Method for Evaluating and Correcting Power Grid Operating Data Quality Based on Spark Framework

Aiming at the difficulty of quantifying the importance of each evaluation index in power grid operation data quality evaluation, this paper proposes a key index weight calculation model based on analytic hierarchy process and entropy weight method, which distinguishes the importance of different indexes by weight. Aiming at the most prominent data abnormally problem in the evaluation of power grid operation data quality, the paper designs an abnormal data correction model based on RBF neural network under the Spark framework to realize the correction of abnormal data. Finally, the effectiveness of the method is verified by using SCADA data from a provincial dispatch center. The results show that the proposed method can effectively deal with abnormal grid operation data and has practical application value.