Robust Coordinated Planning of Multi-Region Integrated Energy Systems With Categorized Demand Response

In this paper, categorized demand response (DR) programs are proposed to address the coordinated planning problem in multi-region integrated energy systems (MRIESs). The categorized DR programs comprise a discrete manufacturing production model for industrial areas, a real-time pricing-based DR program for commercial areas, and diverse operational tasks for various electrical appliances in residential areas. Subsequently, the detailed DR model is leveraged to minimize the operation cost and gas emissions in a renewable-integrated MRIES considering the uncertainties from wind and solar power. Then, a flexible adjustable robust optimization (FARO) approach is presented to deal with all uncertainty sources. The FARO approach aims to ensure the safe operation of the MRIES against any uncertainty while meeting predefined performance objectives. Furthermore, a bi-level solution algorithm is designed by combining the stochastic dichotomy method and the column-and-constraint generation (C&CG) algorithm to solve our coordinated planning model. Finally, case studies are conducted on a practical MRIES in Changsha, China. Experimental results indicate the effectiveness of the categorized DR programs in adjusting allocable resources to maximize holistic system profits. Besides, compared to the commonly used information-gap decision theory (IGDT) method, our FARO approach can maintain the optimality of the solution while reducing conservatism.