On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation
Integrating battery energy storage systems (BESS) into a coal-fired generator can enhance power systems’ secondary frequency regulation capability. To this end, this paper proposes a policy to coordinate the BESS and the coal-fired generator to meet the automatic generation control (AGC)...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10949211/ |
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| author | Xinsong Zhang Ziyun Ma Beiping Gu Lurui Fang Xiuyong Yu |
| author_facet | Xinsong Zhang Ziyun Ma Beiping Gu Lurui Fang Xiuyong Yu |
| author_sort | Xinsong Zhang |
| collection | DOAJ |
| description | Integrating battery energy storage systems (BESS) into a coal-fired generator can enhance power systems’ secondary frequency regulation capability. To this end, this paper proposes a policy to coordinate the BESS and the coal-fired generator to meet the automatic generation control (AGC) requirements and subsequently investigates the optimal BESS capacity to maximize the net profit gained from the frequency regulation. Firstly, probability characteristics of AGC instruction duration period, interval period, regulation rate, and regulation direction are investigated according to the real AGC datalog. The AGC regulation direction would change randomly. Directly switching the BESS between charging and discharging to match the requirement would significantly deplete the lifetime of the battery. Therefore, this paper divides the BESS into two groups, which will be controlled stay in charging and discharging states to respectively respond to the AGC requirement of “up” and “down”. To obtain a cost-effective BESS investment, this paper develops a new sizing method, which optimizes the BESS capacity by simulating the operation of the hybrid coal-fired generator and BESS power station (HCGBPS) over an example day. Finally, the case studies justified the developed sizing method could make satisfying BESS investment decisions to ensure a maximum net profit in operation. |
| format | Article |
| id | doaj-art-00cee9c2d8374187ab7b3daab3d49e91 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-00cee9c2d8374187ab7b3daab3d49e912025-08-20T03:09:09ZengIEEEIEEE Access2169-35362025-01-0113608336084510.1109/ACCESS.2025.355785310949211On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency RegulationXinsong Zhang0Ziyun Ma1Beiping Gu2Lurui Fang3https://orcid.org/0000-0003-0805-8197Xiuyong Yu4https://orcid.org/0000-0001-6804-8850School of Electrical Engineering and Automation, Nantong University, Nantong, Jiangsu, ChinaSchool of Electrical Engineering and Automation, Nantong University, Nantong, Jiangsu, ChinaSchool of Electrical Engineering and Automation, Nantong University, Nantong, Jiangsu, ChinaSchool of Advanced Technology, Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou, Jiangsu, ChinaSchool of Electrical Engineering and Automation, Nantong University, Nantong, Jiangsu, ChinaIntegrating battery energy storage systems (BESS) into a coal-fired generator can enhance power systems’ secondary frequency regulation capability. To this end, this paper proposes a policy to coordinate the BESS and the coal-fired generator to meet the automatic generation control (AGC) requirements and subsequently investigates the optimal BESS capacity to maximize the net profit gained from the frequency regulation. Firstly, probability characteristics of AGC instruction duration period, interval period, regulation rate, and regulation direction are investigated according to the real AGC datalog. The AGC regulation direction would change randomly. Directly switching the BESS between charging and discharging to match the requirement would significantly deplete the lifetime of the battery. Therefore, this paper divides the BESS into two groups, which will be controlled stay in charging and discharging states to respectively respond to the AGC requirement of “up” and “down”. To obtain a cost-effective BESS investment, this paper develops a new sizing method, which optimizes the BESS capacity by simulating the operation of the hybrid coal-fired generator and BESS power station (HCGBPS) over an example day. Finally, the case studies justified the developed sizing method could make satisfying BESS investment decisions to ensure a maximum net profit in operation.https://ieeexplore.ieee.org/document/10949211/Battery energy storage systemsecondary frequency regulationautomatic generation controlcapacity optimizationsequential Monte Carlo simulation |
| spellingShingle | Xinsong Zhang Ziyun Ma Beiping Gu Lurui Fang Xiuyong Yu On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation IEEE Access Battery energy storage system secondary frequency regulation automatic generation control capacity optimization sequential Monte Carlo simulation |
| title | On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation |
| title_full | On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation |
| title_fullStr | On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation |
| title_full_unstemmed | On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation |
| title_short | On BESS Capacity Optimization of Hybrid Coal-Fired Generator and BESS Power Station for Secondary Frequency Regulation |
| title_sort | on bess capacity optimization of hybrid coal fired generator and bess power station for secondary frequency regulation |
| topic | Battery energy storage system secondary frequency regulation automatic generation control capacity optimization sequential Monte Carlo simulation |
| url | https://ieeexplore.ieee.org/document/10949211/ |
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