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Research Articles

Solving Economic Emission Load Dispatch Using Oppositional Slime Mould Algorithm With Wavelet Mutation

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Pages 662-682 | Received 09 Sep 2021, Accepted 18 Aug 2022, Published online: 14 Nov 2022
 

Abstract

This paper introduces a modified slime mould algorithm to enhance the exploitation and exploration of the algorithm. As stated in no free lunch theorem no single algorithm can proficiently solve the optimization problems at hand. Hence, hybridization of more than one heuristic algorithm is employed to tackle the situation. The proposed strategy employs opposition-based learning and wavelet mutation-based strategy to the basic slime mould algorithm for exploring the search space while avoiding local optima. These methods are tested on standard benchmark functions, CEC-14 functions and different single and multiobjective thermal load dispatch problems including small, medium and large-scale problems while satisfying non-differentiable constraints namely valve point loading, prohibited operating zone and ramp rate limit which make objective function non-convex and discontinuous. The pareto dominance technique is employed to achieve the optimal solution in multiobjective problems. This paper also compares the performance of the proposed technique with other methods available in the literature for different economic load dispatch problems and emission dispatch problems. The Wilcoxon signed-rank test performed to confirm the competitiveness of the proposed method for independent samples.

Additional information

Notes on contributors

Kanchan Pawani

Kanchan Pawani is a PhD student at the Electrical and Instrumentation Department of Sant Longowal Institute of Engineering and Technology, specialising in power system optimization.

Manmohan Singh

Manmohan Singh is an Associate Professor at the Electrical and Instrumentation Department of Sant Longowal Institute of Engineering and Technology. His research covers a number of different fields of power system generation, analysis, signal processing and optimization techniques applications mostly focused on dispatch problems of electrical energy.

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