Construction of a frequency compliant unit commitment framework using an ensemble learning technique

Hsin Wei Chiu, Le Ren Chang-Chien, Chin Chung Wu

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)


Frequency control is essential to ensure reliability and quality of power systems. North American Electric Reliability Corporation’s (NERC) Control Performance Standard 1 (CPS1) is widely adopted by many operating authorities to examine the quality of the frequency control. The operating authority would have a strong interest in knowing how the frequency-sensitive features affect the CPS1 score and finding out more effective unit-dispatch schedules for reaching the CPS1 goal. As frequency-sensitive features usually possess multi-variable and high-correlated characteristics, this paper employed an ensemble learning technique (the Gradient Boosting Decision Tree algorithm, GBDT) to construct Frequency Response Model (FRM) of the Taipower system in Taiwan to evaluate by CPS1 score. The proposed CPS1 model was then integrated with Unit Commitment (UC) program to determine the unit-dispatch that achieves the targeted CPS1 score. The feasibility and effectiveness of the proposed CPS1-UC platform were validated and compared with the other benchmark model-based UC methods by two operating cases. The proposed model shows promising results: the system frequency could be maintained well, especially in the periods of the early morning or the high renewable penetration.

出版狀態Published - 2021 一月 2

All Science Journal Classification (ASJC) codes

  • 可再生能源、永續發展與環境
  • 燃料技術
  • 能源工程與電力技術
  • 能源(雜項)
  • 控制和優化
  • 電氣與電子工程


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