Abstract
The main objective of the proposed article is the establishment of rules and tools for energy management optimization as well as the sizing of an autonomous wind and solar production system using an electrochemical storage device. The optimization criterion is techno-economic in order to minimize the energy produced cost, while considering the reliability level required by the consumer. Four most recent nature inspired algorithms have been employed to solve this complex optimization problem. This included ant lion optimizer algorithm (ALO), grey wolf optimizer algorithm (GWO), krill herd algorithm (KH) and JAYA algorithm, which is used for the first time in renewable systems sizing. Thus, the conducted methodology permits to determine the optimal system configuration, by minimizing the unit electricity cost (UEC) for a specified loss of power supply probability (LPSP) while counting the excess energy. Three electrochemical battery technologies including, lead-Acid (LA), lithium-ion (Li-ion) and Nickel-Cadmium (Ni-Cd) have been considered in this study. In order to predict the future performance of the studied system, various sensitivity analyzes have been carried out taking into account, the impact of the lifetime, the depth of discharge (DOD) and the relative cost of divers battery technologies on the UEC. The simulation results demonstrate the supremacy of the JAYA algorithm against the other algorithms. JAYA converges towards the optimal solutions for three battery technologies. It also shows that a 50% reduction in battery cost will reduce the cost of EUC by 30%, which would allow Li-ion batteries to become as competitive as LA batteries in terms of cost. Other similarly interesting results on the effect of DOD on UEC have been found. For DODs of 50% and 80% corresponding respectively, to Ni-Cd and Li-ion technologies, the UEC produced by the PV/Wind/Ni-Cd and PV/Wind/Li-ion systems becomes as attractive as that produced by the PV/Wind/LA system.
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