Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
The output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However,...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9624983/ |
| _version_ | 1818693734011764736 |
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| author | Peiyue Li Zhijie Wang Jiahui Jin |
| author_facet | Peiyue Li Zhijie Wang Jiahui Jin |
| author_sort | Peiyue Li |
| collection | DOAJ |
| description | The output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However, an open question is how the wind-energy storage alliance’s participation affects market clearing and the profits of market participants. Therefore, a stochastic bi-level optimization model is proposed to describe the bidding behavior of wind-energy storage alliances in energy and frequency regulation markets. At the same time, a new quantitative index of bidding behavior is defined—regulation participation ratio. Considering the uncertainty of wind turbine output, the profits of wind-energy storage alliance are maximized in the upper level. The lower level minimizes the power purchase cost of distribution system operator (DSO) for the joint market clearing. The bi-level model is transformed into a mixed integer linear programming (MILP) model by Karush-Kuhn-Tucker (KKT) conditions, strong duality theory and large M method. Regulation participation ratio is set to different values in the case analysis, so as to analyze the influence of the alliance’s bidding behavior on market. Moreover, the economic impact of alliance on wind turbine and energy storage is compared. |
| first_indexed | 2024-12-17T13:18:23Z |
| format | Article |
| id | doaj.art-d10f20a929ec452f892e41b2eb74914d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T13:18:23Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d10f20a929ec452f892e41b2eb74914d2022-12-21T21:46:57ZengIEEEIEEE Access2169-35362021-01-01915653715654710.1109/ACCESS.2021.31301859624983Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under UncertaintyPeiyue Li0https://orcid.org/0000-0001-7241-3929Zhijie Wang1Jiahui Jin2https://orcid.org/0000-0001-8337-1170School of Electrical Engineering, Shanghai Dianji University, Shanghai, ChinaSchool of Electrical Engineering, Shanghai Dianji University, Shanghai, ChinaSchool of Electrical Engineering, Shanghai Dianji University, Shanghai, ChinaThe output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However, an open question is how the wind-energy storage alliance’s participation affects market clearing and the profits of market participants. Therefore, a stochastic bi-level optimization model is proposed to describe the bidding behavior of wind-energy storage alliances in energy and frequency regulation markets. At the same time, a new quantitative index of bidding behavior is defined—regulation participation ratio. Considering the uncertainty of wind turbine output, the profits of wind-energy storage alliance are maximized in the upper level. The lower level minimizes the power purchase cost of distribution system operator (DSO) for the joint market clearing. The bi-level model is transformed into a mixed integer linear programming (MILP) model by Karush-Kuhn-Tucker (KKT) conditions, strong duality theory and large M method. Regulation participation ratio is set to different values in the case analysis, so as to analyze the influence of the alliance’s bidding behavior on market. Moreover, the economic impact of alliance on wind turbine and energy storage is compared.https://ieeexplore.ieee.org/document/9624983/Wind-energy storage allianceregulation participation ratiobi-level optimization problemstrategic bidding |
| spellingShingle | Peiyue Li Zhijie Wang Jiahui Jin Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty IEEE Access Wind-energy storage alliance regulation participation ratio bi-level optimization problem strategic bidding |
| title | Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty |
| title_full | Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty |
| title_fullStr | Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty |
| title_full_unstemmed | Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty |
| title_short | Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty |
| title_sort | market impact of wind energy storage alliance strategic bidding under uncertainty |
| topic | Wind-energy storage alliance regulation participation ratio bi-level optimization problem strategic bidding |
| url | https://ieeexplore.ieee.org/document/9624983/ |
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