Multi-Criteria Decision-Making Approach to the Intelligent Selection of PV-BESS Based on Cost and Reliability

Abstract

Addressing the challenge of meeting power demand with high reliability at low cost in Renewable energy (RE) generation is vital issue. The Autonomous Hybrid Energy Storage System (AHESS) to cover electrical deficit in Zigen clinic in southern Libya is introduced. It designed to produce 4 kW. The system comprises of photovoltaic (PV), Battery Energy Storage System (BESS) Flywheel Storage System (FESS) and Supercapacitance Storage System (SCSS). Six PV-BESS combinations, six criteria and three scenarios are studied. The research aim is to find the optimal PV-BESS combination based on low cost and high reliability. Multi-Criteria Decision Methods (MCDM) is implemented to select the optimal combination. The study utilizes Net Present Costs (NPC), Loss Power Supply Probability (LPSP), and Levelized Cost of Energy (LCOE) to assess each criterion. Six combinations of AHESS are implemented in MATLAB. Three MCDM methods are used to determine the optimal sizing of PV-BESS. Simulation results show that 30 PV panels and BESS 60 Ah are the optimal choices based on these results NPC = 19801 $/kWh, LPSP = 0.104 $/kWh, and LCOE = 0.032 $/kWh.