Cross-Sectoral Reliability-Constrained Sizing of Thermal Storage in Multi-Energy Systems

The increasing electrification in district heating systems through electric heat pumps and the resulting coupling between electrical and heating systems presents challenges to network operators and planners, but it also offers high flexibility potential in distribution network operation. The flexibility offered by electric heat pumps and thermal storages can play a vital role in providing affordable energy storage and the potential for load shifting. However, this flexibility comes with uncertainty as it depends on changing weather conditions and customer behavior. Therefore, the correct sizing of the thermal storage capacities in the planning phase of multi-energy systems (MES) is essential for guaranteeing sufficient flexibility for electrical network operation. Moreover, existing reliability metrics do not capture the interactions between the electrical and thermal domains of MESs. In this paper, a novel methodology is presented for optimal sizing under the uncertainty of thermal storage capacities in a heating network coupled to an electrical network. Distributionally robust chance-constrained optimization (DRCC) is used to model the system to limit the probability of insecure operation due to uncertainty in heat demand forecasting. The proposed approach is demonstrated on a modified MES and the results are compared to those obtained from a conventional deterministic optimization model. A new reliability metric, Expected Heat Not Supplied (EHNS), is introduced to evaluate system reliability. The proposed methodology is designed to provide network planners and operators with the optimal storage capacities needed to balance robustness against existing uncertainties, costs, and system reliability.