Abstract
Currently, the ideal sizing of hybrid technologies is one of the vital aspects of power system design. In this article, the design and optimization of the sizing of hybrid renewable energy systems (HRESs) with power-sharing capabilities in conjunction with electric vehicles (EVs) were proposed in two case studies. Two algorithms, namely, multi-objective particle swarm optimization (MOPSO) and multi-objective crow search (MOCS), have been formulated and were used to solve the problem being investigated. In case study 1 (CS1), four different HRESs are designed in the presence of EVs, meaning that for each HRES an EV and the power-sharing capability is employed. And also, the stochastic behavior of the EV using Monte Carlo simulation (MCS) is modeled. In case study 2 (CS2), four HRESs are designed with power-sharing capabilities, but in this case, for any of the HRESs, EV is not considered. This idea can be considered a novel breakthrough for the potential of power-sharing has been incorporated with the integration of EVs and HRESs. This approach improves the life cycle cost and loss of power supply probability indices. In summary, both cases in the presence and absence of EVs were compared with the simulation results. The results show that the use of the proposed EV significantly reduces the total cost of the engineered system. Furthermore, two meta-heuristic techniques were compared, and it was concluded that MOPSO had performed better than MOCS. Highlights Optimal sizing and power sharing of hybrid renewable systems with EVs. Proposed novel heuristic optimization approach using MOPSO and MOCS. Optimization of uncertainty parameters using 100 different scenarios using MCS. Economic and reliability benefits of the proposed system.