Application of a new hybridization to solve economic dispatch problem on an algerian power system without or with connection to a renewable energy
1
Faculty of electrical engineering. USTO, B.P 1505 El M’naouar, Oran, 31000, Algeria
2
Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, 47133, Ghardaïa, Alegria.
3
Department of Electrical Engineering, University Kasdi Merbah, 30000 Ouargla, Algeria
Submission date: 2021-06-22
Final revision date: 2021-09-07
Acceptance date: 2021-09-08
Online publication date: 2021-09-13
Publication date: 2021-09-13
Corresponding author
Abdelkader Si Tayeb
Faculty of electrical engineering. USTO, B.P 1505 El M’naouar, Oran, 31000, Algeria
Faculty of electrical engineering. USTO, B.P 1505 El M’naouar, Oran, 31000, Algeria
Diagnostyka 2021;22(3):101-112
KEYWORDS
TOPICS
ABSTRACT
The most important contribution of this article is the use of four metaheuristic approaches to tackle the problem of economic dispatching, with the goal to study the influence of the injection of a renewable energy source on the electricity cost in the Algerian network, and minimizing the production cost of electrical energy while accounting for transmission losses.
A Genetic Algorithm (GA) (a real coding) and Egyptian Vulture Optimization Algorithm (EVOA), as well as two hybridizations between the metaheuristics: Classic and Modern hybridization (C.H.GA-EVOA, M.H.GA-EVOA), are presented in this work. These techniques are used to address optimization difficulties of two Algerian electricity networks. The first has three system units, whereas the second has fifteen system units. The second electricity network is connected to a solar energy source.
The findings obtained are compared with other techniques to validate the high performance of the suggested methods for addressing the economic dispatch issue. This study demonstrates that EVOA and C.H.GA-EVOA provide trustworthy results, and that M.H.GA-EVOA surpasses them.
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