Abstract
this paper, a fuzzy C-means controller proposed to the generation of optimal fuzzy rule base by Fuzzy C - Means clustering technique (FCM) for load frequency control in deregulated environment. The phase-plane plot of the inputs of the fuzzy controller is utilized to obtain the rule-base in the linguistic form. The proposed method is tested on a two-area power system with different contracted scenarios under various operating conditions. The results of the proposed controller are compared with the fuzzy PID controller and conventional PID controller to illustrate its robust performance. These comparisons demonstrate the superiority and robustness of the proposed controller. and/or similarity functions. These groups can later be used directly in selecting appropriate fuzzy set boundaries. Also the algorithms can automatically combine similar objects (data entries) in order to reduce the global size of the data. Finally the clustering algorithms let us easily detect potential outliers (clusters containing one or very few data entries). This feature is taken into consideration to design a decentralized fuzzy controller. The phase plane plot of the input space is formed into clusters with the cluster centers is formed to obtain the required rule-base of the proposed fuzzy controller(22).The proposed control has simple structure and does not require an accurate model of the plant. Thus, its construction and implementation are fairly easy and can be useful for the real world complex power system. The proposed method is applied to a two-area restructured power system as a test system. The results of the proposed Fuzzy-C-means controller are compared with the Fuzzy PID (FPID) controller (18) and conventional PID controller (9) through some performance indices in the presence of large parametric uncertainties and system nonlinearities under various area load changes
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