Automatic Identification Method of Substation Household Change Relationship Based on BiLSTM-TCNN
Traditional recognition methods extract data feature s in a sequential manner during the classification process,which leads to significant errors in the recognition results of substation household relationships.Therefore,a BiLSTM-TCNN based automatic recognition method for substation household relationships is proposed.Using remote centralized meter reading to obtain electricity consumption data of substation users,preprocessing the original data as sample data,constructing a parallel structured classification model composed of BiLSTM and TCNN,inputting the sample data into the model,and outputting the automatic recognition results of substation user relationship after training.The results indicate that the Pearson correlation coefficient value for identifying the household variation relationship in the substation area using this design method is 0.98,confirming that the method has high recognition accuracy.
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