Techno-economic analysis and optimization of hybrid energy systems based on hydrogen storage for sustainable energy utilization by a biological-inspired optimization algorithm

Abstract

Wind energy resources based on hydrogen energy storage systems are recognized as clean alternative sources from the perspective of sustainable development. A low-cost hydrogen energy storage system is recognized as a cornerstone of a renewables-hydrogen economy. The hybridization of wind turbines, as a non-dispatchable resource, and hydrogen storage system, as energy storage, can provide a promising hybrid energy system. The main outlook of the present paper is to develop a biological-inspired optimization algorithm for the optimal design of an off-grid wind power generator considering a hydrogen energy storage system. The parameters of the system are optimized with respect to two objective functions, namely the total cost, and load loss of the system. To obtain an efficient optimum capability, an artificial bee colony optimization method is introduced. Its results are compared with the results of the particle swarm optimization algorithm. Eight different small horizontal-axis wind turbines are used for the optimal design of an off-grid system. A sensitivity analysis is conducted by varying the capital cost of the components to determine how total cost and load loss are affected by the change of the input variables. Simulation results show that at load loss = 0 and 20 %, the cost of energy (COE) is around 0.6907 and 0.3771 $/kWh, respectively. The variation of wind turbine (WT) and hydrogen storage system capital costs have a significant impact on total cost value. Among the investigated systems, the Fortis-WT- hydrogen storage system with 0.5987 $/kWh COE has the minimum cost and maximum reliability (100 %). The superiority of the proposed algorithm compared to the particle swarm optimization algorithm is confirmed.