杨秀, 傅广努, 刘方, 田英杰, 徐耀杰, 柴梓轩. 考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究[J]. 电网技术, 2022, 46(2): 699-708. DOI: 10.13335/j.1000-3673.pst.2021.0268
引用本文: 杨秀, 傅广努, 刘方, 田英杰, 徐耀杰, 柴梓轩. 考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究[J]. 电网技术, 2022, 46(2): 699-708. DOI: 10.13335/j.1000-3673.pst.2021.0268
YANG Xiu, FU Guangnu, LIU Fang, TIAN Yingjie, XU Yaojie, CHAI Zixuan. Potential Evaluation and Control Strategy of Air Conditioning Load Aggregation Response Considering Multiple Factors[J]. Power System Technology, 2022, 46(2): 699-708. DOI: 10.13335/j.1000-3673.pst.2021.0268
Citation: YANG Xiu, FU Guangnu, LIU Fang, TIAN Yingjie, XU Yaojie, CHAI Zixuan. Potential Evaluation and Control Strategy of Air Conditioning Load Aggregation Response Considering Multiple Factors[J]. Power System Technology, 2022, 46(2): 699-708. DOI: 10.13335/j.1000-3673.pst.2021.0268

考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究

Potential Evaluation and Control Strategy of Air Conditioning Load Aggregation Response Considering Multiple Factors

  • 摘要: 空调负荷已成为电力系统重要的需求响应资源,但由于其类型差异性、接入分散性,造成调度中心难以直接获取其聚合功率并开展调度控制,限制了响应潜力发挥。对此,提出考虑空调负荷聚合响应潜力多类型资源协同调度与精准控制相结合的双层调控框架。在日前调度层,基于近似聚合模型获取空调负荷聚合功率,考虑用户热舒适度、意愿度及可控度等多重因素,建立空调负荷聚合响应潜力评估模型,获取其聚合响应潜力,并结合基础柔性负荷响应特性建立联合调度模型,充分挖掘负荷侧多类型资源参与系统调节的潜力;在日内控制层,针对执行降负荷调温控制策略中空调群组功率跌落现象,为引导其有序参与电网需求响应,建立变状态数的状态队列模型,并引入准备时间对参数异质空调集群进行分组控制,使空调负荷跟随调度计划,提升控制精度,缓解功率跌落对系统运行产生的影响。最后,通过某简化配网系统进行仿真分析,结果表明:所提双层调控框架在调度层可深度挖掘并引导利用空调负荷响应潜力,在控制层实现精准控制并削弱功率跌落负面影响,工程应用价值显著。

     

    Abstract: Air conditioning load has become an important demand response resource of a power system. However, due to its different types and decentralized access, it is difficult for the dispatching center to directly obtain its aggregated power and carry out dispatching control, which limits the utilization of its response potential. In view of this, this paper proposes a two-layer regulation framework considering the potential of the aggregated response of the air conditioning load, which combines the cooperative scheduling of the multiple types of the resources with precise control. In the day-ahead scheduling layer, the air conditioning load aggregation power is obtained based on the approximate aggregation model. Considering the users' thermal comfort, intention and controllable degrees and other factors, the air conditioning load aggregation response potential evaluation model is set up to get its aggregation response potential. Combined with the flexible foundation load response characteristics the joint scheduling model is established, fully excavating the adjusting potential of the load side multi-types resources involved in the system. On the day control layer, to perform the load temperature control strategy in the air conditioning group power drop phenomenon and guide the orderly participation in the power grid demand response, the state queue model is set up. Introducing the preparation time for parameters of the heterogeneous cluster grouping control, the air conditioning load follows the scheduling plan, improves the control accuracy, and reduces the impact of falling power on the system running. Finally, a simplified distribution network system simulation analysis is carried out. The results show that the proposed. two-layer control framework can deeply tap and guide the utilization of the air-conditioning load response potential in the scheduling layer and achieve accurate control and reduce the negative impact of power sagging in the control layer, a significant engineering application value.

     

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