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

Downloads

Download data is not yet available.

References

X. Bai and H. Wei, "Semi-definite programming-based method for security-constrained unit commitment with operational and optimal power flow constraints," IET Generation, Transmission & Distribution, vol. 3, no. 2, pp. 182–197, Feb. 2009.

S. Elsaiah, M. Benidris, J. Mitra, and N. Cai, "Optimal economic power dispatch in the presence of intermittent renewable energy sources," in 2014 IEEE PES General Meeting | Conference & Exposition, National Harbor, MD, USA, Jul. 2014.

S. Deb, D. S. Abdelminaam, M. Said, and E. H. Houssein, "Recent Methodology-Based Gradient-Based Optimizer for Economic Load Dispatch Problem," IEEE Access, vol. 9, pp. 44322–44338, 2021.

J. K. Pattanaik, M. Basu, and D. P. Dash, "Improved real coded genetic algorithm for dynamic economic dispatch," Journal of Electrical Systems and Information Technology, vol. 5, no. 3, pp. 349–362, Dec. 2018.

Τ. M. Kumar and Ν. A. Singh, "Environmental Economic Dispatch with the use of Particle Swarm Optimization Technique based on Space Reduction Strategy," Engineering, Technology & Applied Science Research, vol. 9, no. 5, pp. 4605–4611, Oct. 2019.

N. Cherkaoui, A. Belfqih, F. E. Mariami, J. Boukherouaa, and A. Berdai, "Active power ouptut optimization for wind farms and thermal units by minimizing the operating cost and emissions," International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 4, pp. 3412–3422, Aug. 2020.

M. Khalil, R. S. Wibowo, and O. Penangsang, "Combined economic emission dispatch with cubic criterion function using cuckoo search algorithm," in 2018 International Conference on Information and Communications Technology (ICOIACT), Yogyakarta, Indonesia, Mar. 2018, pp. 36–40.

B. M. Alshammari, "Teaching-Learning-Based Optimization Algorithm for the Combined Dynamic Economic Environmental Dispatch Problem," Engineering, Technology & Applied Science Research, vol. 10, no. 6, pp. 6432–6437, Dec. 2020.

X. Xia and A. M. Elaiw, "Optimal dynamic economic dispatch of generation: A review," Electric Power Systems Research, vol. 80, no. 8, pp. 975–986, Aug. 2010.

S. Li, H. Chen, M. Wang, A. A. Heidari, and S. Mirjalili, "Slime mould algorithm: A new method for stochastic optimization," Future Generation Computer Systems, vol. 111, pp. 300–323, Oct. 2020.

G. A. Alshammari, F. A. Alshammari, T. Guesmi, B. M. Alshammari, A. S. Alshammari, and N. A. Alshammari, "A New Particle Swarm Optimization Based Strategy for the Economic Emission Dispatch Problem Including Wind Energy Sources," Engineering, Technology & Applied Science Research, vol. 11, no. 5, pp. 7585–7590, Oct. 2021.

C. R. Edwin Selva Rex, M. Marsaline Beno, and J. Annrose, "A Solution for Combined Economic and Emission Dispatch Problem using Hybrid Optimization Techniques," Journal of Electrical Engineering & Technology, Sep. 2019.

N. Kherfane, R. L. Kherfane, M. Younes, and F. Khodja, "Economic and Emission Dispatch with Renewable Energy Using HSA," Energy Procedia, vol. 50, pp. 970–979, Jan. 2014.

"IEEE 3-Units ELD Test System," Alroomi, Apr. 20, 2016. https://www.al-roomi.org/economic-dispatch/3-units-system.

M. M. El-Saadawi, K. M. Abo-Al-Ez, and A. Fathy, "Comparative Study for Combined Economic and Emission Dispatch Problem Considering Valve Point Effect," Journal of Electrical Engineering, vol. 16, no. 1, pp. 13–13, 2016.

H. C. S. Rughooputh and R. T. F. Ah King, "Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm," in IEEE International Conference on Industrial Technology, 2003, Maribor, Slovenia, Sep. 2003, vol. 1, pp. 48–53.

N. T. P. Thao and N. T. Thang, "Environmental Economic Load Dispatch with Quadratic Fuel Cost Function Using Cuckoo Search Algorithm," International Journal of u- and e-Service, Science and Technology, vol. 7, no. 2, pp. 199–210, Apr. 2014.

A. N. Afandi and H. Miyauchi, "A New Evolutionary Method for Solving Combined Economic and Emission Dispatch," Energy and Power Engineering, vol. 5, no. 4, pp. 774–779, 2013.

T. Dridi, H. Jouini, A. Mami, A. E. Mhamedi, and E. M. Dafaoui, "Application of the Levenberg-Marquardt Algorithm in Solving the Economic Emission Dispatch Problem Integrating Renewable Energy," Engineering, Technology & Applied Science Research, vol. 12, no. 4, pp. 8850–8855, Aug. 2022.

Downloads

How to Cite

[1]
Dridi, T., Jouini, H., Mami, A., El Mhamedi, A. and Dafaoui, E.M. 2023. Application of the Slime Mould Algorithm on the Bi-Objective Environmental Economic Dispatch Problem. Engineering, Technology & Applied Science Research. 13, 6 (Dec. 2023), 12190–12197. DOI:https://doi.org/10.48084/etasr.6358.

Metrics

Abstract Views: 277
PDF Downloads: 311

Metrics Information

License

Copyright (c) 2023 Tawba Dridi, Houda Jouini, Abdelkader Mami, Abderrahman El Mhamedi, El Mouloudi Dafaoui

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.

Crossref
Scopus
Google Scholar
Europe PMC