Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

Khaled Guerraiche, Latifa Dekhici, Eric Chatelet and Abdelkader Zeblah
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Khaled Guerraiche: Department of Electrical Engineering, Higher School of Electrical Engineering and Energetic of Oran, Oran 31000, Algeria
Latifa Dekhici: Department of Computer Sciences, University of Sciences and the Technology of Oran, (USTO-MB), Oran 31000, Algeria
Eric Chatelet: Université de technologie de Troyes, UR InSyTE, 12 rue Marie Curie, CS 42060, CEDEX, 10004 Troyes, France
Abdelkader Zeblah: Department of Electrical Engineering, Engineering Faculty, University of Sidi Bel Abbes, Sidi Bel Abbès 22000, Algeria

Energies, 2021, vol. 14, issue 13, 1-19

Abstract: The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system.

Keywords: multi-objective optimization; metaheuristics; bat algorithm; generalized fly; reliability; cost; power system design; Ushakov method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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