Automatic Identification Method for Abnormal Load in Distributed Power Grid Based on Genetic LM Algorithm
The traditional automatic identification method for abnormal loads in distributed power grids directly classifies the load data without preprocessing,resulting in a high recognition error rate.Propose a distributed power grid abnormal load automatic identification method based on genetic LM algorithm.Firstly,preprocess the collected abnormal load data of the distributed power grid.Secondly,an initial population is generated through genetic algorithm,where each individual corresponds to a parameter combination of power grid load data and abnormal load characteristics.Then,using the local optimization characteristics of the LM algorithm to optimize the combination of power grid data parameters,improving the genetic algorithm,calculating its fitness,and obtaining accurate abnormal classification results of power grid load data.Finally,identify abnormal values of power load.The results indicate that this research method has a lower recognition error rate and practicality.
genetic LM algorithmdistributed power gridabnormal load
NETL
NSTL
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