综合能源系统是实现“双碳”目标的有效途径,为进一步挖掘其需求侧可调节潜力对碳减排的作用,提出了一种碳交易机制下考虑需求响应的综合能源系统优化运行模型。首先,根据负荷响应特性将需求响应分为价格型和替代型2类,分别建立了基于价格弹性矩阵的价格型需求响应模型,及考虑用能侧电能和热能相互转换的替代型需求响应模型;其次,采用基准线法为系统无偿分配碳排放配额,并考虑燃气轮机和燃气锅炉的实际碳排放量,构建一种面向综合能源系统的碳交易机制;最后,以购能成本、碳交易成本及运维成本之和最小为目标函数,建立综合能源系统低碳优化运行模型,并通过4类典型场景对所提模型的有效性进行了验证。通过对需求响应灵敏度、燃气轮机热分配比例和不同碳交易价格下系统的运行状态分析发现,合理分配价格型和替代型需求响应及燃气轮机产热比例有利于提高系统运行经济性,制定合理的碳交易价格可以实现系统经济性和低碳性协同。

The integrated energy system (IES) is an effective way to achieve the“carbon neutrality and emission peak”goal. In order to further explore the role of the adjustable potential of demand side on carbon emission reduction, an optimized operation model of IES considering the demand response under the carbon trading mechanism is proposed. Firstly, according to the characteristics of load response, the demand response is divided into two types: price-type and substitution-type. The price-type demand response model is established on the basis of price elasticity matrix, and the substitution-type demand response model is constructed by considering the conversion of electricity and heat. Secondly, base-line method is used to allocate free carbon emission quota for the system, and considering the actual carbon emissions of gas turbine and gas boiler, a carbon trading mechanism for the IES is constructed. Finally, a low-carbon optimal operation model of IES is established, whose objective is to minimize the sum cost of energy purchase, cost of carbon transaction and cost of IES operation and maintenance. The effectiveness of the proposed model is verified through four typical scenarios. By analyzing the sensitivity of demand response, heat distribution ratio of gas turbine and the operating state of the system under different carbon trading prices, it is found that reasonable allocation of price-type and substitution-type demand response and heat production ratio of gas turbine is beneficial to improve the operating economy of the system. Making reasonable carbon trading price can realize the coordination of system economy and low carbon.

为兼顾区域综合能源系统（regional integrated energy system，RIES）中能耗成本、污染排放、风电消纳等多个调度目标，建立了考虑综合需求响应的RIES多目标优化模型。首先，对含电转气、储能系统、热电联产机组等设备的RIES建模，并在区域内引入了具体考虑削减负荷、转移负荷和替代负荷的综合需求响应，旨在削减系统负荷峰谷差。然后，分别建立了以系统用能成本、弃风功率和污染物治理成本最小的目标函数，采用多目标优化方法——以模糊加权规划遍历权值求解帕累托前沿，再根据证据推理决策方法寻找最优调度策略。最后基于典型算例研究，结果表明了所提多目标优化算法能有效在多个调度目标间做出权衡，考虑综合需求响应的RIES在总能耗、环境友好和风电消纳等方面更具优势。

In order to reconcile several dispatch objectives such as the cost of energy consumptions， pollutant emissions and wind power accommodation in the integrated energy system， the multi-objective optimal dispatch model of the integrated energy system considering integrated demand response is established in this paper. Firstly， the modeling of the regional integrated energy system including some devices such as power to gas， energy storage， and combined heat and power units is elaborated， and the modeling of the integrated demand response which consists of load shedding， load shifting， and load substituting is also considered in the system to decrease peak-valley difference. Secondly， the objectives that are respectively to minimize the comprehensive cost， wind power curtailment， and cost of pollutant treatment are established. The proposed multi-objective optimization method， which firstly utilizes multi-objective weighted fuzzy programming to obtain the Pareto front， and then pursue the minimum Euclidean distance between all the Pareto non-inferior solution and the ideal solution， is adopted to solve the optimal dispatch strategy. Finally， on the basis of the typical numerical simulations， the results demonstrate that the proposed multi-objective optimization algorithm can effectively balance the multiple dispatch objectives. The integrated energy system would have more advantages in the gross energy consumptions， environment， and the wind power accommodation after considering the integrated demand response.

In the context of the Energy Internet, customers are supplied by energy hubs (EH), while the EHs are interconnected through an upper-level transmission system. In this paper, a stochastic scheduling model is proposed for the interconnected EHs considering integrated demand response (DR) and wind variation. The whole integrated energy system (IES) is linearly modeled for the first time. The output-input relationship within the energy hub is denoted as a linearized matrix, while the upper-level power and natural gas transmission systems are analyzed through piecewise linearization method. A novel sequential linearization method is further proposed to balance computational efficiency and approximation accuracy. Integrated demand response is introduced to smooth out demand curve, considering both internal DR achieved by the optimal energy conversion strategy within energy hubs, and external DR achieved by demand adjustment on the customer’s side. Distributed energy storage like natural gas and heat storage are considered to provide buffer for system operation. The proposed stochastic model is solved by scenario-based optimization with a backward scenario reduction strategy. Numerical tests on a three-hub and seventeen-hub interconnected system that validates the effectiveness of the proposed scheduling model and solution methodology.

