Optimal bidding strategy for price takers and customers in a competitive electricity market
Bidding strategies are highly associated with the profit maximization and decreasing the risks for power utilities in a competitive market. For finding the optimal bidding strategies price takers need appropriate bidding structure. Thus, it is required to consider the model as a bi-level optimizatio...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-01-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2017.1358545 |
| _version_ | 1797706559382355968 |
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| author | Somendra P.S. Mathur Anoop Arya Manisha Dubey |
| author_facet | Somendra P.S. Mathur Anoop Arya Manisha Dubey |
| author_sort | Somendra P.S. Mathur |
| collection | DOAJ |
| description | Bidding strategies are highly associated with the profit maximization and decreasing the risks for power utilities in a competitive market. For finding the optimal bidding strategies price takers need appropriate bidding structure. Thus, it is required to consider the model as a bi-level optimization problem. In the lower level price takers submit bid strategically to the ISO and in the upper level maximization of social welfare performed by solving the ISO Market clearing price (MCP). This paper aim to summarize the price taker’s bidding strategy modeling methods for competitive market models on the state-of-the art. A new genetic algorithm approach in a day-ahead electricity market in sealed auction with a pay-as-bid MCP has been employed to solve the problem from two different viewpoints i.e. with symmetrical and unsymmetrical information. The efficiency of the proposed method has been tested on the IEEE-30 bus system. |
| first_indexed | 2024-03-12T05:54:05Z |
| format | Article |
| id | doaj.art-0058ccb2b7b1474cbe3f1eec874dd5fd |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T05:54:05Z |
| publishDate | 2017-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-0058ccb2b7b1474cbe3f1eec874dd5fd2023-09-03T04:50:05ZengTaylor & Francis GroupCogent Engineering2331-19162017-01-014110.1080/23311916.2017.13585451358545Optimal bidding strategy for price takers and customers in a competitive electricity marketSomendra P.S. Mathur0Anoop Arya1Manisha Dubey2Maulana Azad National Institute of TechnologyMaulana Azad National Institute of TechnologyMaulana Azad National Institute of TechnologyBidding strategies are highly associated with the profit maximization and decreasing the risks for power utilities in a competitive market. For finding the optimal bidding strategies price takers need appropriate bidding structure. Thus, it is required to consider the model as a bi-level optimization problem. In the lower level price takers submit bid strategically to the ISO and in the upper level maximization of social welfare performed by solving the ISO Market clearing price (MCP). This paper aim to summarize the price taker’s bidding strategy modeling methods for competitive market models on the state-of-the art. A new genetic algorithm approach in a day-ahead electricity market in sealed auction with a pay-as-bid MCP has been employed to solve the problem from two different viewpoints i.e. with symmetrical and unsymmetrical information. The efficiency of the proposed method has been tested on the IEEE-30 bus system.http://dx.doi.org/10.1080/23311916.2017.1358545bidding strategycompetitive electricity marketrival’s behaviorgenetic algorithm |
| spellingShingle | Somendra P.S. Mathur Anoop Arya Manisha Dubey Optimal bidding strategy for price takers and customers in a competitive electricity market Cogent Engineering bidding strategy competitive electricity market rival’s behavior genetic algorithm |
| title | Optimal bidding strategy for price takers and customers in a competitive electricity market |
| title_full | Optimal bidding strategy for price takers and customers in a competitive electricity market |
| title_fullStr | Optimal bidding strategy for price takers and customers in a competitive electricity market |
| title_full_unstemmed | Optimal bidding strategy for price takers and customers in a competitive electricity market |
| title_short | Optimal bidding strategy for price takers and customers in a competitive electricity market |
| title_sort | optimal bidding strategy for price takers and customers in a competitive electricity market |
| topic | bidding strategy competitive electricity market rival’s behavior genetic algorithm |
| url | http://dx.doi.org/10.1080/23311916.2017.1358545 |
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