Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets
Purely financial players without any physical assets can participate in day-ahead electricity markets as virtual bidders. They can arbitrage the price difference between day-ahead (DA) and real-time (RT) markets to maximize profits. Virtual bidders encounter various monetary risks and uncertainties...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Open Access Journal of Power and Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9514619/ |
| _version_ | 1831643190515466240 |
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| author | Hossein Mehdipourpicha Siyuan Wang Rui Bo |
| author_facet | Hossein Mehdipourpicha Siyuan Wang Rui Bo |
| author_sort | Hossein Mehdipourpicha |
| collection | DOAJ |
| description | Purely financial players without any physical assets can participate in day-ahead electricity markets as virtual bidders. They can arbitrage the price difference between day-ahead (DA) and real-time (RT) markets to maximize profits. Virtual bidders encounter various monetary risks and uncertainties in their decision-making due to the high volatility of the price difference. Therefore, this paper proposes a max-min two-level optimization model to derive the optimal bidding strategy of virtual bidders. In this model, the risks of uncertainties associated with the rivals’ strategies and RT market prices are managed by robust optimization. The proposed max-min two-level model is turned into a single-level mixed integer linear programming model through duality theory (DT), strong duality theory (SDT), and Karush-Kuhn-Tucker (KKT) conditions. An illustrative case is designed to demonstrate the advantages of the proposed model over the deterministic model. Moreover, case studies on the IEEE 24-bus test system validate the applicability of the proposed model. |
| first_indexed | 2024-12-19T12:55:21Z |
| format | Article |
| id | doaj.art-0376805d52e140c3803bbf0624ff9057 |
| institution | Directory Open Access Journal |
| issn | 2687-7910 |
| language | English |
| last_indexed | 2024-12-19T12:55:21Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Access Journal of Power and Energy |
| spelling | doaj.art-0376805d52e140c3803bbf0624ff90572022-12-21T20:20:23ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102021-01-01832934010.1109/OAJPE.2021.31050979514619Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity MarketsHossein Mehdipourpicha0https://orcid.org/0000-0002-3502-5262Siyuan Wang1https://orcid.org/0000-0003-1443-0709Rui Bo2https://orcid.org/0000-0001-9108-1093Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USADepartment of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USADepartment of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USAPurely financial players without any physical assets can participate in day-ahead electricity markets as virtual bidders. They can arbitrage the price difference between day-ahead (DA) and real-time (RT) markets to maximize profits. Virtual bidders encounter various monetary risks and uncertainties in their decision-making due to the high volatility of the price difference. Therefore, this paper proposes a max-min two-level optimization model to derive the optimal bidding strategy of virtual bidders. In this model, the risks of uncertainties associated with the rivals’ strategies and RT market prices are managed by robust optimization. The proposed max-min two-level model is turned into a single-level mixed integer linear programming model through duality theory (DT), strong duality theory (SDT), and Karush-Kuhn-Tucker (KKT) conditions. An illustrative case is designed to demonstrate the advantages of the proposed model over the deterministic model. Moreover, case studies on the IEEE 24-bus test system validate the applicability of the proposed model.https://ieeexplore.ieee.org/document/9514619/Bidding strategyduality theoryrobust optimizationuncertaintyvirtual bidding |
| spellingShingle | Hossein Mehdipourpicha Siyuan Wang Rui Bo Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets IEEE Open Access Journal of Power and Energy Bidding strategy duality theory robust optimization uncertainty virtual bidding |
| title | Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets |
| title_full | Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets |
| title_fullStr | Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets |
| title_full_unstemmed | Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets |
| title_short | Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets |
| title_sort | developing robust bidding strategy for virtual bidders in day ahead electricity markets |
| topic | Bidding strategy duality theory robust optimization uncertainty virtual bidding |
| url | https://ieeexplore.ieee.org/document/9514619/ |
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