Design optimization of a thermal-storage-based electricity storage for nanogrid applications

Thermal Energy Storage (TES) systems have shown a high potential for integrating intermittent renewable energy sources into energy systems by assisting with electrification of thermal loads. The aim of this paper is to develop a tool for the simulation and optimal design of a TES-based electricity storage of electricity produced by a photovoltaic system for nanogrid applications. The tool adopts a multi-objective approach with a view to reducing the costs associated with the nanogrid and saving primary energy, while satisfying the end-user multi-energy demand. The simulation/optimization tool is developed by coupling TRNSYS and Matlab softwares with the aim to find the design and operation strategies solutions on the Pareto frontier, and the problem is solved by using genetic algorithms. In the numerical test case, a single-family house of 200 m2 located in Italy is considered as residential end-user, and the winter and summer scenarios are considered for simulations. Results show the functionality of the tool in simulating and optimizing more or less complex energy systems and its effectiveness for providing good balancing solutions for end-users based on economic and energetic priorities.