Optimal Planning of Integrated Electricity and Heat System Considering Seasonal and Short-Term Thermal Energy Storage

This paper proposes a novel three-stage planning model for an integrated electricity and heat system (IEHS) with seasonal thermal energy storage (STES) and short-term TES, which considers the different energy cycling characteristics of STES and short-term TES and coordinately addresses multiscale uncertainties. In the proposed model, heat demand is firstly decomposed into two components reflecting seasonal and daily heat demand variations. Then, the operation of STES and short-term TES is separated considering multiscale uncertainties, where the large-scale uncertainty of seasonal heat demand is modeled as a fuzzy set in the second stage whereas the small-scale uncertainty of daily heat demand and wind power is represented by a set of scenarios in the third stage. To improve the computational efficiency while preserving the chronological continuity of the state of charge (SoC), a new STES model with the SoC limits only at the initial point in each representative period is developed. Furthermore, a pairwise reformulation is proposed to linearize the bilinear terms in pair fashion by taking advantage of the complementarity of two binary variables, which leads to fewer constraints with binary variables. Finally, numerical results demonstrate the effectiveness of the proposed planning model in improving the cost efficiency of the IEHS while reducing wind power curtailments. The superiority of the proposed STES model and pairwise reformulation on the improvement of computational efficiency is also verified.