Modeling and optimization of a heating and cooling combined seasonal thermal energy storage system towards a carbon-neutral community: A university campus case study

Combined energy storage system is a promising solution addressing renewables intermittent, improving storage density, and enhancing energy integration for sustainable community. However, achieving global optimization for this system with complex physical features and energy interactions is still challenging in current literature, especially in a seasonal vision. This paper proposes a modeling and optimization method for designing heating and cooling combined seasonal energy storage systems. Involving hybrid sensible-latent heat utilization, seasonal heat and cold shift are simultaneously achieved in one storage tank. To mathematically model the physical processes, we introduce temperature-constrained binary variables aligned with physical laws. Using a synthetic linearization based on McCormick envelope, the intrinsic nonlinearity in storage energy term is addressed while preserving constraints effectiveness. A campus case study illustrates the capability of the proposed method in capacity and operation co-optimizing for an integrated energy system with combined seasonal storage. Results indicate the combined system can reduce storage volume by 34.1 percent compared to traditional system. It contributes to a 25.9 percent decrease in generation capacity and an 11.1 percent reduction in conversion capacity, saving 10.5 percent of costs. Electricity load peak in winter and summer can be further reduced by 4.8 percent and 9.3 percent, respectively.