Optimal sizing of hybrid renewable energy systems in presence of electric vehicles using multi-objective particle swarm optimization

Delnia Sadeghi, Ali Hesami Naghshbandy and Salah Bahramara

Energy, 2020, vol. 209, issue C

Abstract: In this paper, the optimal sizing problem of the micro-grid’s resources in two different modes in the presence of the electric vehicle using the multi-objective particle swarm optimization algorithm is investigated. In this regard, the uncertain behavior of the electric vehicle is modeled using the Monte Carlo Simulation. In the first case named as PV/wind/battery, the optimum number of components and the amount of cost at different levels of reliability are determined. Then, the electric vehicle is added to the system regarding which the loss of power supply probability is recalculated in the both deterministic and stochastic states. The results show that the electric vehicle increases the system reliability. In the second system named as PV/wind/battery/EV, the effect of deterministic and stochastic behavior of electric vehicle on the number of components and the loss of power supply probability was investigated for the first time. The results demonstrated that the design of both systems is feasible, but the first system was more efficient than the second, because the latter used more winds in a number of identical LPSPs. Moreover, sensitivity analysis has been performed to show the effect of wind speed and load parameters on decision variables.

Keywords: Renewable energy sources; Micro-grid; Electric vehicle; Monte Carlo simulation; Multi-objective particle swarm optimization (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:209:y:2020:i:c:s0360544220315796

DOI: 10.1016/j.energy.2020.118471

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