Emission Constrained Economic Dispatch Using Logistic Map Adaptive Differential Evolution
A novel adaptive differential evolution based algorithm for solving emission constrained economic dispatch (ECED) problem is presented in this paper. The key factor for successful operation DE is the proper selection of user defined parameters. Choosing suitable values of parameters are difficult for DE, which is usually a problem-dependent task. Unfortunately, there is no fix rule for selection of parameters. The trial-and-error method adopted generally for tuning the parameters in DE requires multiple optimization runs. Even this method can not guarantee optimal results every time and sometimes it may lead to premature convergence. The proposed method combines differential evolution with chaos theory for self adaptation of DE parameters. The performance of the proposed method is demonstrated on a sample test system. The results of the proposed method are compared with other methods. It is found that the results obtained by the proposed method are superior in terms of fuel cost, emission output and losses.
KeywordsDifferential Evolution Fuel Cost Chaos Theory Chaotic Sequence Trial Vector
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