## 1 Introduction
### Studies Related to the Hybrid Energy Systems  
Techno-economic feasibility of a hybrid energy system was investigated for electrifying village load in Sarawak, Malaysia. The system included FC and excluded FC were assessed and compared with diesel generation. Homer software was used to optimize and analyze. The analysis was based on net present cost (NPC), and the cost of energy (COE). The result shows that the hybrid system (PV/batteries) was economically feasible with NPC of $3,335,297 and the energy cost of 0.323 $/kWh with no emission. It was a suitable choice for replacement of conventional diesel based system, whereas FC based system was higher cost and excluded as the best choice for a case study [34]. A flower pollination algorithm (FPA) was employed to optimize hybrid energy system, and compared with the particle swarm optimization (PSO) and the artificial bee colony (ABC) techniques. The outcomes results shown that the FPA has less convergence time, and was better than the other two algorithms. Additionally, the losses power supply probability (LPSP) was 1.52% and the system NPC was $3,244,897, with levelized cost of energy (LCOE) of 0.334 $/kWh [35]. In [36] PSO showed a better result for optimization of grid-connected hybrid energy system (PV, solar thermal collector, FC) compared with genetic algorithm(GA). In the hybrid energy system (PV/Battery/FC), the hydrogen and fuel cell have been assessed and their potential verified for the telecom market. The result collected of full year has compared with diesel generator-based power system. The result illustrated that the integration of renewable energy solution was competitive regarding energy efficiency and reduced consumption of fossil fuel [37]. The colony selection algorithm (CSA) has been used for optimizing a hybrid energy system (PV/wind /FC), the results indicated that CSA was most cost-effective, and ensure reliable power supply with better LPSP. However, convergence time was longer compared with homer optimization [38]. In hybrid power system (PV/battery/FC/grid) [38], a demand response program (DRP) has been employed to achieve the best operation cost of the proposed system. The load was classified into off-peak, mid, and peak periods, and in each period the energy prices were different, export some amount of load from peak to other periods to reduce the cost. A thermal storage system is used to save energy in both off-peak and mid-period to supply load at peak hours. The result illustrated that using a demand response program has achieved the best cost effect of the system and minimized purchases power from the grid compared without used DRP [39]. A techno-economic study of hybrid energy system (PV/wind/battery/FC) has been conducted based on metrological data for different towns in Saudi Arabia. Six different configurations were studied. Homer pro was used to perform simulation and optimization. The study showed that the hybrid renewable energy sources with battery storage was most cost-effective, replacement battery with hydrogen storage system the cost increased because of the cost of electrolyzer, hydrogen tank, and fuel cell [40]. In addition, a hydrogen and battery storage system were powered by hybrid (PV/wind) for electrifying costal electric load in Izmir, Turkey. Homer pro was used to perform simulation, calculations, and optimization. The result illustrated that the LCOE of microgrid hybrid renewable energy sources was above the price of the energy unit of grid electricity. As well, battery storage has become a very mature technology, and is still economically dominant to hydrogen storage [41]. In the hybrid energy system (PV/wind/battery/FC), to minimize the cost cases of hydrogen energy storage were considered. The FC is considered as the secondary backup power supply to meet load deficit when the battery reached its minimum capacity. Homer is used to simulate and optimize the system. The result shows that the LCOE was more economical than previous study of hybrid power system (PV/wind/Genset) [42].