A line loss calculation method of a BP neural network optimized by a genetic algorithm

Abstract

The invention relates to a line loss prediction method of a BP neural network optimized by a genetic algorithm, belonging to the technical field of line loss prediction and machine learning of a powernetwork. At first, the method obtains line characteristic parameters through the power network line, and establishes a prediction model of a BP neural network for the characteristic parameters. Then,the individual length is determined according to the weights and thresholds in the topology of BP neural network, and the individual is selected, crossed and mutated by genetic algorithm with real number coding. Finally, the convergence condition is judged and the optimal individual is selected. Then the BP neural network is initialized and trained with the variable learning rate momentum BP algorithm until the network converges. The genetic algorithm is used to optimize the BP neural network algorithm to predict the line loss. The method has the advantages of improved prediction accuracy, less calculation time and enhanced stability. Therefore, the method has certain research significance.

Description

technical field [0001] The invention relates to a line loss calculation method for optimizing a BP neural network with a genetic algorithm, and belongs to the technical fields of power grid line loss prediction and machine learning. Background technique [0002] So far, many theoretical methods for calculating line loss have been proposed in China, such as root mean square current method, average current method, maximum current method, equivalent resistance method, power flow calculation method, etc. However, due to the large number of components, the distribution is complicated and the data is not easy Collection, the workload is too large and difficult to carry out. As a fringe subject, artificial neural network has penetrated into various fields. With a large number of pioneering applications of artificial neural network, some people have also proposed to apply this method to line loss calculation. BP neural network is a multi-layer feed-forward neural network, the main ...

AI Technical Summary

Problems solved by technology

This algorithm is now used for chaotic time series prediction, remote sensing data land cover classification, transformer fault diagnosis, waste incinerator slagging prediction, tourist scenic spot daily passenger flow prediction, gas concentration prediction research, etc., but has not optimized BP neural network with genetic algorithm Method for Predicting and Calculating Line Loss by Network

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