Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers
The competition among renewable power producers (RPPs) may cause the cleared power of RPPs to be less than the bidding power, while the impact of competition is neglected in the existing price-taker methods. To overcome the above deficiency, this paper develops an optimal bidding strategy, consideri...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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China electric power research institute
2024-01-01
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| Series: | CSEE Journal of Power and Energy Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9606941/ |
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| _version_ | 1841533436123152384 |
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| author | Jifeng Cheng Zheng Yan Xiaoyuan Xu Han Wang Yan Zhang Shuying Zhang |
| author_facet | Jifeng Cheng Zheng Yan Xiaoyuan Xu Han Wang Yan Zhang Shuying Zhang |
| author_sort | Jifeng Cheng |
| collection | DOAJ |
| description | The competition among renewable power producers (RPPs) may cause the cleared power of RPPs to be less than the bidding power, while the impact of competition is neglected in the existing price-taker methods. To overcome the above deficiency, this paper develops an optimal bidding strategy, considering the competition among RPPs. First, a bivariate stochastic optimization (BSO) model for a bidding strategy is proposed by considering the variable power output of RPPs and the competition among RPPs. Particularly, the cleared power estimated by the demand-supply ratio is a random variable in the proposed BSO model. Then, the Newton method and particle swarm optimization (PSO) are combined to solve the BSO model in which various probability distribution functions (PDFs) of renewable energy generation are considered. Finally, the effectiveness of the proposed method is verified based on the results of a case study, which shows that the proposed model performed better than the traditional chance-constrained programming (CCP) model in power market competition. |
| format | Article |
| id | doaj-art-bf683e0c4a9c48e98be7da308a6b4d62 |
| institution | Kabale University |
| issn | 2096-0042 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | China electric power research institute |
| record_format | Article |
| series | CSEE Journal of Power and Energy Systems |
| spelling | doaj-art-bf683e0c4a9c48e98be7da308a6b4d622025-01-16T00:02:19ZengChina electric power research instituteCSEE Journal of Power and Energy Systems2096-00422024-01-011062539255010.17775/CSEEJPES.2020.029509606941Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power ProducersJifeng Cheng0Zheng Yan1Xiaoyuan Xu2Han Wang3Yan Zhang4Shuying Zhang5Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240The competition among renewable power producers (RPPs) may cause the cleared power of RPPs to be less than the bidding power, while the impact of competition is neglected in the existing price-taker methods. To overcome the above deficiency, this paper develops an optimal bidding strategy, considering the competition among RPPs. First, a bivariate stochastic optimization (BSO) model for a bidding strategy is proposed by considering the variable power output of RPPs and the competition among RPPs. Particularly, the cleared power estimated by the demand-supply ratio is a random variable in the proposed BSO model. Then, the Newton method and particle swarm optimization (PSO) are combined to solve the BSO model in which various probability distribution functions (PDFs) of renewable energy generation are considered. Finally, the effectiveness of the proposed method is verified based on the results of a case study, which shows that the proposed model performed better than the traditional chance-constrained programming (CCP) model in power market competition.https://ieeexplore.ieee.org/document/9606941/Bidding strategypower marketpower producerrenewable energy generationstochastic optimization |
| spellingShingle | Jifeng Cheng Zheng Yan Xiaoyuan Xu Han Wang Yan Zhang Shuying Zhang Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers CSEE Journal of Power and Energy Systems Bidding strategy power market power producer renewable energy generation stochastic optimization |
| title | Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers |
| title_full | Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers |
| title_fullStr | Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers |
| title_full_unstemmed | Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers |
| title_short | Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers |
| title_sort | bivariate stochastic optimization model for bidding strategies considering competition among renewable power producers |
| topic | Bidding strategy power market power producer renewable energy generation stochastic optimization |
| url | https://ieeexplore.ieee.org/document/9606941/ |
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