Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors
Considering the economy, reliability, and output characteristics of multiple power sources (MPS) and energy storage (ES) comprehensively, a multi-source system integrated with offshore wind farms (OWFs) and its construction cost, and operating and maintenance cost model are established. The system i...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.884886/full |
| _version_ | 1818277959762444288 |
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| author | Qingzhi Jian Xiaoming Liu Xinye Du Yuyue Zhang Nan Wang Yonghui Sun |
| author_facet | Qingzhi Jian Xiaoming Liu Xinye Du Yuyue Zhang Nan Wang Yonghui Sun |
| author_sort | Qingzhi Jian |
| collection | DOAJ |
| description | Considering the economy, reliability, and output characteristics of multiple power sources (MPS) and energy storage (ES) comprehensively, a multi-source system integrated with offshore wind farms (OWFs) and its construction cost, and operating and maintenance cost model are established. The system is mainly composed of OWFs, thermal power plants, gas turbine power plants, and pumped hydro storage plants. Given the economy of the power system and offshore wind power accommodation, a bi-level optimal capacity configuration and operation scheduling method is proposed for the multi-source system integrated with OWF clusters with the objective function of optimal total cost. Then, a robust bi-level planning method for the multi-source system integrated with OWFs considering the dual uncertainty of load and offshore wind power prediction is proposed, in which the upper and lower models are solved by an improved particle swarm optimization (PSO) algorithm and CPLEX solver, respectively. Based on the method, the cost-optimal capacity configuration and operation scheduling scheme of an MPS and ES can be obtained. Finally, an OWF group in Shandong Province is taken as an example to check the validity and feasibility of the proposed method. |
| first_indexed | 2024-12-12T23:09:50Z |
| format | Article |
| id | doaj.art-269a785abdb146288cc3ff0d55b35205 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-12-12T23:09:50Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-269a785abdb146288cc3ff0d55b352052022-12-22T00:08:37ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2022-04-011010.3389/fenrg.2022.884886884886Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction ErrorsQingzhi Jian0Xiaoming Liu1Xinye Du2Yuyue Zhang3Nan Wang4Yonghui Sun5Economic and Technological Research Institute, State Grid Shandong Electric Power Co., LTD., Jinan, ChinaEconomic and Technological Research Institute, State Grid Shandong Electric Power Co., LTD., Jinan, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing, ChinaEconomic and Technological Research Institute, State Grid Shandong Electric Power Co., LTD., Jinan, ChinaEconomic and Technological Research Institute, State Grid Shandong Electric Power Co., LTD., Jinan, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing, ChinaConsidering the economy, reliability, and output characteristics of multiple power sources (MPS) and energy storage (ES) comprehensively, a multi-source system integrated with offshore wind farms (OWFs) and its construction cost, and operating and maintenance cost model are established. The system is mainly composed of OWFs, thermal power plants, gas turbine power plants, and pumped hydro storage plants. Given the economy of the power system and offshore wind power accommodation, a bi-level optimal capacity configuration and operation scheduling method is proposed for the multi-source system integrated with OWF clusters with the objective function of optimal total cost. Then, a robust bi-level planning method for the multi-source system integrated with OWFs considering the dual uncertainty of load and offshore wind power prediction is proposed, in which the upper and lower models are solved by an improved particle swarm optimization (PSO) algorithm and CPLEX solver, respectively. Based on the method, the cost-optimal capacity configuration and operation scheduling scheme of an MPS and ES can be obtained. Finally, an OWF group in Shandong Province is taken as an example to check the validity and feasibility of the proposed method.https://www.frontiersin.org/articles/10.3389/fenrg.2022.884886/fulloffshore wind power integrationgeneration expansion planningbi-level optimizationuncertaintyeconomic optimizationimproved PSO |
| spellingShingle | Qingzhi Jian Xiaoming Liu Xinye Du Yuyue Zhang Nan Wang Yonghui Sun Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors Frontiers in Energy Research offshore wind power integration generation expansion planning bi-level optimization uncertainty economic optimization improved PSO |
| title | Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors |
| title_full | Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors |
| title_fullStr | Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors |
| title_full_unstemmed | Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors |
| title_short | Robust Bi-Level Planning Method for Multi-Source Systems Integrated With Offshore Wind Farms Considering Prediction Errors |
| title_sort | robust bi level planning method for multi source systems integrated with offshore wind farms considering prediction errors |
| topic | offshore wind power integration generation expansion planning bi-level optimization uncertainty economic optimization improved PSO |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2022.884886/full |
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