This paper performs computational studies and develops control schemes for a virtual power plant (VPP) network formed by a community of homes with rooftop solar PV generation, and battery energy storage. Appropriate control and scheduling of the battery operations, and peer-peer power flow between the homes provide a possible solutions for reducing the higher costs and uncertainties brought to grid by high solar PV penetration. The residential community studied here includes twelve homes categorized into four types depending on whether they have energy storage or rooftop solar PV panels. The homes exchange power among themselves, and the real-time electricity rate and the energy assignment for each are decided based on their individual bidding schemes. The homes benefit due to the lower electricity rate enabled by this aggregation, as compared with that available from the utility grid. In this work, the PV generation and load consumption for the different types of homes are calculated from building models. Simulation studies demonstrate that the advantages of the proposed transactive power flow include lower maximum power demand as well as reduced peak-peak power on the duck curve.
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The support of University of Kentucky, the L. Stanley Pigman endowment, and of the SPARK program and the Power and Energy Institute of Kentucky (PEIK) is gratefully acknowledged.
Gong, Huangjie; Rallabandi, Vandana; and Ionel, Dan M., "Load Variation Reduction by Aggregation in a Community of Rooftop PV Residences" (2019). Power and Energy Institute of Kentucky Faculty Publications. 18.