Robust Scheduling of Integrated Electricity and Heating System Hedging Heating Network Uncertainties

The coordinated operation of an integrated electricity and heating system (IEHS) can improve overall energy efficiency and provide additional flexibility. However, the inherent uncertainties pertaining to pipeline parameters and ambient temperature in a district heating network (DHN) have not been addressed in the literature, although such uncertainties could affect the quality or even security of IEHS operation. To address this issue, we propose a two-stage robust IEHS scheduling model that considers the uncertainties of the heat load, ambient temperature and heat dissipation coefficients of heating pipelines. The proposed model embedded with bilinear terms is equivalently transformed via the big-M method into an adaptive linear robust optimization problem that can be solved by the column-and-constraint generation (C&CG) algorithm. Case studies are conducted for two test systems. The simulation results show that the proposed method can effectively handle the uncertainties in DHN and improve the robustness of the IEHS.