董杰, 宋利明, 黄赟鹏, 陈志敏, 林丽娟, 贾清泉. 含高比例光伏配电网电压安全性数字孪生预警方法[J]. 现代电力, 2023, 40(2): 170-181. DOI: 10.19725/j.cnki.1007-2322.2021.0261
引用本文: 董杰, 宋利明, 黄赟鹏, 陈志敏, 林丽娟, 贾清泉. 含高比例光伏配电网电压安全性数字孪生预警方法[J]. 现代电力, 2023, 40(2): 170-181. DOI: 10.19725/j.cnki.1007-2322.2021.0261
DONG Jie, SONG Liming, HUANG Yunpeng, CHEN Zhimin, LIN Lijuan, JIA Qingquan. A Digital Twin Warning Method for Voltage Security of Distribution Network Containing High Proportion of Photovoltaic[J]. Modern Electric Power, 2023, 40(2): 170-181. DOI: 10.19725/j.cnki.1007-2322.2021.0261
Citation: DONG Jie, SONG Liming, HUANG Yunpeng, CHEN Zhimin, LIN Lijuan, JIA Qingquan. A Digital Twin Warning Method for Voltage Security of Distribution Network Containing High Proportion of Photovoltaic[J]. Modern Electric Power, 2023, 40(2): 170-181. DOI: 10.19725/j.cnki.1007-2322.2021.0261

含高比例光伏配电网电压安全性数字孪生预警方法

A Digital Twin Warning Method for Voltage Security of Distribution Network Containing High Proportion of Photovoltaic

  • 摘要: 光伏的随机不确定性易引起配电网电压越限,而同时光伏又具有电压主动支撑能力,对电压影响产生一定的自消作用。因而,含高比例光伏的新型配电系统电压安全问题日益复杂。因此提出一种新型配电网数字孪生电压安全分析和预警方法。首先论述了孪生配电网电压安全预警的实现机理和功能方案,并基于运行数据建立配电网源荷随机行为的马尔科夫模型,提出不确定场景下电压越限风险评判指标。然后采用吉布斯算法对源荷马尔科夫模型进行蒙特卡洛随机抽样,根据配电网当前的运行状态,利用孪生配电网超实时计算能力快速仿真配电网未来随机场景,并计算电压风险指标,评判电压安全性。最后应用算例分析验证了所提分析方法的有效性及合理性。

     

    Abstract: In distribution network the random uncertainty of photovoltaic (abbr. PV) easily leads to the voltage out-of-limit, however at the same time PV possesses active voltage supporting capacity to take a certain self-elimination effect on the affection of voltage, therefore the voltage security of the new-type distribution system containing high proportion of PV becomes more and more complicated. For this reason, a new type of digital twin voltage security analysis and early warning method for new type of distribution network was proposed. Firstly, the realization mechanism and functional scheme for voltage security warning in twin distribution network twins were expounded and based on operating data an Markov model of random behavior of sources and loads in distribution network was established, and the voltage out-of-limit risk evaluation indices under uncertain scenario was proposed. Secondly, the Gibbs algorithm was utilized to perform Monte Carlo random sampling for sources and loads in distribution network and according to current operating state of the distribution network and by use of ultra-real-time computing capacity of the digital twins, the afterward random scenes of the distribution network was quickly simulated and the voltage risk index was computed to evaluate the voltage security. Finally, by means of calculating example the effectiveness and reasonableness of the proposed analysis method is verified.

     

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