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Multi-Objective Immune-Commensal-Evolutionary Programming for Total Production Cost and Total System Loss Minimization via Integrated Economic Dispatch and Distributed Generation Installation

Author

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  • Mohd Helmi Mansor

    (Department of Electrical and Electronics Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Ismail Musirin

    (School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam 40450, Selangor, Malaysia)

  • Muhammad Murtadha Othman

    (School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam 40450, Selangor, Malaysia)

Abstract

Economic Dispatch (ED) problems have been solved using single-objective optimization for so long, as Grid System Operators (GSOs) previously only focused on minimizing the total production cost. In modern power systems, GSOs require not only optimizing the total production cost but also, at the same time, optimizing other important objectives, such as the total emissions of the greenhouse gasses, total system loss and voltage stability. This requires a suitable multi-objective optimization approach in ensuring the ED solution produced is satisfying all the objectives. This paper presents a new multi-objective optimization technique termed Multi-Objective Immune-Commensal-Evolutionary Programming (MOICEP) for minimizing the total production cost and total system loss via integrated Economic Dispatch and Distributed Generation installation (ED-DG). This involved the application of a weighted-sum multi-objective approach that combined with an optimization technique called Immune-Commensal-Evolutionary Programming (ICEP). The proposed MOICEP has been compared with other multi-objective techniques, which are Multi-Objective-Evolutionary Programming (MOEP) and Multi-Objective-Artificial Immune System (MOAIS). It was found that MOICEP performs very well in producing better optimization results for all the three types of Economic Dispatch (ED) problems compared to MOEP and MOAIS in terms of cheap total production costs and low total system loss.

Suggested Citation

  • Mohd Helmi Mansor & Ismail Musirin & Muhammad Murtadha Othman, 2021. "Multi-Objective Immune-Commensal-Evolutionary Programming for Total Production Cost and Total System Loss Minimization via Integrated Economic Dispatch and Distributed Generation Installation," Energies, MDPI, vol. 14(22), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7733-:d:681945
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    References listed on IDEAS

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    1. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
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