Wang, H, Jia, Y, Lai, CS et al. (1 more author) (2022) Optimal Virtual Power Plant Operational Regime Under Reserve Uncertainty. IEEE Transactions on Smart Grid, 13 (4). pp. 2973-2985. ISSN 1949-3053
Abstract
Virtual power plant (VPP) has become an important resource for reserve provision owing to its fast-responding capability. In this paper, an optimal VPP operational regime considering reserve uncertainty is proposed, which includes a novel day-ahead offering strategy and a real-time dispatching model. At the day-ahead stage, the offering strategy gives the VPP’s price-dependent offers in the energy market under multiple uncertainties on market price, renewable generation, and calls of reserve deployment. A hybrid stochastic minimax regret (MMR) model is proposed to facilitate making offering decisions in the electricity market. At the real-time dispatching stage, generation scheduling can be realized based on the MMR criterion in an online fashion. To alleviate the intrinsic conservativeness of the dispatching model, a self-adaptive algorithm is also proposed to instantly modify the confidence bounds. The proposed regime is comprehensively tested through extensive case studies, which demonstrate the effectiveness of our method in obtaining operational decisions that are less conservative.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Uncertainty , price-dependent offering strategy , stochastic minimax regret , secondary reserve , self-adaptive |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Apr 2022 09:20 |
Last Modified: | 17 May 2023 01:22 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/tsg.2022.3153635 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185433 |