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.
Highlights
Over the past two decades, many researchers were concerned about multi-state systems dependability, for example, regarding optimization and performance measurement [1], multi-state analysis using a fault tree applied to a satellite-based railway system [2], and a multi-state dependability simulation using Monte Carlo [1]
The purpose is to select the optimal combination of elements used in theseries-parallel electrical power system, which must correspond to the maximization of system availability and the minimization of system investment cost
We have proposed a resolution for the multi-state heterogeneousseriesparallel electrical power system design multi-objective problem, considering the necessity of high reliability and a lower budget
Summary
Over the past two decades, many researchers were concerned about multi-state systems dependability, for example, regarding optimization and performance measurement [1], multi-state analysis using a fault tree applied to a satellite-based railway system [2], and a multi-state dependability simulation using Monte Carlo [1]. We used Lagrange multipliers to determine the number of redundant elements in the power system in order to maximize reliability [9] At this time, the redundancy optimization problem still attracts many researchers, such as a binary matrix to model a multi-type production system with cold standby redundant subsystems [10]. The authors of [24] proposed an advanced reliability–redundancy problem that considers an optimal redundancy strategy, either active or cold standby, with an imperfect detector/switch They used a parallel genetic algorithm for solving the allocation problem in a mixed-integer nonlinear programming model. To evaluate the reliability of multi-state series-parallel systems, a rapid reliability estimation function was developed This procedure is based on the mathematical technique of the Laplace transform. The proposed approach regarding the distinctive multi-objective problems is investigated, based on an industrial system of electro-energy production
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