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With the rapid advancement of the Energy Internet strategy, the number ofsensors within the Power Distribution Internet of Things (PD-IoT) has increaseddramatically. In this paper, an edge intelligence-based PD-IoT multi-sourcedata processing and fusion method is proposed to solve the problems ofconfusing storage and insufficient fusion computing performance of multi-sourceheterogeneous distribution data. First, a PD-IoT multi-source data processingand fusion architecture based on edge smart terminals is designed. Second, torealize the uniform conversion of various sensor data sources in thedistribution network in terms of magnitude and order of magnitude. Byintroducing the Box-Cox transform to improve the data offset problem in theZscore normalization process, a multi-source heterogeneous data processingmethod for distribution networks based on the Box-Cox transform Zscore isproposed. Then, the conflicting phenomena of DS inference methods in datasource fusion are optimally handled based on the PCA algorithm. A multi-sourcedata fusion model based on DS inference with conflict optimization isconstructed to ensure the effective fusion of distribution data sources fromdifferent domains. Finally, the effectiveness of the proposed method isverified by an experimental analysis of an IEEE39 node system in a regionaldistribution network in China.

Multi-source data processing and fusion method for power distribution internet of things based on edge intelligence