基于非参数核密度估计的电力市场用户电量异常数据辨识与修正方法
摘要：随着我国电力现货市场的逐步推进，电力市场中的交易结算环节对电力市场用户电量数据的准确度提出了更高的要求。首先，为解决由于计量装置等问题造成的分时电量数据缺失与异常，采取非参数核密度估计(kernel density estimation，KDE)的方法，对窗宽进行优化选取，根据电力市场用户的历史电量数据提取其日分时电量特征曲线。其次，将提取的特征曲线结合历史电量所蕴含的信息得到用户电量数据的可行域矩阵，并将其应用于异常数据的辨识中。再次，根据异常数据区间用电量大小对特征曲线进行缩放处理后的数据作为连续缺点数据修正值。最后，利用某省电力市场用户的计量电量数据，对所提方法的有效性和准确性进行了验证。结果表明所提方法能够有效地处理异常数据，和其他方法相比较，该文方法在连续多点电量数据异常的修正过程中准确度最高，具有实际应用价值。
Abstract:With the gradual development of electricity spot markets in China, the settlement link of transactions in electricity market makes a higher request for the accuracy of power users’ electricity consumption data. Firstly, to cope with the deficiency and abnormity of time-of-use type of electrical quantity data caused by metering device and so on, the nonparametric kernel density estimation (KDE) method was adopted to optimally select the window width, and according to the historical electric quantity data of users in electricity market their daily time-of-use type of electrical quantity characteristic curves was extracted. Secondly, combining the extracted characteristic curves with the information contained in the historical electric quantity, the feasible domain matrix of users’ electric quantity data was obtained and applied to the identification of abnormal data. Thirdly, according to the magnitude of consumed electric quantity of the abnormal data interval, the data from scaled characteristic curves was taken as the modification value of continuous defective data. Finally, the effectiveness and veracity of the proposed method were verified by use of the data of the metered electric quantity of the consumers in the electricity market of a certain province. The results of the computing example show that the abnormal data can be effectively processed by the proposed method, and comparing with other methods, the proposed method possesses the highest accuracy in the correction process of continuous multi-point electric quantity data anomalies, thus the proposed method could apply in practice.
标题：基于非参数核密度估计的电力市场用户电量异常数据辨识与修正方法
英文标题：An Identification and Correction Method of Abnormal Data of Electricity Market Consumers Based on Nonparametric Kernel Density Estimation
作者：严明辉, 潘舒宸, 吴滇宁, 崔雪, 卢少平, 赵俊,
关键词：核密度估计(KDE), 电力现货市场, 电量异常数据, 辨识与修正,
发表日期：2022-01-10
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