Multiobjective Optimal Power Flow Using Hybrid Evolutionary Algorithm
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Multiobjective Optimal Power Flow Using Hybrid Evolutionary Algorithm

Authors: Alawode Kehinde O., Jubril Abimbola M. Komolafe Olusola A.

Abstract:

This paper solves the environmental/ economic dispatch power system problem using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator Operator (CAO), called the NSGA-II/CAO. These multiobjective evolutionary algorithms were applied to the standard IEEE 30-bus six-generator test system. Several optimization runs were carried out on different cases of problem complexity. Different quality measure which compare the performance of the two solution techniques were considered. The results demonstrated that the inclusion of the CAO in the original NSGA-II improves its convergence while preserving the diversity properties of the solution set.

Keywords: optimal power flow, multiobjective power dispatch, evolutionary algorithm

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1056284

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