基于网络传播特性的配电网电压暂降随机预估方法

敏感负荷的大量投运使得用户对电能质量的要求不断提高,电压暂降的快速有效预估成为当前电压暂降研究的一项重要内容。提出了一种基于网络传播特性的配电网电压暂降随机预估方法。首先基于配电网拓扑搜索电压暂降传播路径,通过序分量法获得不同路径下电压暂降的垂直/水平传播特性。进而根据路径搜索结果建立故障源至负荷侧的配电网电压暂降传播方程。最后结合不同故障类型及线路故障率计算暂降凹陷域和相应预估指标。对某实例配电网系统开展算例分析,验证了所提方法的有效性与优越性。     

WB-KNN for emotion recognition from physiological signals

K-nearest neighbor (KNN) has yielded excellent performance in physiological signals based on emotion recognition. But there are still some issues:the majority vote only by the nearest neighbors is too simple to deal with complex (like skewed) class distribution; features with the same contribution to the similarity will degrade the classification accuracy; samples in boundaries between classes are easily misclassified when k is larger. Therefore, we propose an improved KNN algorithm called WB-KNN, which takes into account the weight (both features and classification) and boundaries between classes. Firstly, a novel weighting method based on the distance and farthest neighbors named WDF is proposed to weight the classification, which improves the voting accuracy by making the nearer neighbors contribute more to the classification and using the farthest neighbors to reduce the weight of non-target class. Secondly, feature weight is introduced into the distance formula, so that the significant features contribute more to the similarity than noisy or irrelevant features. Thirdly, a voting classifier is adopted in order to overcome the weakness of KNN in boundaries between classes by combining different classifiers. Results of WB-KNN algorithm are encouraging compared with the traditional KNN and other classification algorithms on the physiological dataset with a skewed class distribution. Classification accuracy for 29 participants achieves 94.219 2% for the recognition of four emotions.     

杂散电容对电容式电压互感器测量误差的影响

电容式电压互感器(capacitor voltage transformer,CVT)测量谐波的精度受补偿电抗器杂散电容的影响较大。通过对补偿电抗器杂散电容物理特性的分析,建立等效电路模型,以及对CVT谐波传递特性的分析计算,利用MATLAB/Simulink仿真软件,研究了杂散电容在不同范围内波动时对CVT各次谐波的传变误差的影响。仿真结果表明:不同杂散电容在相同范围内波动时,数值越大的杂散电容对CVT的传递特性影响越大。     

基于最小幅值搜索的电压暂降监测点优化配置

为实现全网任意位置电压暂降可观测,提出一种基于最小幅值搜索的电压暂降监测点优化配置方法。首先根据电压暂降幅值解析式,利用黄金分割法搜索故障位置在各线路变化时节点的最小暂降幅值;进而根据电压阈值确立可观测域,构建出计及各种短路故障情形的最恶劣可观测矩阵。最后以系统内监测点数目最少为目标,全网任意位置电压暂降可观测为约束,建立电压暂降监测点优化配置模型。在构造电压暂降可观测矩阵的计算中,考虑了系统最恶劣电压暂降情形,避免了监测盲区。并且通过对IEEE 30节点系统的仿真计算证明了该方法的有效性。     

杂散电容对CVT谐波测量影响的处理方法研究

电容式电压互感器(CVT)在用于谐波电压测量时受杂散电容的影响较大。通过对杂散电容的变化特点的分析,利用CVT的等效电路,本文提出了一种由输入输出传变关系的数据映射,在杂散电容可能的变化区间内,依据数理统计理论,以测量数据置信度为优化条件,校正误差最小为优化目标的数学处理方法确定杂散电容参数的优化组合,从而实现对谐波电压校正测量的方法,并通过实际案例的验证分析证明了方法的合理性和有效性。