计及需求响应不确定性的综合能源系统协同优化配置

提出了一种计及综合需求响应(IDR)不确定性的综合能源系统(IES)设备优化配置方法。首先,以提高能源利用效率为目标,基于冷/热/电联供系统构建了计及IDR的IES基本结构。然后,采用证据理论对IDR中的随机和认知不确定性进行分析,并利用可信水平约束,优化一定电价方案下的负荷曲线。在此基础上,建立兼顾设备优化配置及运行策略的双层协同规划模型,上层以规划总成本最低为目标进行设备选型和容量配置,下层以运行成本最低为目标优化设备出力。通过比较所有电价方案下的总成本,获得最优电价与设备配置方案。最后,通过算例验证了计及IDR不确定性的优化配置结果对风险的抵御能力更强,且采用证据理论能够实现概率理论和区间理论的统一。

Collaborative Optimal Configuration for Integrated Energy System Considering Uncertainties of Demand Response

This paper proposes a method of equipment optimal configuration for an integrated energy system (IES) considering the uncertainties of integrated demand response (IDR). Firstly, in order to improve the efficiency of energy use, the basic structure of IES considering IDR is constructed based on a combined cooling, heating and power system. Then, the aleatory and epistemic uncertainty of IDR are analyzed by the evidence theory, and the load curve under a certain price scheme is optimized by using a credible level constraint. On this basis, a bi-level collaborative planning model considering the optimal configuration and operation strategy of the equipment in IES is established. In the upper level, the equipment selection and capacity allocation are conducted with the goal of minimizing the total planning cost. And in the lower level, the equipment output is optimized with the lowest operation cost as the objective. By comparing the total costs of all tariff schemes, the optimal tariff and equipment allocation scheme is obtained. Finally, the proposed approach is illustrated on an example and the results demonstrate that the optimal allocation results considering the uncertainties of IDR are more resistant to risks. Meanwhile, evidence theory can be used to achieve the unification of probability theory and interval theory.