Abstract
Virtual power plants (VPPs) are increasingly utilized to efficiently coordinate and manage the increasing number of distributed energy resources (DERs) within power grids. Traditionally, VPP models have prioritized commercial or financial objectives, often overlooking the technical limitations inherent in the distribution system. A technical VPP (TVPP) operational framework is proposed in this work to enhance the scheduling efficiency of various DERs participating in a day-ahead energy market while considering grid management limitations. This paper presents the formulation of the optimal operation of TVPP within a reconfigurable distribution network as a non-linear optimization problem. An incentive-based demand response model has been incorporated into the TVPP scheduling operation to mitigate energy reliance on the utility grid during peak demand periods. The proposed work is analyzed using a TVPP that aggregates solar and wind energy sources, energy storage systems, and consumers with flexible loads, all connected at various nodes of a 33-bus radial distribution network. The outcome of the TVPP scheduling operation confirms the reduction in power loss, bus voltage variation, and grid power variance by 29.18%, 26.54%, and 36.80%, respectively.
Original language | English |
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Title of host publication | 2024 Annual Conference of the IEEE Industrial Electronics Society (IECON24) |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
Publication status | Accepted/In press - 24 Jun 2024 |
Event | IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society - Sheraton Grand Chicago Riverwalk, Chicago, United States Duration: 3 Nov 2024 → 6 Nov 2024 Conference number: 50th https://www.iecon-2024.org/ |
Conference
Conference | IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society |
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Abbreviated title | IECON 2024 |
Country/Territory | United States |
City | Chicago |
Period | 3/11/24 → 6/11/24 |
Internet address |
Keywords
- demand response
- energy scheduling
- optimization
- reconfiguration
- virtual power plant