Autonomous operation domain generation and reduction method supporting the seamless power supply of important loads

Jinhui Zhou, Ke Wang, Jiabei Ge, Xu Xu, Hongmin Wu
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Abstract

In order to fully and accurately perceive the security risks of the intelligent distribution network, an autonomous operation domain generation and reduction method to support the seamless power supply of important loads is proposed. This method first adopts the scenario analysis method to analyze the photovoltaic uncertainty, introduces the micro-phasor measurement units (µPMU) with real-time, synchronization, accuracy, and comprehensive measurement data, and builds the fault data set through the scenario of each fault type occurring in each node of the smart distribution network. By constructing the load loss risk index of the autonomous operation domain under the photovoltaic scenario and the seamless switching ability index under the fault state, the autonomous operation domain evaluation and screening method based on the Dynamic Time Warping (DTW) algorithm is proposed. Combined with the evaluation index system, the autonomous operation domain scenario under the fault state is evaluated. The simulation results prove that this method is enough to realize the reliable screening of the autonomous operation domain scene set in the fault state, and effectively support the seamless power supply of important loads and the seamless operation of the distribution network.
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支持重要负载无缝供电的自主运行域生成和缩减方法
为了全面、准确地感知智能配电网的安全风险,提出了一种支持重要负荷无缝供电的自主运行域生成与还原方法。该方法首先采用情景分析法对光伏不确定性进行分析,引入具有实时性、同步性、准确性和测量数据全面性的微脉冲测量单元(μPMU),通过智能配电网各节点各故障类型发生的情景,建立故障数据集。通过构建光伏场景下自主运行域的负荷损耗风险指标和故障状态下的无缝切换能力指标,提出了基于动态时间扭曲(DTW)算法的自主运行域评估筛选方法。结合评价指标体系,对故障状态下的自主运行域场景进行评价。仿真结果证明,该方法足以实现故障状态下自主运行域场景集的可靠筛选,有效支持重要负荷的无缝供电和配电网的无缝运行。
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