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Intelligent Optimization Algorithm Based Load Frequency Controller Design and Its Control Performance Assessment in Interconnected Power Grids |
Zuo Jian1, Xie Pingping1,2, Li Yinhong1, Duan Xianzhong1 |
1.State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China 2.Electric Power Research Institute of China Southern Power Grid Guangzhou 510080 China |
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Abstract Load frequency control (LFC) plays an important role in ensuring safe and reliable operation of the interconnected power grids. Appropriate controller parameter settings can maintain the system frequency stability and a constant tie line power exchange value under various random load disturbances. On the issue of tuning optimization of two-area interconnected power grid LFC controller parameters, this paper presents a controller parameter optimal design scheme based on intelligent optimization algorithm. The scheme adopted integral of time multiplied absolute error (ITAE) as the objective function and grey wolf optimizer (GWO) was employed for searching the optimal LFC controller parameters. GWO algorithm has the advantages of swiftness, efficiency, adaptivity and high accuracy during controller parameters optimization tuning process, because the algorithm imitates the features of leadership hierarchy and pack hunting behaviors of grey wolves. In addition, the possibility of controller performance degradation was also considered in this paper due to the parameter uncertainty of controller itself. And the fragility of the controller was investigated. First, a two-area interconnected power grid LFC control system simulation model was established; then, the proposed optimization algorithm was used to optimize the PI/PID type LFC controller parameters; finally, the simulation results validated that the proposed PI/PID design method has better optimization capability and control effectiveness in comparison to conventional design method and other intelligent optimization algorithms. And the optimized PI/PID controller can ensure robustness and non-fragility under system parameter uncertainty and the controller parameter uncertainty.
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Received: 25 November 2016
Published: 26 February 2018
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