Multi-source fusion of distribution network operation data containing new energy sources based on joint Kalman filtering

At present, the constraint mechanism of multi-source fusion of distribution network operation data containing new energy is generally set as a single form, and the data fusion efficiency is low, resulting in an increase in the average absolute percentage error. Therefore, the design and analysis of multi-source fusion method of distribution network operation data containing new energy based on joint Kalman filter is proposed. According to the current measurement, first collect the characteristics of distribution network operation data, set up multi-source data fusion levels, adopt a multi-level approach, improve the overall efficiency of data fusion, and build a multi-level constraint mechanism. On this basis, a multi-source fusion model of distribution network operation data with new energy based on joint Kalman filter is constructed, and multisource data fusion is realized by mapping auxiliary processing. The final test results show that the average absolute percentage errors of the four randomly selected test areas within the coverage of H distribution network are well controlled below 1.2 after three cycles of measurement, which indicates that the designed multi-source fusion method of new energy distribution network operation data is more reliable and efficient with the help of the joint Kalman filter technology, The degree of data fusion is high, targeted, and has practical application value.