Component Sizing and Energy Management of Electric-Hydrogen Hybrid Energy Storage Systems for Solid-State-Transformer-Based Meshed Networks

This paper proposes a meshed distribution network architecture based on solid-state transformers (SSTs) to integrate various distributed energy resources (DERs) such as photovoltaic (PV) systems, battery energy storage systems (BESSs), and hydrogen energy storage systems (HESSs) composed of fuel cells, electrolyzers, and hydrogen tanks. Moreover, a co-design framework is developed to optimize the component sizing and energy management of an electric-hydrogen hybrid energy storage system (ESS) including a BESS and an HESS. The objective of the optimization framework is to minimize the total cost of the hybrid ESS categorized as the investment cost associated with component sizing and the operating cost related to energy management. In particular, this optimization framework explicitly considers the losses of the BESS, the HESS, and the distribution lines to more comprehensively evaluate the total cost of the hybrid ESS. In addition, convex transformations are introduced to reformulate the nonlinear equality constraints and the discrete inequality constraints into convex forms. Therefore, convex programming can be utilized to solve the optimization framework efficiently to obtain a globally optimal solution. The meshed network and the co-design framework are evaluated using a modified 59-node low-voltage AC (LVAC) grid model in the German SimBench dataset. Comprehensive simulations are performed using a 12-day dataset and a 366-day dataset of the year of 2016. Simulation results show that the meshed network leads to a better economy and a better voltage stability compared to the radial network. The optimization framework properly determines the power distribution between the BESS and the HESS based on the constraints and bounds of the ESS states such as the battery state of charge (SOC). In addition, the optimization framework is scalable and can be used to address the component sizing and energy management issues in large-scale distribution networks.