陈璨, 杜维柱, 白恺, 孙贝贝, 孙靓, 付新园, 吴俊勇. 空调温控负荷集群参与光伏消纳的潜力评估与互动框架[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0332
引用本文: 陈璨, 杜维柱, 白恺, 孙贝贝, 孙靓, 付新园, 吴俊勇. 空调温控负荷集群参与光伏消纳的潜力评估与互动框架[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0332
CHEN Can, DU Weizhu, BAI Kai, SUN Beibei, SUN Liang, FU Xinyuan, WU Junyong. Potential Assessment and Interaction Framework of Air Conditioning Thermostatically Controlled Load Cluster Participating in Photovoltaic Consumption[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0332
Citation: CHEN Can, DU Weizhu, BAI Kai, SUN Beibei, SUN Liang, FU Xinyuan, WU Junyong. Potential Assessment and Interaction Framework of Air Conditioning Thermostatically Controlled Load Cluster Participating in Photovoltaic Consumption[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0332

空调温控负荷集群参与光伏消纳的潜力评估与互动框架

Potential Assessment and Interaction Framework of Air Conditioning Thermostatically Controlled Load Cluster Participating in Photovoltaic Consumption

  • 摘要: 空调温控负荷集群作为当下最具调节潜力的需求侧响应资源之一,在削峰、填谷、分布式光伏消纳和电网调控中将发挥重要作用。因此提出了一种电力市场环境下,基于数据驱动和深度置信网络的空调温控负荷集群参与分布式光伏消纳的可调节潜力评估与互动框架。首先,利用数据驱动构建了基于深度置信网络的可调节潜力评估模型,实时输出温控负荷集群的可调节潜力;其次,考虑功率调整量在一定范围内变化的前提下,构建了基于深度置信网络的需求互动模型,对温控负荷集群进行实时温度调控。最后以冀北地区某10kV馈线作为实际算例进行分析,结果表明:所提框架能够充分利用空调温控负荷集群的可调节潜力,参与分布式光伏的消纳。

     

    Abstract: As one of the most potential demand side response resources, air conditioning thermostatically controlled load (abbr. TCL) cluster will play an important role in peak shifting, distributed photovoltaic consumption and power grid regulation. An adjustable potential assessment and interaction framework of air conditioning thermostatically controlled load cluster participating in photovoltaic consumption based on data-driven and Deep Belief Nets (abbr. DBN) is proposed in the power market environment. Firstly, a data-driven adjustable potential assessment model based on Deep Belief Nets is constructed to output the adjustable potential of thermostatically controlled load cluster in real time. Secondly, within the certain range of power adjustment, a demand interaction framework based on Deep Belief Nets is also constructed to regulate the real-time temperature setting of thermostatically controlled load cluster. Finally, taking a 10KV feeder in Northern Hebei as an example, the results show that the proposed framework can make full use of the adjustable potential of the air conditioning thermostatically controlled load cluster, participate in the consumption of distributed photovoltaic, and have high engineering application value.

     

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