电容式电压互感器（capacitor voltage transformer, CVT）是高压电网中广泛使用的测量设备，对CVT的内绝缘状态进行实时在线评估将有助于维护电力系统的安全稳定。但现有基于群体关联性的CVT内绝缘状态在线评估方法未考虑一次电压波动影响，导致评估结果可靠性不够高。针对这个问题，提出了一种计及一次电压波动影响的CVT内绝缘状态在线评估方法，该方法以CVT群体间的内在关联性和主成分分析方法对群体的输出信号进行特征提取，以排除一次电压波动的影响，得到表征CVT内绝缘异常的特征信息，再采用随机森林方法对该特征信息进行分析，实现CVT内绝缘状态的实时在线评估。实验分析表明，该方法可有效消除一次电压波动对CVT内绝缘状态在线评估的影响，实现CVT内绝缘状态的准确评估。
英文摘要:
Capacitive voltage transformer (CVT) are widely used measurement equipment in high-voltage power grids. Real-time online assessment of the internal insulation state of CVT will help maintain the safety and stability of power systems. However, the existing online assessment methods of CVT internal insulation state based on group correlation do not consider the influence of primary voltage fluctuations, resulting in insufficient reliability of the assessment results. Aiming at this problem, an on-line evaluation method of CVT internal insulation state considering the influence of primary voltage fluctuation is proposed. This method uses the intrinsic correlation between CVT populations and principal component analysis method to extract features from the output signals of the population to exclude the primary voltage fluctuation, and the characteristic information that characterizes the insulation anomaly in the CVT is obtained. And then, the random forest method is used to analyze the characteristic information to realize the real-time online assessment of the CVT internal insulation state. The experimental analysis shows that this method can effectively eliminate the influence of primary voltage fluctuation on the online evaluation of the CVT internal insulation state, and realize the accurate evaluation of the CVT internal insulation state.