Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system. (15th November 2016)

• Record Type: Journal Article
• Authors: Baghaee, H.R.; Mirsalim, M.; Gharehpetian, G.B.; Talebi, H.A.
• Is Part Of: Energy. Volume 115(2016)Part 1
• Page Start: 1022
• Page End: 1041
• Publication Date: 2016-11-15
• Subjects: Wind energy -- Photovoltaic -- Fuel cell -- Reliability -- Optimal sizing -- Multi-objective particle swarm optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.09.007
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The main goal for designing hybrid wind–solar generating microgrid systems is reliable supply of load, under varying weather conditions, with the minimum cost and maximum reliability. In this paper, a hybrid wind-solar generation microgrid system with hydrogen energy storage is designed for a 20-year period of operation using novel multi-objective optimization algorithm to minimize the three objective functions namely annualized cost of the system, loss of load expected and loss of energy expected. System costs involve investment, replacement and operation and maintenance costs and the major components of system may be subjected to failure. The simulation results based on multi-objective particle swarm optimization for different cases reveal the impact of components outage on reliability and cost of the system. In addition, an approximate method for reliability evaluation of hybrid system is presented which lead to reduce computation time. Simulation results show effectiveness of proposed multi-objective algorithm to solve optimal sizing problem in contrast with traditional single objective methods. Highlights: Using MOPSO algorithm to minimize costs of the system and reliability indices LOLE & LOEE. Comparison and improvement respect to the previous researches. presenting an approximate method for reliability evaluations of the hybrid system. Detailed simulation of proposed optimal sizing for all cases.