create a Holonic Multiagent System (HMAS) architecture to support transactive energy market of “active consumers” engaged in buying and selling electricity (locally generated from resources such as rooftop solar photovoltaic) in response to real time electricity pricing. The architecture should require little change to the existing investment in power distribution systems while allowing for the dynamic, adaptive control required to integrate active consumers with current and future combinations of high-variability distributed power sources, such as PV generators and storage batteries. Specific research issues to be addressed include 1) an HMAS architecture for integrating the cyber and physical system aspects all the way from the consumer level to the power grid, 2) stochastic models for consumer behavior that capture consumer preferences and reactions to changing electricity prices, and 3) distributed control actions the utility can take to mitigate adverse effects associated with active consumers and to proactively create conditions beneficial to consumers and the utility.
Submitted by Anil Pahwa
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This project aims to create a Holonic Multiagent System (HMAS) architecture to support transactive energy market of “active consumers” engaged in buying and selling electricity (locally generated from resources such as rooftop solar photovoltaic) in response to real time electricity pricing. The architecture should require little change to the existing investment in power distribution systems while allowing for the dynamic, adaptive control required to integrate active consumers with current and future combinations of high-variability distributed power sources, such as PV generators and storage batteries. Specific research issues to be addressed include 1) an HMAS architecture for integrating the cyber and physical system aspects all the way from the consumer level to the power grid, 2) stochastic models for consumer behavior that capture consumer preferences and reactions to changing electricity prices, and 3) distributed control actions the utility can take to mitigate adverse effects associated with active consumers and to proactively create conditions beneficial to consumers and the utility.