Techno-economic assessment of a Hybrid Energy Storage System for the production of green hydrogen using Particle Swarm Optimization

In a future energy system, the large share of volatile renewable energy will increase flexibility needs to resolve the temporal mismatch between demand and supply. A central enabler for this flexibility needs is energy storage. While short duration storage applications recently are getting widely adopted, in a renewable based future energy system there will be an increasing need for Long Duration Energy storage. Stand-alone long duration energy storage technologies, however, face economic challenges due to their high capital costs and limited revenue streams. To overcome these challenges, hybrid energy storage systems (HESS) that combine long duration storage with short duration storage have gained significant attention in scientific literature. By integrating different storage technologies, HESS can enhance the overall performance and economic viability of energy storage systems, benefitting from the strength of both technologies. This master's thesis project focuses on conducting a techno economic analysis of an energy system to produce green hydrogen in combination with a Li-ion battery storage and a hydrogen storage. The hydrogen is produced to substitute the methane consumption of a final heavy industry user on an hourly basis. By utilizing Particle Swarm Optimization (PSO), the research aims to optimize contemporary the sizing of the components. A rule-based control system determines the control strategy, considering the specific requirements of heavy industry applications. Through the development of a rule-based energy management strategy, the system takes the generation and demand profile and is able to compute the hourly state for each component. The whole system is developed in python. The results highlight that the high capital cost of battery storage cannot be recovered through a better exploitation of solar energy. To make the Li-ion battery storage interesting the grid withdrawal price must be increased substantially, or other revenue sources for the battery storage must be included. Hydrogen storage on the other side allows to transform a higher share of PV into hydrogen and with the comparably low capital cost lowers the levelized cost of hydrogen. Consequently, the optimal solution is not represented by a HESS, but rather by a single storage solution with hydrogen. A sensitivity analysis on the electricity prices shows that if grid injection is remunerated at a price close to the levelized cost of electricity of PV or higher, it is convenient to maximize the installed capacity. For these grid injection prices the PV grid injection subsidizes the hydrogen production. On the other side lower electricity acquisition prices lower the installed PV capacity and consequently also the installed electrolyzer and hydrogen storage capacity. The analysis of a 2030 future scenario shows significant cost reductions compared to today, being in line with recent studies on green hydrogen production. However, none of the solutions is able to economically compete with the cost of conventional natural gas supply, even if carbon taxes are considered. These results highlight further need for technological improvement as well as policy adaptions to generate interesting investment cases and foster the substitution of natural gas.