基于CSO-BP神经网络的电缆谐波损耗智能评估

doi:10.3969/j.issn.1674-1951.2021.08.006

摘要/Abstract

摘要：

国内外对于电缆线路谐波损耗的研究主要是通过电磁物理分析进行计算,等值参数的修正多依赖经验公式,精度方面有所欠缺。为准确评估电缆线路的谐波损耗,提出一种基于纵横交叉优化（CSO）算法-反向传播（BP）神经网络的损耗智能评估模型。谐波影响下的电缆线路普遍是谐波次数多样且各次含有率不定,训练样本的影响因素众多,为了克服传统的BP神经网络算法收敛速度慢、容易陷入局部最优的缺点,使用搜索能力更强的CSO算法优化BP神经网络,得到基于CSO-BP神经网络的电缆线路谐波损耗智能评估模型。将该模型的损耗评估值、传统BP模型评估值以及物理公式法计算值进行对比,仿真结果表明,基于CSO-BP神经网络的电缆谐波损耗智能评估模型得出的结果与实际值更为接近,具有较高的准确性和稳定性。

关键词: 电缆, 损耗, 谐波, 反向传递神经网络, 纵横交叉优化算法

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

中图分类号:

TM726:TP183

陈德, 孟安波, 蔡涌烽. 基于CSO-BP神经网络的电缆谐波损耗智能评估[J]. 华电技术, 2021, 43(8): 41-47.

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.

图/表 4

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