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.

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.

The electricity-heat integrated system can realize the cascade utilization of energy and the coordination and complementarity between multiple energy sources. In this paper, considering the thermal comfort of users, taking into account the difference in dynamic characteristics of electric and heating networks and the response of users’ demands, a dispatch model is constructed. In this model, taking into account the difference in the time scale of electric and thermal dispatching, optimization of the system can be improved by properly extending the thermal balance cycle of the combined heat and power (CHP) unit. Based on the time-of-use electricity prices and heat prices to obtain the optimal energy purchase cost, a user demand response strategy is adopted. Therefore, a minimum economic cost on the energy supply side and a minimum energy purchase cost on the demand side are considered as a bilevel optimization strategy for the operation of the system. Finally, using an IEEE 30 nodes power network and a 31 nodes heating network to form an electricity-heat integrated system, the simulation results show that the optimal thermal balance cycle can maximize the economic benefits on the premise of meeting the users’ thermal comfort and the demand response can effectively realize the wind curtailment and improve the system economy.