基于卷积神经网络的电力系统暂态稳定预防控制方法  

A preventive control method of power system transient stability based on a convolutional neural network

作　　者：田芳 周孝信 史东宇 陈勇 黄彦浩 于之虹 TIAN Fang;ZHOU Xiaoxin;SHI Dongyu;CHEN Yong;HUANG Yanhao;YU Zhihong(State Key Laboratory of Power Grid Safety and Energy Conservation(China Electric Power Research Institute),Beijing 100192,China)

机构地区：[1]电网安全与节能国家重点实验室(中国电力科学研究院有限公司),北京100192

出　　处：《电力系统保护与控制》2020年第18期1-8,共8页Power System Protection and Control

基　　金：国家重点研发计划项目资助(5442XT180029)。

摘　　要：为了更好地实现电力系统暂态稳定预防控制,提出了基于卷积神经网络(Convolutional Neural Network,CNN)的电力系统暂态稳定预防控制方法。通过CNN模型输出变量灵敏度选择控制发电机并确定控制量,然后采用CNN和时域仿真相结合的暂态稳定评估方法进行控制方案校核,得到使系统在预想故障下稳定的控制方案。采用某省级电网算例进行预防控制效果验证。结果表明,采用所提出的预防控制方法,可以找到使系统恢复稳定的预防控制策略。A preventive control method of power system transient stability based on a Convolutional Neural Network(CNN)is presented to better realize the control.The sensitivities of the CNN output variable are calculated to select control generators and determine the control amount,and the corresponding control scheme is verified by the transient stability assessment method based on the CNN combined with time-domain simulation to obtain the control scheme.This can stabilize the system under anticipated contingencies.A particular provincial power grid is analyzed to verify the effectiveness of the method.The results reveal that effective control measures are obtained with the proposed CNN-based transient stability preventive control method,and they can restore the system to a stable state.

关 键 词：卷积神经网络 电力系统 暂态稳定 预防控制 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TM712[自动化与计算机技术—控制科学与工程]