基于BP神经网络和动态群仿真的电网安全控制系统可靠性试验方法

Qibing Wang, Xin-hui Du, Kai-Lun Zhang, Junjun Pan, Weiguo Yu, Xiaoquan Gao, Rihong Lin
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引用次数: 1

摘要

针对电网安全稳定控制策略动态验证不完善、测试成本高的问题,提出了一种基于BP神经网络和动态群仿真的电网安全控制系统可靠性测试方法。首先,以实时数字仿真系统(RTDS)软件的故障仿真结果为数据源,借助现有调度数据网、无线虚拟专网、全球定位系统等通信资源获得动态测试数据;其次,通过最小冗余最大相关算法选取重要的测试项,将测试项组成特征集,然后利用BP神经网络模型对测试结果进行预测;最后,对动态远程测试平台进行了安全稳定控制系统的动态整群仿真测试。与传统测试方法相比,该方法可将测试成本降低50%以上。实验结果表明,该方法能够有效地完成基于动态群仿真的电网安全控制系统可靠性测试,降低测试成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliability Test Method of Power Grid Security Control System Based on BP Neural Network and Dynamic Group Simulation
Aiming at the problems of imperfect dynamic verification of power grid security and stability control strategy and high test cost, a reliability test method of power grid security control system based on BP neural network and dynamic group simulation is proposed. Firstly, the fault simulation results of real-time digital simulation system (RTDS) software are taken as the data source, and the dynamic test data are obtained with the help of the existing dispatching data network, wireless virtual private network, global positioning system and other communication resources; Secondly, the important test items are selected through the minimum redundancy maximum correlation algorithm, and the test items are used to form a feature set, and then the BP neural network model is used to predict the test results. Finally, the dynamic remote test platform is tested by the dynamic whole group simulation of the security and stability control system. Compared with the traditional test methods, the proposed method reduces the test cost by more than 50%. Experimental results show that the proposed method can effectively complete the reliability test of power grid security control system based on dynamic group simulation, and reduce the test cost.
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