International Joint Polish-Swedish Publication Service

Evolutionary computation based four-area automatic generation control in a restructured environment

Artur Forney , Hartmut PenzigHartmut Penzig

Abstract

The present study aimed to analyze four-area automatic generation control in a restructured environment. There are various types of ancillary services available in power system, one of which is load following with frequency control that comes broadly under automatic generation control in a restructured power system. The main objective of this paper was to introduce some novel evolutionary computation based techniques applied independently to obtain optimal gain parameters for optimal transient performances under various system operating conditions. Computational results and transient performances were compared in order to identify the best optimization technique for resolving this problem. A novel particle swarm based algorithm namely modified chaotic ant swarm optimization (MCASO), and real coded genetic algorithm (RGA) proved to be competitively the best. Conventional PSO and binary coded genetic algorithm were the other next techniques yielding sub-optimal performances. A DISCO can contract individually and multilaterally with a GENCO for power under the supervision of ISO. In this paper, the concept of DISCO participation matrix was used to simulate bilateral contracts in the four-area diagram. The computed values of generators' participation and tie-line power exchanges were in good agreement with the corresponding actual values obtained from MATLAB-SIMULINK. Optimal transient responses were obtained by substituting optimal gains in the MATLAB-SIMULINK based four-area multi-units diagram.

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