TY - EJOU AU - Rezk, Hegazy AU - Mukhametzyanov, Irik Z. AU - Al-Dhaifallah, Mujahed AU - Ziedan, Hamdy A. TI - Optimal Selection of Hybrid Renewable Energy System Using Multi-Criteria Decision-Making Algorithms T2 - Computers, Materials \& Continua PY - 2021 VL - 68 IS - 2 SN - 1546-2226 AB - Several models of multi-criteria decision-making (MCDM) have identified the optimal alternative electrical energy sources to supply certain load in an isolated region in Al-Minya City, Egypt. The load demand consists of water pumping system with a water desalination unit. Various options containing three different power sources: only DG, PV-B system, and hybrid PV-DG-B, two different sizes of reverse osmosis (RO) units; RO-250 and RO-500, two strategies of energy management; load following (LF) and cycle charging (CC), and two sizes of DG; 5 and 10 kW were taken into account. Eight attributes, including operating cost, renewable fraction, initial cost, the cost of energy, excess energy, unmet load, breakeven grid extension distance, and the amount of CO2, were used during the evaluation process. To estimate these parameters, HOMER® software was employed to perform both the simulation and optimization process. Four different weight estimation methods were considered; no priority of criteria, based on a pairwise comparisons matrix of the criteria, CRITIC-method, and entropy-based method. The main findings (output results) confirmed that the optimal option for the case study was hybrid PV-DG-B with the following specification: 5 kW DG, RO-500, and load following control strategy. Under this condition, the annual operating cost and initial costs were $ 5546 and $ 161022, respectively, whereas the cost of energy was 0.077 $/kWh. The excess energy and unmet loads were 40998 and 2371 kWh, respectively. The breakeven grid extension distance and the amount of CO2 were 3.31 km and 5171 kg per year, respectively. Compared with DG only, the amount of CO2 has been sharply reduced by 113939 kg per year. KW - Al-Minya city (Egypt); energy efficiency; multi-criteria decision-making; optimization; renewable energy; reverse osmosis units DO - 10.32604/cmc.2021.015895