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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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2025-01-01
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| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=0a6c340d-8eb8-4a4f-a404-0849f11c8cf8 |
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| Summary: | 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. |
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| ISSN: | 1007-1881 |