A data-driven modeling method for secondary frequency regulation characteristic of thermal power units
The existing mechanism models for thermal power units face challenges in accurately reflecting unit response characteristics and obtaining precise model parameters. This paper proposes a data-driven modeling method for secondary frequency regulation characteristic of thermal power units. First， the...
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| Format: | Article |
| Language: | zho |
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zhejiang electric power
2025-01-01
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| Series: | Zhejiang dianli |
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| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=0a6c340d-8eb8-4a4f-a404-0849f11c8cf8 |
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| _version_ | 1823857091872292864 |
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| author | LI Zhijun SHA Qianli YAN Xinrong YAN Gangui ZHU Lin FANG Zheng LI Junhui |
| author_facet | LI Zhijun SHA Qianli YAN Xinrong YAN Gangui ZHU Lin FANG Zheng LI Junhui |
| author_sort | LI Zhijun |
| collection | DOAJ |
| description | The existing mechanism models for thermal power units face challenges in accurately reflecting unit response characteristics and obtaining precise model parameters. This paper proposes a data-driven modeling method for secondary frequency regulation characteristic of thermal power units. First， the frequency regulation response characteristics of automatic generation control （AGC） are analyzed， and operational conditions are categorized based on regulation intensity. Using multiple sets of secondary frequency response curves under similar regulation intensities， the least squares method is applied to extract the response features of secondary frequency regulation. Next， a second-order model represents the mathematical model of the units， with online adjustments to the model's damping coefficients to enhance adaptability to changes in regulation intensity. Adaptive parameters for the three response stages during the unit's response process are determined using particle swarm optimization （PSO）. Finally， case studies are designed to validate the effectiveness and superiority of the proposed model. |
| format | Article |
| id | doaj-art-cd625238db3547b28a03afe58908871b |
| institution | Kabale University |
| issn | 1007-1881 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | zhejiang electric power |
| record_format | Article |
| series | Zhejiang dianli |
| spelling | doaj-art-cd625238db3547b28a03afe58908871b2025-02-12T00:54:58Zzhozhejiang electric powerZhejiang dianli1007-18812025-01-01441152310.19585/j.zjdl.2025010021007-1881（2025）01-0015-09A data-driven modeling method for secondary frequency regulation characteristic of thermal power unitsLI Zhijun0SHA Qianli1YAN Xinrong2YAN Gangui3ZHU Lin4FANG Zheng5LI Junhui6Huadian Electric Power Research Institute Co.， Ltd.， Hangzhou 310030， ChinaKey Laboratory of Modern Power System Simulation and Control & New Energy Technology， Ministry of Education （Northeast Electric Power University）， Jilin， Jilin 132012， ChinaHuadian Electric Power Research Institute Co.， Ltd.， Hangzhou 310030， ChinaKey Laboratory of Modern Power System Simulation and Control & New Energy Technology， Ministry of Education （Northeast Electric Power University）， Jilin， Jilin 132012， ChinaHuadian Electric Power Research Institute Co.， Ltd.， Hangzhou 310030， ChinaHuadian Electric Power Research Institute Co.， Ltd.， Hangzhou 310030， ChinaKey Laboratory of Modern Power System Simulation and Control & New Energy Technology， Ministry of Education （Northeast Electric Power University）， Jilin， Jilin 132012， ChinaThe existing mechanism models for thermal power units face challenges in accurately reflecting unit response characteristics and obtaining precise model parameters. This paper proposes a data-driven modeling method for secondary frequency regulation characteristic of thermal power units. First， the frequency regulation response characteristics of automatic generation control （AGC） are analyzed， and operational conditions are categorized based on regulation intensity. Using multiple sets of secondary frequency response curves under similar regulation intensities， the least squares method is applied to extract the response features of secondary frequency regulation. Next， a second-order model represents the mathematical model of the units， with online adjustments to the model's damping coefficients to enhance adaptability to changes in regulation intensity. Adaptive parameters for the three response stages during the unit's response process are determined using particle swarm optimization （PSO）. Finally， case studies are designed to validate the effectiveness and superiority of the proposed model.https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=0a6c340d-8eb8-4a4f-a404-0849f11c8cf8thermal power unitdata-drivenresponse characteristicleast square methodadjustment depthadaptive parameters |
| spellingShingle | LI Zhijun SHA Qianli YAN Xinrong YAN Gangui ZHU Lin FANG Zheng LI Junhui A data-driven modeling method for secondary frequency regulation characteristic of thermal power units Zhejiang dianli thermal power unit data-driven response characteristic least square method adjustment depth adaptive parameters |
| title | A data-driven modeling method for secondary frequency regulation characteristic of thermal power units |
| title_full | A data-driven modeling method for secondary frequency regulation characteristic of thermal power units |
| title_fullStr | A data-driven modeling method for secondary frequency regulation characteristic of thermal power units |
| title_full_unstemmed | A data-driven modeling method for secondary frequency regulation characteristic of thermal power units |
| title_short | A data-driven modeling method for secondary frequency regulation characteristic of thermal power units |
| title_sort | data driven modeling method for secondary frequency regulation characteristic of thermal power units |
| topic | thermal power unit data-driven response characteristic least square method adjustment depth adaptive parameters |
| url | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=0a6c340d-8eb8-4a4f-a404-0849f11c8cf8 |
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