Research on Identification Methods for Abnormal User Electricity Data in the Electricity Spot Market
A method for identifying abnormal user electricity consumption data in the electricity spot market is proposed to address the issues of unclear mapping of abnormal user electricity consumption data and low identification rate using existing identification methods.By collecting abnormal user electricity consumption data,supplementing and normalizing missing values,calculating the difference between current user electricity consumption data and historical electricity consumption,and then establishing a model to observe the relationship between electricity consumption and system status,obtaining changes in different time periods.Using the non parametric density method to statistically analyze electricity consumption data,extracting daily electricity consumption characteristics,weighted user characteristic curves,and feasible matrices of user electricity consumption data,comparing whether the upper and lower limits of the data curve to be identified are within the feasible range,in order to complete the identification of abnormal data.The results showed that there were significant cases of exceeding the upper and lower limits of the feasible domain when mapping abnormal electricity data to the feasible domain.The experimental group's accuracy in identifying abnormal data was 100%,achieving accurate identification of user abnormal electricity data in the electricity spot market.
electricity spot marketuser electricity consumptionabnormal datainformation collectionidentification model
NETL
NSTL
万方数据
