Self-adaptive differential evolution algorithm for economic dispatch with transmission losses consideration

In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical programming environment of MATLAB in this work. The efficiency of the proposed methodology is initially demonstrated via the analysis of IEEE 30-bus test case. A detailed comparative study among Lambda iteration, conventional genetic algorithm (CGA), tabu search/simulated annealing (TS/SA), ant colony search algorithm (ACSA) and the proposed method is presented. From the experimental results, the proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computational time.

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