Fuzzy C-Means clustering for robust decentralized load frequency control of interconnected power system with Generation Rate Constraint

Load–frequency control (LFC) is important in electric power system design and operation moreover, to ensure the quality of the power supply. Literature shows that Fuzzy logic controller, one of the most useful approaches, for utilizing expert knowledge, is adaptive in nature and is applied successfully for power system stabilization control. Fuzzy controller’s design depends mainly on the rule base and membership functions over the controller’s input and output ranges. The simple and efficient clustering algorithms permit the classification of the data in distinct groups using distance and/or similarity functions. The present paper proposes the generation of optimal Fuzzy rule base by Fuzzy C-Means clustering technique (FCM) for load frequency control. The phase-plane plot of the inputs of the Fuzzy controller is utilized to obtain the rule-base in the linguistic form. The system parametric uncertainties are obtained by changing parameters by 40% simultaneously from their typical values. The performance of the proposed FCM controller is compared with conventional controller and original Fuzzy controller in the presence of Generation Rate Constraint (GRC) in case of two area and three area inter connected power systems.

► Generation of optimal Fuzzy rule-base by Fuzzy C-Means clustering technique (FCM). ► Phase-plane plot is utilized to obtain the Fuzzy rule-base in the linguistic form. ► FCM controller with Generation Rate Constraint is applied to interconnected systems. ► Performance is compared with conventional and original Fuzzy controller.