Two-Stage Distributed Robust Optimal Allocation of Integrated Energy Systems under Carbon Trading Mechanism

Abstract

The development of renewable energy and the construction of a comprehensive energy system with multiple complementary energy sources have gradually become the main direction of China’s energy development. As the penetration rate of renewable energy increases, the intermittent and fluctuating output of wind and solar power has a more significant impact on the system. This article conducts research on the optimization configuration of integrated energy system (IES) considering photovoltaic output uncertainty under a ladder carbon trading mechanism. Firstly, a two-stage distributed robust optimization (DRO) configuration model for integrated energy system is established. In detail, a deterministic model aimed at minimizing investment costs is given in the first stage and an uncertainty model aimed at minimizing operating costs in the probability distribution of the worst scenario is built in the second stage. Then, a data-driven distributed robust optimization method is adopted to deal with the uncertainty of photovoltaic output using MATLAB software (R2020A). Finally, the column and constraint generation (C&CG) algorithm is used to solve the problem, and the optimal investment capacity and cost results of the integrated energy system considering demand response under a ladder carbon trading mechanism are obtained. Through analysis, the proposed method achieves a 5.54% reduction in carbon emission costs while maintaining nearly unchanged investment costs, thus balancing economic and environmental benefits. Additionally, the CCG algorithm can effectively improve computational efficiency and guarantee the optimality of the solution.