Abstract
Frequency is an important index for the stable and secure operation of the power system. In the conventional methods, an inappropriate value of the frequency bias coefficient will lead to over-biasing or under-biasing of generators, causing unintended cross-regional interaction. This paper proposes a fully non-interactive automatic generation control strategy for power systems. Through the derivation of deviation of frequency and tie-line active power under disturbance, it’s found that the disturbance can be located from the deviation of frequency and active power of tie-line. Based on this, the conventional AGC control model is modified. With the proposed method, only the AGC units in disturbed areas respond to disturbances, and the AGC units in other areas will not act. Thus, the unintended cross-regional interaction in the conventional AGC control method is avoided. The proposed method only needs minor modification to the conventional AGC control model and hence is easy to implement for onsite application. The effectiveness of the proposed strategy is confirmed via simulation on the Kundur four-machine two-area system.
Additional information
Notes on contributors
Jianhua Chen
Jianhua Chen received the B.S. degree in electrical engineering and automation from Xi'an Jiaotong University of Xi'an, Xi'an, China, in 2008 and the Ph.D. degree in electrical engineering from Tsinghua University of Beijing, Beijing, China, in 2013. Currently, he is a senior Electrical Engineer at State Grid Jibei Electric Power Company, Beijing, China. His research interests include large-scale wind power dispatch and control theory, system security, and robust optimization.
Dong Ding
Dong Ding received the M.S. degree in electrical engineering and automation from China Agricultural University of Beijing, Beijing, China, in 2005. Currently, he is a senior Electrical Engineer at State Grid Beijing Electric Power Company, Beijing, China. His research interests include power loss management and optimization of transmission and distribution.
Xiang Yuan
Xiang Yuan received the B.S. degree in computer science and technology from Wuhan University of Hydraulic and Electric Engineering of Wuhan, Hubei, China, in 2005 and the M.S. degree in computer science and technology from Tsinghua University of Beijing, Beijing, China, in 2012. Currently, he is a senior Electrical Engineer at State Grid Jibei Electric Power Company, Beijing, China. His research interests include reactive power optimization and line loss technical reduction.
Kai Liu
Kai Liu received the B.S. degree in electrical engineering and automation from Hebei University of Science and Technology of Shijiazhuang, Hebei, China, in 2007. Currently, he is an Electrical Engineer at State Grid Jibei Electric Power Company Qinhuangdao Power Supply Company, Qinhuangdao, China. His research interests include reactive power optimization and line loss technical reduction.
Yao Zhang
Yao Zhang received the B.S. degree in marketing management from Harbin Institute of Technology of Harbin, Heilongjiang, China, in 2007 and the M.S. degree in enterprise management from Xi'an Jiaotong University of Xi'an, Xi'an, China, in 2011. Currently, she is a Senior Engineer at China nuclear power engineering Company, Beijing, China. Her research interests include large-scale wind power dispatch and control theory, system security, and robust optimization.