Li, Yong, Deng, Youyue, Wang, Yahui, Jiang, Lin
ORCID: 0000-0001-6531-2791 and Shahidehpour, Mohammad
(2023)
Robust bidding strategy for multi-energy virtual power plant in peak-regulation ancillary service market considering uncertainties
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 151.
109101-.
ISSN 0142-0615, 1879-3517
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MEVPP-Manuscript-IJEPE Author accepted version 2rd revision.pdf - Author Accepted Manuscript Download (1MB) | Preview |
Abstract
Multi-energy virtual power plant (MEVPP) can aggregate flexible resources such as energy storage and flexible loads that decentralized in the region to meet the access conditions in the peak-regulation ancillary service market. However, the uncertainties in energy sources and loads bring adverse impact on the operation of MEVPP. Therefore, this paper proposes a day-ahead robust bidding strategy for MEVPP to participate in the peak-regulation market. Firstly, this paper analyzes the impact of uncertainties for MEVPP on the peak-regulation market. On this basis, the operation mechanism for MEVPP in the peak-regulation market is proposed by considering the integrated demand response (IDR). Additionally, the day-ahead two-stage robust bidding model is established to minimize the operation cost of MEVPP. Finally, the case studies show that the day-ahead robust bidding strategy can effectively reduce the peak-regulation deviation penalty compared with traditional deterministic optimization. Specifically, with the proposed robust bidding strategy, the total revenue in the actual operation stage is increased by 5.16% and 8.45% on sunny day and raised by 8.28% and 15.35% on cloudy day when the predicted deviations are respectively 20% and 30%, comparing with traditional deterministic optimization.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Multi -energy virtual power plant, Peak -regulation market, Robust bidding strategy, Uncertainty |
| Divisions: | Faculty of Science & Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 19 May 2023 07:25 |
| Last Modified: | 22 May 2026 19:32 |
| DOI: | 10.1016/j.ijepes.2023.109101 |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3170480 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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