Large-scale renewable energy penetration desires higher flexibility in the power system. Combined heat and power virtual power plants (CUP-VPPs) provide an economic-effective method to improve the power system flexibility by aggregating the distributed resources of an electric-thermal coupling system. The topology can be optimally reconfigured in a power distribution system by operating tie and segment switches. Similarly

the heat flow profile can be redistributed in the district heating system (DHS) with valve switching and provide notable flexibility for CHP-VPPs self-scheduling. To address this issue

an aggregation model for the CHP-VPP is proposed to trade in typical day-ahead energy and reserve electricity markets

which is formulated as an adjustable robust optimization (ARO) problem to assure the realizability of all dispatch requests. The energy flow model is introduced in DHS formulation to make the model solvable. Due to the binary switching variables in the second stage of the proposed ARO problem

classical Karush-Kuhn-Tucker-based algorithms cannot be adopted directly and a nested column-and-constraint generation solution strategy is proposed. Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.