The dynamic planning of a microgrid, considering uncertainties, was performed by Sun et al. in [16]. The optimal scheduling of a microgrid that comprised wind, photovoltaic (PV) and hydrogen storage was determined by Zhang et al. in [17]. A rural microgrid was investigated by Alluraiah et al. in [18], and its operation cost was minimum, while in [19] study was performed by Zhong et al. on a real microgrid. In [20], the optimal power dispatch of the microgrid sources and hydrogen storage was determined by Ghezelbash et al. in order to maximize the profit of the microgrid. A control strategy was developed by Villa Londono et al. in [21]; power exchange was reduced, and stability of the microgrid was improved. The management of a microgrid using wind, PV, battery, fuel cell and supercapacitor power was studied by Sahri et al. in [22], who found that overcharging was avoided. The recent advances in the field of PV and fuel cells were investigated by Arsalis et al. [23].

The management and optimization of the operation of an islanded microgrid were performed by Abdelsalam et al. in [24], in which RESs provided a high amount of power and the backup diesel generator was used less. The expenditure cost and operational revenues were optimized by Cao et al. for a microgrid in [25], so the costs were reduced by 50%. Day-ahead and intra-day optimization were performed by Wang et al. in [26], so the operation cost of the microgrid which comprised wind, PV and hydrogen storage was reduced. The energy management of a hybrid microgrid was studied by Alzahrani in [27], so the reactive power of the loads was reduced by 90%. The optimal power dispatch was determined by Hou et al. in [28] for a system with power, hydrogen and heat storage, in which efficiency and profit were improved. The use of an electrolyser designed for a quick response in case the power demand was higher than the power supplied in a microgrid was investigated by Ganeshan et al. in [29]. In [30], it was determined by Oliveira et al. that the use of hydrogen for transport, industrial applications and buildings can help reduce CO₂ emissions by 18%. A controller was developed by Behera et al. in [31] for power smoothing in a microgrid with a supercapacitor and redox flow battery. The economic feasibility of a microgrid was investigated by Shanbog et al. in [32] considering the cost of power, investment costs and operational costs.

The optimal management of a residential microgrid, which comprised combined heat and power loads, electric vehicles and charging/discharging behaviour was determined by Gong et al. in [33]. A 100% RES station was developed by Li in [34] in order to supply a microgrid. Fan et al., in [35], minimized the daily operation cost of a microgrid. The performance of a hydrogen storage system in a microgrid was investigated by Serra et al. in [36], in which its annual hydrogen production was optimized. In [37], the optimal management of a microgrid with bidirectional power–hydrogen conversion was determined by Khaligh et al. considering price uncertainties and RES power output. The optimal design of a microgrid was determined by Valverde et al. in [38], while a controller was developed by Cecilia et al. in [39] for the optimal management of a microgrid with short-term storage. The frequency and voltage control were investigated by Naseri et al. in [40] for an islanded microgrid that comprised PV sources. The operation of a hydrogen hub with a microgrid was studied by Hossain et al. in [41], so power balance was respected and power-to-hydrogen and hydrogen-to-power were provided when required.

The efficiency of a hydrogen storage system was studied by Bovo et al. in [42], while in [43] Van et al. reviewed the energy management strategies for microgrids. Califano et al. reduced the size of a hydrogen storage tank by 40% in [44] due to the control strategy. The optimization of a microgrid with electrical and hydrogen loads was performed by Mah et al. in [45], while the participation of the power-to-hydrogen in the power markets in order to minimize the operation costs was investigated by Mansour-Saatloo in [46]. The modeling and analysis of a direct-current microgrid with hydrogen storage were studied in [47,48]. A self-control algorithm for a microgrid was developed and studied by Yang et al. in [49], while Gugulothu et al. determined in [50] the optimal strategy for the power output of the microgrid sources.

The optimal supply of electric and fuel cell vehicles was studied by Förster et al. in [51], while Abo-Elyousr et al. determined in [52] the optimal configuration and size of the sources of a microgrid. Hybrid power–hydrogen refuelling stations, electric, natural gas and hydrogen stations in microgrids were studied in [53,54], while Navas et al. optimized the investment and operation costs in [55] for a hybrid heat and power residential microgrid. The optimal power management was studied by Yousri et al. in [56] for a microgrid considering battery degradation, discomfort, peak-to-average ratio and consumer discomfort, while Kbidi et al. studied in [57] the unit commitment for the components of a microgrid (PV sources, fuel cell, battery and electrolyser). The dispatch of power and hydrogen in real time was studied by Lin et al. in [58] considering the power markets, which resulted in a reduction in the daily operational costs of 37%. The emissions of a FCEV were studied by Heidary et al. in [59]. The emissions were between 50% and 28% lower compared to gasoline vehicles and BEVs. The use of FCEVs in vehicle-to-grid mode was studied by Robledo in [60]. The use was economically beneficial for the end user if the hydrogen prices were below 8.24 EUR/kg. The techno-economic, environmental and safety assessments of hydrogen microgrids were studied by Mukherjee in [61]. The results showed that the system does not have a positive net present value at the end of its project life. The optimal design of a hybrid charging station for battery electric vehicles and fuel cell electric vehicles was performed by Sánchez-Sáinz in [62].

Similar to battery electric vehicles, it is anticipated that sales of fuel cell electric vehicles will increase in the upcoming years. Due to the large hydrogen demand that will result from this increase, it is necessary to research any potential effects on power costs and CO₂ emissions.