Intelligent Perception Analysis of Distribution Systems Based on Data-driven
In order to improve the accuracy of load forecasting for low voltage areas,cluster analysis of the station load based on K-Means++is firstly carried out.Then,a load forecasting model based on minimum redundancy maximum rel-evance method and long short-term memory network is proposed.Based on data mining,the identification of feeder trans-former connectivity and the correction of the station and users relationship are further studied,and the real-time topology acquisition of distribution system is realized.Based on the above,a data sensing method of distribution network state based on decomposition-coordination framework is proposed,which effectively solves the problem that the distribution network is difficult to achieve the observability of the whole network.
intelligent distribution networkload forecastingfeeder transformer connectivitystation and users relation-shipstate estimation
NETL
NSTL
万方数据
