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Comparative study of the popular distribution strategies for the wind farm layer AGC |
DOI:10.19783/j.cnki.pspc.181243 |
Key Words:wind farm automatic generation control distribution strategy response time |
Author Name | Affiliation | E-mail | WU Xiaodong | Key Laboratory of Mining Electrical Equipment and Intelligent Control, Taiyuan University of Technology, Taiyuan 030024, China Department of Electric Power Engineering, Shanxi University, Taiyuan 030006, China | | ZHU Yanfang | State Grid Shanxi Electric Power Company, Taiyuan 030001, China | | TIAN Muqin* | Key Laboratory of Mining Electrical Equipment and Intelligent Control, Taiyuan University of Technology, Taiyuan 030024, China | tianmuqin2018@163.com |
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Abstract:The wind farm layer Automatic Generation Control (AGC) is responsible for receiving, distributing and sending the active command target value distributed by the power system dispatching to the wind turbines, and the distribution strategy will directly affect the control performance of the wind farm AGC. At present, the popular distribution strategies include the active power variation average distribution, the active power equal distribution, and the similar margin distribution. In this paper, the effects of three popular distribution strategies on the wind farm AGC response time are compared from the aspects of the wind turbine number, the electricity limit and the available theoretical active calculation error. The results show the influences of the wind turbine number and the electricity limit on the wind farm AGC response time are small, but the available theoretical active calculation error may increase the response time since the active command target value distributed by the power system dispatching is distributed and sent to the wind farm layer AGC, and then operated by the wind turbine layer AGC, is still unable to enter the regulating dead zone, and needs the second distribution. The paper will provide technical basis for improving the control performance of the wind farm AGC. This work is supported by National Natural Science Foundation of China (No. U1510112). |
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