Intelligent evaluation of cable harmonic loss based on CSO-BP neural network

doi:10.3969/j.issn.1674-1951.2021.08.006

Abstract

Abstract:

Researches on the harmonic loss of cable lines at home and abroad are mainly based on electromagnetic physical analysis. The correction of equivalent parameters mostly relies on empirical formulas, and the accuracy is inadequate. In order to accurately evaluate the cable harmonic loss, an intelligent loss evaluation model based on crisscross optimization algorithm optimized-back propagation （CSO-BP） neural network is proposed. Generally, cable lines under the influence of harmonics are of various harmonic orders, different proportions of varied orders and multiple influencing factors on training samples. In order to overcome the shortages of the traditional BP algorithm such as slow convergence and being easy to fall into local optimum, BP neural network is optimized by CSO algorithm which can search better. After the optimization, an intelligent evaluation model for cable harmonic loss based on CSO-BP neural network is obtained. The values calculated by this model, traditional BP model and physical formulas are compared. The simulation results show that the cable harmonic loss calculated by CSO-BP neural network based intelligent evaluation model is closer to the actual value. The model is of accuracy and stability.

Key words: cable, loss, harmonic, BP neural network, CSO algorithm

CLC Number:

TM726:TP183

CHEN De, MENG Anbo, CAI Yongfeng. Intelligent evaluation of cable harmonic loss based on CSO-BP neural network[J]. Huadian Technology, 2021, 43(8): 41-47.

Figures/Tables 4

References 22

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