Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage

Abstract

Energy storage is essential to address the intermittent issues of renewable energy systems, thereby enhancing system stability and reliability. This paper presents the design and operation optimisation of hydrogen/battery/hybrid energy storage systems considering component degradation and energy cost volatility. The study examines a real-world case study, which is a grid-connected warehouse located in a tropical climate zone with a photovoltaic solar system. An accurate and robust Multi-Objective Modified Firefly Algorithm (MOMFA) is proposed for the optimal design and operation of the energy storage systems of the case study. To further demonstrate the robustness and versatility of the optimisation method, another synthetic case is tested for a location in a temperate climate zone that has a high seasonal mismatch. The modelling results show thatthe system in the tropical zone always provides a superior return when compared to a similar system in the temperate zone due to abundant solar resources.When comparing battery-only and hydrogen-only systems, battery systems perform better than hydrogen systems in many situations, with a higher self-sufficient ratio and net present value. However, if there is high seasonal variation and a high requirement for using renewable energy (the penetration of renewable energy is >80 %), using hydrogen for energy storage is more beneficial. Furthermore, the hybrid system (i.e., combining battery and hydrogen) outperforms battery-only and hydrogen-only systems. This is attributed to the complementary combination of hydrogen, which can be used as a long-term energy storage option, and battery, which is utilised as a short-term option. This study also shows that storing hydrogen in a long-term strategy can lower component degradation, enhance efficiency, and increase the total economic performance of hydrogen and hybrid storage systems. The developed optimisation method and findings of this study can support the implementation of energy storage systems for renewable energy.