Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests

Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests

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This paper proposes a new metahaeuristic algorithm named particle swarm optimization and chaotic gravitational search algorithm (PSO-CGSA) for solving the combined economic and emission dispatch (CEED) problem.First, we determine the efficiency and effectiveness measures of the algorithm and compare it with other well-known algorithms.Then, we analyze the obtained solutions using the statistical procedure proposed in the paper.

The proposed procedure contains the following: (i) the behavior analysis of the algorithms when solving the CEED problem, using non-parametric tests, and (ii) the ranking of the algorithms using the PROMETHEE/GAIA multi-criteria decision-making method.The behavior analysis is iphone 13 price ohio performed for two cases: iphone 13 price dallas (i) when solving individual variants of the CEED problem (single-problem analysis) and (ii) when solving a set of CEED variants (multiple-problem analysis).The results of the applied procedure for the test system with six generators show that PSO-CGSA has (i) the best solution for each tested variant of the CEED problem; (ii) the best standard deviation, mean value, error rate, and behavior for the CEED variant with a bi-objective function that simultaneously minimizes fuel cost and emission, taking into account the valve point effect; and (iii) the best rank when solving a set of CEED variants.