Application of the Slime Mould Algorithm on the Bi-Objective Environmental Economic Dispatch Problem

Authors

  • Tawba Dridi Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia
  • Houda Jouini Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia
  • Abdelkader Mami Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia
  • Abderrahman El Mhamedi IUT of Montreuil, University of Paris 8, France
  • El Mouloudi Dafaoui IUT of Montreuil, University of Paris 8, France
Volume: 13 | Issue: 6 | Pages: 12190-12197 | December 2023 | https://doi.org/10.48084/etasr.6358

Received: 2 September 2023 | Revised: 29 September 2023 | Accepted: 5 October 2023 | Online: 5 December 2023


Corresponding author: Tawba Dridi

Abstract

This paper investigates the performance of one of the latest metaheuristic swarm-based approaches called Slime Mould Algorithm (SMA). SMA is used here to solve the static bi-objective constrained Economic Emission Dispatch (EED) problem in the presence of renewable energy sources while considering the Valve-Point Effects (VPE). The SMA approach is applied to indicate the adequate optimal solutions for operating the committed thermal units under different operational constraints. The sought optimal solutions are the midpoint between cost saving and pollutant gas emission reduction. This study also examines the influence of integrating renewable energy sources (wind and solar) into the conventional power production network. SMA technique is applied on 3- and 6-unit IEEE test systems in several case studies. The simulation numerical results indicate that SMA has a high efficiency and a better performance compared to known state-of-the-art algorithms. The proposed approach was programmed and simulated in MATLAB.

Keywords:

economic emission dispatch, renewable energy sources, slime mould algorithm, valve-point effects

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How to Cite

[1]
T. Dridi, H. Jouini, A. Mami, A. El Mhamedi, and E. M. Dafaoui, “Application of the Slime Mould Algorithm on the Bi-Objective Environmental Economic Dispatch Problem”, Eng. Technol. Appl. Sci. Res., vol. 13, no. 6, pp. 12190–12197, Dec. 2023.

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