Low carbon economic dispatch of integrated energy system considering extended electric heating demand response

Retrofitting coal-fired units with carbon capture plants is an important means to achieve low-carbon improvements in integrated energy systems (IES). However, the lack of flexible resources restricts the development of carbon capture power plants, and the uncertainty of IES affects the reliability of system. With this background, this study proposes a low-carbon economic dispatch strategy considering extended electric heating demand response. Firstly, the organic Rankine cycle waste heat power generation is introduced to decouple the "power determined by heat" mode of combined heat and power. Secondly, incentive-based electric load demand response, as well as comfort fuzziness-based heat load demand response are considered. Subsequently, a datadriven distributionally robust optimization model is developed to solve the source-load uncertainty problem, where the confidence set of the uncertainty probability distribution is constrained by both 1-norm and infinity-norm constraints. The column and constraint generation (C&CG) algorithm is used to solve the model and obtain the operating output configuration. Finally, the test system verifies the effectiveness of the proposed method.