考虑综合需求响应与“双碳”机制的综合能源系统优化运行

针对我国经济社会发展所面临的高耗能、高污染问题，综合能源系统(integrated energy system, IES)为解决能源效率和环境污染等问题提供了新的途径。同时，灵活协调系统内各设备出力是实现系统低碳经济运行的关键前提。为进一步挖掘IES在经济运行与低碳环保方面的调度潜力，提出一种IES低碳经济调度模型。首先，建立一个包含光伏、风电、燃气机组、多种储能、碳捕集与电转气等设备的IES模型，并结合电、气、热负荷能源转换间耦合关系与柔性特征，构建综合需求响应模型。其次，考虑IES加入碳交易市场，引入阶梯式碳交易成本模型，对系统碳排放量进行制约。最后，以包含购能成本、碳排放相关成本以及需求响应补偿成本的系统综合运行成本最低为优化目标，采用CPLEX软件对模型求解。采用CPLEX软件对多种运行场景仿真求解，结果表明：所提出模型可有效降低系统运行成本与碳污染排放量。

Optimal operation of an integrated energy system considering integrated demand response and a "dual carbon "mechanism

In view of the high energy consumption and pollution problems facing economic and social development in China, an integrated energy system (IES) provides a new way to solve problems such as energy efficiency and environmental pollution. At the same time, flexible coordination of the output of various pieces of equipment in the system is key to realizing low-carbon and economic operation. To further explore the IES in terms of dispatch potential in economic operation and low-carbon environmental protection, an IES low-carbon economic dispatch model is proposed. First, this paper establishes an IES model including photovoltaic, wind power, gas-fired units, various types of energy storage, carbon capture and power-to-gas equipment. It then combines the coupling relationship and flexibility characteristics between electricity, gas, and heat load energy conversion to construct a comprehensive demand response model. Second, it considers IES joining the carbon trading market, and introduces a stepped carbon trading cost model to restrict system carbon emissions. Finally, the optimization goal is to minimize the comprehensive operating cost of the system including energy purchase, carbon emission-related and demand response compensation costs. CPLEX software is used to simulate various operation scenarios, and the results show that the proposed model can effectively reduce the system operation cost and carbon pollution emissions. This work is supported by the General Program of National Natural Science Foundation of China (No. 51777155).