基于近似低秩矩阵补全的配电网负荷缺失数据恢复方法

• Format: Patent
• Language: Chinese
• Published: 08.12.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

本发明公开了基于近似低秩矩阵补全的配电网负荷缺失数据恢复方法，包括以下步骤：S1、负荷历史数据把其分为有数据丢失向量与数据完整向量两类；S2、构成原始矩阵；S3、对缺失的元素进行插值，形成初步恢复矩阵；S4、对初步恢复矩阵求皮尔逊相关系数矩阵，筛选出与数据缺失向量相关性高的向量；S5、把原始含有数据丢失的向量，经皮尔逊相关系数矩阵筛选后的向量；S6、运用奇异值阈值收缩算法对恢复矩阵中的缺失元素进行恢复补全；S7、取出下一条存在数据丢失的向量，重复上述步骤。本发明改进算法相较于传统的低秩矩阵补全算法，取得了更佳的整体恢复效果与稳定性，在补全配电网负荷缺失数据上有更为出色的运用。 The invention discloses a power distribution network load missing data recovery method based on approximate low-rank matrix completion. The power distribution network load missing data recovery methodcomprises the following steps: S1, dividing load historical data into two types including a data loss vector and a data integrity vector; S2, forming an original matrix; S3, performing interpolationon the missing elements to form a preliminary recovery matrix; S4, solving a Pearson correlation coefficient matrix for the preliminary recovery matrix, and screening out a vector with high correlation with a data missing vector; s5, performing Pearson correlation coefficient matrix screening on the original vectors containing data