Robust Dispatch of Integrated Electric-Heat Systems Considering Weather-Parameter-Driven Residential Thermal Demands

Conventional day-ahead scheduling strategies of integrated electricity and heating system (IEHS) are oversimplified for the thermal demand modeling and cannot meet the thermal comfort of the users. Furthermore, this unbalanced power may lead to reserve capacity deficiency in the power system, due to the thermal-electric coupling of the combined heat and power (CHP) units in IEHS. This paper derives a tractable and accurate residential thermal demand (RTD) model, which comprehensively considers the impact of weather conditions. Then, a robust scheduling strategy is employed to tackle the uncertainties of the renewable generation outputs and RTDs, suggesting a double-stage optimization model. The first stage is to identify the unit commitment with minimum operational cost. In the second stage, the feasibility of the first stage unit commitment would be checked to minimize the summation of slack variables. Besides, the robust optimization model is converted into a mixed-integer linear program via the big-M method and solved by column and constraint generation (C & CG) algorithm. The simulation results show the effectiveness of the proposed RTD model, as well as the robust scheduling strategy for IEHS.