TY - GEN
T1 - Primary frequency regulation performance evaluation of thermal power units based on frequency regulation data segment identification using improved swinging door algorithm
AU - Wang, Zhenyi
AU - Hu, Bin
AU - Lu, Xuegang
AU - Zhang, Ziyu
AU - Ju, Chang
AU - Zhang, Xiaosheng
AU - Ding, Tao
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As a key power system primal frequency regulation (PFR) resource, the PFR performance evaluation of thermal power units has a significant meaning. However, most PFR performance evaluation depends on the unit performance test which leads to a result different from the actual operation performance. In this paper, a PFR performance evaluation based on frequency regulation data segment identification in daily operation is proposed. Firstly, the ramping data segments from daily operating data are selected by the improved swinging door algorithm. Secondly, PFR data segments are identified by three rules. Thirdly, three evaluation indicators including the response time, the adjustment coefficient, and the stable time of the units are calculated and a comprehensive index is formulated to evaluate the PFR performance of thermal power units by the entropy-osculating value method. Finally, the effectiveness of the proposed method is verified by a practical case.
AB - As a key power system primal frequency regulation (PFR) resource, the PFR performance evaluation of thermal power units has a significant meaning. However, most PFR performance evaluation depends on the unit performance test which leads to a result different from the actual operation performance. In this paper, a PFR performance evaluation based on frequency regulation data segment identification in daily operation is proposed. Firstly, the ramping data segments from daily operating data are selected by the improved swinging door algorithm. Secondly, PFR data segments are identified by three rules. Thirdly, three evaluation indicators including the response time, the adjustment coefficient, and the stable time of the units are calculated and a comprehensive index is formulated to evaluate the PFR performance of thermal power units by the entropy-osculating value method. Finally, the effectiveness of the proposed method is verified by a practical case.
KW - data segment identification
KW - entropy-osculating value method
KW - improved swinging door algorithm
KW - performance evaluation
KW - primary frequency regulation
UR - https://www.scopus.com/pages/publications/85143837567
U2 - 10.1109/ACFPE56003.2022.9952309
DO - 10.1109/ACFPE56003.2022.9952309
M3 - 会议稿件
AN - SCOPUS:85143837567
T3 - Proceedings - 2022 Asian Conference on Frontiers of Power and Energy, ACFPE 2022
SP - 57
EP - 62
BT - Proceedings - 2022 Asian Conference on Frontiers of Power and Energy, ACFPE 2022
A2 - Liu, Youbo
A2 - Al-Kayiem, Hussain H.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Asian Conference on Frontiers of Power and Energy, ACFPE 2022
Y2 - 22 October 2022
ER -
