为了实现“双碳”目标、促进多能源互补，构建以新能源为主体的新型电力系统，文中建立了电转气-碳捕集利用与封存装置（power to gas and carbon capture utilization and storage，P2G-CCUS）耦合系统下含光热发电（concentrating solar power，CSP）站的虚拟电厂（virtual power plant，VPP）优化调度模型，考虑需求响应（demand response，DR）参与调峰市场（peak shaving market，PSM）制定分时电价为系统带来收益，从而进一步降低系统运行成本，并引入短期风功率预测及熵值权重法协助后期调度求解。在多能源互补层面，针对风能特点建立风电与CSP联合运行系统。在低碳化方面，建立P2G-CCUS耦合系统，其中包含两段式电转气、燃气轮机（gas turbine，GT）和碳捕集利用与封存系统的数学模型，提出以运行成本最低、碳排放量最小为目标的优化调度策略。采用MATLAB调用CPLEX进行求解，通过设置不同的场景进行对比，结果表明文中所提的优化调度策略可充分实现碳循环利用，极大限度地减少碳排放，具有显著的经济及社会效益。
英文摘要:
In order to realize the goal of "dual carbon", promote the complementarity of multiple energy sources, and construct a novel power system with new energy as the main body, this paper establishes a virtual power plant (VPP) optimal scheduling model with concentrating solar power under the coupling system of power to gas and carbon capture utilization and storage (P2G-CCUS) device, and considers the demand response (DR) to participate in peak shaving market (PSM) to establish time-of-use electricity price to bring benefits to the system, so as to further reduce the operating cost of the system. The short-term wind power prediction and entropy weight method are introduced to assist the later scheduling solution. At the level of multi-energy complementarity, the combined operation system of wind power and concentrating solar power（CSP）is established according to the characteristics of wind energy. In terms of low carbonization, the P2G-CCUS coupling system is established, which includes the mathematical models of two-stage power to gas, gas turbine (GT) and carbon capture utilization and storage system, and the optimal scheduling strategy with the lowest operating cost and minimum carbon emission is proposed. MATLAB is used to call CPLEX to solve the problem, and different scenarios are set for comparison. The results show that the optimal scheduling strategy proposed in the paper can fully realize the recycling of carbon, greatly reduce carbon emissions, which has significant economic and social benefits.