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人工神经网络和短时仿真结合的暂态安全评估事故筛选方法
引用本文:顾雪平,曹绍杰,张文勤.人工神经网络和短时仿真结合的暂态安全评估事故筛选方法[J].电力系统自动化,1999,23(8):16-19,26.
作者姓名:顾雪平  曹绍杰  张文勤
作者单位:1. 华北电力大学电力工程系,071003,保定
2. 香港城市大学智能设计、自动化及制造研究中心,香港九龙
摘    要:结合人工神经网络(ANN)和短时数字仿真提出一个用于在线暂态安全评估的事故筛选方法,将3层BP网络作为模式分类器,用来建立稳定评估结果和所选特征量之间的映射关系,在故障切除时刻终止的短时数字仿真被用来生成ANN的输入量,每个ANN处理一个特定的事故状态,使用一个半监督学习算法,ANN可产生一个能够指示相对稳定度的连续分布的暂态稳定指标,基于这个连续分布的稳定指标,设置一个相对保守的分类门槛值,避免

关 键 词:电力系统  暂态稳定  神经网络  安全评估  事故筛选

INTEGRATION OF ANNS AND SHORT-DURATION NUMERICAL SIMULATION FOR CONTINGENCY SCREENING OF TRANSIENT SECURITY ASSESSMENT
Gu Xueping,S K Tso,Zhang Wenqing.INTEGRATION OF ANNS AND SHORT-DURATION NUMERICAL SIMULATION FOR CONTINGENCY SCREENING OF TRANSIENT SECURITY ASSESSMENT[J].Automation of Electric Power Systems,1999,23(8):16-19,26.
Authors:Gu Xueping  S K Tso  Zhang Wenqing
Abstract:Integration of short-duration numerical simulation techniques and artificial neural networks is investigated for application to contingency screening of dynamic security assessment. In the proposed approach, the back-propagation neural networks are employed to assess transient stability of power systems. The short-duration numerical simulation is employed to produce the input atributes to the ANNs. Each ANN is designed to handle a single contingency scenario. The ANN can derive a continuous-spread stability index to indicate the relative stability degree by means of a semi-supervised learning algorithm. Based on the stability index, a conservative classification threshold is set to avoid omission of insecure cases. Applications to the 10-unit New England Power System demonstrate the validity of the proposed approach.
Keywords:power  systems  transient  stability  neural  networks  security  assessment  contingency  screening
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