神经网络故障识别模型在电网设备生产指挥系统中的应用研究

Research on the Application of Neural Network Fault Identification Model in the Production Command System of Power Grid Equipment

随着电力系统复杂性的增加,电网设备的线路故障识别变得越来越重要。因此,文章提出了一种基于神经网络的故障识别模型,并对其在电网设备生产指挥系统中的应用进行了研究,使用神经网络建立故障识别模型,在实际电网设备生产指挥系统中进行了线路故障测试。试验结果表明,该模型在准确率、召回率、系统稳定性、故障预警时间和系统响应时间等方面都优于传统的基于规则的故障识别系统,这说明,神经网络故障识别模型在电网设备生产指挥系统中有显著的应用价值。

With the increasing complexity of the power system,the identification of line faults in power grid equipment has become increasingly important.Therefore,the article proposes an application research of a fault identification model based on neural networks in the production command system of power grid equipment.And a fault identification model was established using neural networks,and line fault testing was conducted in the actual production command system of power grid equipment.The experimental results show that the model outperforms traditional rule-based fault recognition systems in terms of accuracy,recall,system stability,fault warning time,and system response time.This indicates that the neural network fault identification model has significant application value in the production command system of power grid equipment.