###### Abstract  
Due to the rising cost of fossil fuels and environmental pollution, renewable energy (RE) resources are currently being used as alternatives. To reduce the high dependence of RE resources on the change of weather conditions, a hybrid renewable energy system (HRES) is introduced in this research, especially for an isolated microgrid. In HRES, solar and wind energies are the primary energy resources while the battery and fuel cells (FCs) are considered as the storage systems that supply energy in case of insufficiency. Moreover, a diesel generator is adopted as a back-up system to fulfill the load demand in the event of a power shortage. This study focuses on the development of HRES with the combination of battery and hydrogen FCs. Three major parts were considered including optimal sizing, maximum power point tracking (MPPT) control, and the energy management system (EMS). Recent developments and achievements in the fields of machine learning (ML) and reinforcement learning (RL) have led to new challenges and opportunities for HRES development. Firstly, the optimal sizing of the hybrid renewable hydrogen energy system was defined based on the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software for the case study in an island in the Philippines. According to the assessment of EMS and MPPT control of HRES, it can be concluded that RL is one of the most emerging optimal control solutions. Finally, a hybrid perturbation and observation (P&O) and Q-learning (h-POQL) MPPT was proposed for a photovoltaic (PV) system. It was conducted and validated through the simulation in MATLAB/Simulink. The results show that it showed better performance in comparison to the P&O method. HRES; optimal sizing; MPPT control; EMS and reinforcement learning +
Footnote †: journal: Applied  
in the Association of Southeast Asian Nations (ASEAN), especially Vietnam, Thailand, Indonesia, Malaysia, and the Philippines have recently begun paying attention to green energy and have become the most successful countries for renewable energy deployment [1]. With the cost reduction and technological improvement, renewable energy (RE) resources are being combined with conventional generator and storage systems to supply the load demand with low power generation cost, high efficiency and reliability, and low fuel consumption that can reduce the environmental pollution problem. Moreover, the standalone hybrid renewable energy system (HRES) for rural and islanding electrification could be more cost-effective than grid extension, which is estimated to cost US$10,000 to US$50,000 per kilometer [2]. The developed system for this project adopted the RE resources (solar and wind energies) as primary energy resources. In addition, an electrolyzer was applied to produce hydrogen that was contained in the hydrogen tank for the operation of fuel cells (FCs). The battery and FCs were used as the storage systems that supply energy in case of insufficiency, and a diesel generator functioned as a back-up system to fulfill the load in the event of bad weather conditions [3]. In HRES, FC can be used as an option for long term energy storage [4]. However, the slow dynamics of FC and its degradation for the frequent start-up and shut down cycles are major disadvantages. Therefore, the battery is introduced to such hybrid systems for taking care of power deficits and acting as a short term energy storage medium [5]. The combination of FC and battery along with photovoltaic (PV) and wind turbines (WTs) ensures an uninterrupted power supply to the load. Based on the requirement of energy demand and various technologies of RE resources, it is important to figure out the optimal configuration or suitable sizing of hybrid energy system components which can decrease the system cost and retain high reliability. There are many methodologies applied to proper unit sizing of HRES components such as artificial intelligence [6; 7], multi-objective design [8], an iterative technique [9], probabilistic approach [6], etc.