基于改进BP神经网络的10k V配电网线损评估方法

Li-ping Liu, Jianghong Bai, Yi-Tao Zhang, Mu Jiang, Yun-Chao Sun, Qi Wang
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引用次数: 2

摘要

提出了一种基于自适应遗传算法的改进BP神经网络模型,并通过编程实现了10kV配电网线损计算的新方法。首先,根据样品的电特性参数建立特征指标体系;然后,利用改进的bp神经网络模型对训练样本进行学习,得到线损评估模型。在此基础上,可以对测试样品的10kV线路损耗进行实际评估。采用改进的bp神经网络算法拟合线损与电特性参数之间复杂的非线性关系。以实际系统中的10kV配电网为例。仿真和算例验证了所提方法的准确性。与传统的bp神经网络相比,该方法具有收敛速度快、精度高等优点。
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An Evaluation Method of 10k V Distribution Network Line Loss Based on Improved BP Neural Network
A novel method of calculating 10kV distribution network line loss is proposed and realized by programming, which is improved BP neural network model based on adaptive genetic algorithm. Firstly, the characteristic index system is established according to electric characteristic parameters of samples. Then, through leaning the training samples by improved model of BPNN, the line loss evaluation model is obtained. After that,10kV line loss of test samples can be evaluated actually. The improved algorithm of BPNN is adopted to fit complex nonlinear relation between line loss and electric characteristic parameters. The 10kV distribution network in a real system is taken as an example. The accuracy of the proposed method is verified by simulation and calculation of the example. Compared with traditional BPNN, This method has the advantages of fast convergence and high accuracy.
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