The community integrated energy system (CIES) can significantly improve energy utilization and promote the consumption of renewable energy through multi-energy coupling complementary and collaborative optimization scheduling. It has become a new energy utilization realization approach for users to meet multi-energy supply and demand. Taking a community in Xiong’an New District, Hebei province as the research object, this paper designed a two-stage optimization approach for the CIES that takes into account the reliability of load supply. The first stage is based on the non-dominated sorting genetic algorithm II(NSGA-II) with elite preservation strategy to optimize the equipment type and capacity of the community energy station. It is a multi-objective planning optimization problem, and its purpose is to achieve the coordinated optimization of economic costs and environmental costs. The second stage is an operation optimization problem. As for the multiple Pareto frontier solutions obtained in the previous planning stage, the mixed integer linear programming (MILP) was used to separately optimize the operation cost and load supply reliability indicators of each planning scheme, and the result is used as an important reference for determining the best planning scheme. Case studies show that the designed planning approach can effectively reduce the system operating cost and guarantee the reliability of load supply, and it is more practical for instructing the CIES planning.

综合能源系统是推动我国“双碳”目标实施，实现国家能源低碳转型的重要手段之一。为有效提升IES碳减排能力和经济效益水平，提出一种考虑改进阶梯式碳交易机制与需求响应的IES优化调度模型。首先，在能量中心框架下引入碳流模型，促进反应系统中二氧化碳的流动，并改进阶梯式碳交易机制，从而有力推动系统碳减排；其次，引入用户侧的多能需求响应，以价格激励推进用户用能方式转变，促进可再生能源消纳；最后，考虑决策者偏好，以改进碳交易机制为连接点，建立IES低碳经济优化调度模型，以碳排放指标和用户舒适度引导运行调度，并利用CPLEX求解器对IES模型进行求解。进一步，通过5种场景对所提模型和方法进行仿真验证，结果证明了改进碳交易机制、需求响应机制与优化调度模型的配合可有效提高IES的低碳性和经济性。

The integrated energy system （IES） is an important approach to pursue the "dual carbon" target and achieve low-carbon energy transformation of China. In order to facilitate the carbon emission reduction of the IES and improve its economic benefits， an IES optimization scheduling model considering improved stepped carbon trading mechanism and demand response mechanism is proposed. Firstly， a carbon flow model is introduced in the energy hub framework to reflect the flow of carbon dioxide in the system， and an improved stepped carbon trading mechanism is proposed to facilitate carbon reduction of the system. Then， the multi-energy demand response mechanism on user side is introduced to drive the transformation of energy usage pattern motivated by pricing mechanism，so as to promote the consumption of renewable energy. Considering decision maker preference， with the improved stepped carbon trading mechanism as the connection point， a low-carbon IES economic optimization scheduling model is established. The optimization scheduling is guided by the carbon emission index and user comfort， and CPLEX solver is used to solve the scheduling model. The proposed model and mechanisms are verified under five scenarios， whose results prove that the cooperation of the improved carbon trading mechanism， demand response mechanism and optimization scheduling model can effectively lower the carbon emissions and improve the economy of IESs.

为应对未来高比例新能源接入带来的挑战，需充分挖掘不同类型调度资源的可调潜力。为此，提出了一种考虑需求响应的源-荷-储多时间尺度优化调度策略，旨在通过源-荷-储参与电网协同优化调度，提高系统运行的经济性和可靠性。首先，分析了不同类型可调资源的特性，构建了多时间尺度滚动调度总体框架，将整体调度分为日前调度和日内调度2个阶段；其次，基于多场景随机规划方法，建立了以系统总运行成本最小为目标的日前、日内优化调度模型，并在保证系统可靠运行的前提下对模型进行求解；最后，采用改进IEEE-30节点系统进行仿真分析，验证了所提策略的可行性和有效性。

In order to meet the challenges brought by the high proportion of new energy access in the future, it is necessary to fully tap the adjustable potential of different types of scheduling resources. Therefore, a multi-time scale optimal scheduling strategy of source-load-storage considering demand response was proposed to improve the economy and reliability of system operation by participating in the coordinated optimal scheduling of power grid. Firstly, the characteristics of different types of adjustable resources were analyzed, and the overall framework of multi-time scale rolling scheduling was constructed. The overall scheduling was divided into two stages: day-ahead scheduling and intra-day scheduling. Secondly, based on the multi-scenario stochastic programming method, the day-ahead and intra-day optimal scheduling models with the goal of minimizing the total operating cost of the system were established, and the models were solved under the premise of ensuring the reliable operation of the system. Finally, the improved IEEE-30 node system was used for simulation analysis to verify the feasibility and effectiveness of the proposed strategy.