Comparative transient assessment and optimization of battery and hydrogen energy storage systems for near-zero energy buildings

This research study aims to address the integration of solar energy systems that can be incorporated into buildings to provide zero-energy buildings. In this study, a typical building is considered located in Bandar Abbas city, Iran. Since renewable energy is not always available, energy storage becomes crucial to supplying the energy needed. The primary objective of this case study is to compare two different methods of energy storage: battery and hydrogen storage. TRNSYS, a powerful program for transient simulation is used to model the energy system. TRNSYS's energy system simulation provides consumers with several notable benefits, but it lacks optimization methods. A neural network-genetic algorithm optimization is suggested as a solution to solve this issue. The results indicate that in systems with battery and H2 storage, 39 % and 37 % of the buildings' required electricity can be generated by PV panels, respectively. The findings show that integrating a storage system into the primary system enhances the system's energy security and reduces reliance on grid power. Following that, the optimal value related to the power of the electrolyzer, and fuel cell is computed using a neural network-genetic algorithm optimization approach. The optimal configuration has the least loss of power supply probability (LPSP), CO2 emission, and installation costs. MATLAB software is used to perform the optimization process. According to evaluated data, the hydrogen storage system results in total CO2 generation, LPSP, and total cost of 342 (ton/year), 0.841, and 0.637 (EUR.hr−1), respectively. Also, a parametric study on the battery-based system showed that with the best capacity (7 kW), the values of LPSP, CO2, and cost are 0.5412, 249 (ton/year), and 0.2751 (EUR.hr−1), respectively. Consequently, the battery is an appropriate storage solution for this case study.