Optimal Scheduling of Integrated Energy Systems Considering Demand Response and Conditional Value at Risk

To reduce carbon emissions, flatten load curves, and mitigate potential risks stemming from source-load uncertainties, an optimal scheduling model for the integrated energy system (IES) that incorporates demand response (DR) and conditional value at risk (CVaR) is proposed. Firstly, a carbon-green joint trading mechanism that incorporates a tiered green certificate mechanism is proposed on the source side, and a DR model guided by multiple energy prices on the load side is introduced into the model. Furthermore, the CVaR theory is introduced to quantify the potential risks brought by source-load uncertainty to the system from the perspectives of load loss and DR scheduling deviation. Subsequently, an optimized scheduling model is developed that comprehensively considers the carbon-green joint trading mechanism, DR model, and CVaR. Finally, the results indicate that the model effectively reduces system carbon emissions and mitigates the peak-to-trough difference in load profiles through case analysis and demonstration. With the introduction of CVaR, decision-makers are required to balance the economic and security aspects of the system, thereby enabling them to select a more rational optimization scheduling strategy.