针对阵地建设安装工程安全风险评估的问题,依据证据推理算法,提出一种阵地建设安装工程安全风险评估方法。将安全风险影响因素逐级分解至指标层,并对指标间的相关关系进行梳理,构建阵地建设安装工程安全风险评估指标体系,根据风险评估结...针对阵地建设安装工程安全风险评估的问题,依据证据推理算法,提出一种阵地建设安装工程安全风险评估方法。将安全风险影响因素逐级分解至指标层,并对指标间的相关关系进行梳理,构建阵地建设安装工程安全风险评估指标体系,根据风险评估结果,运用RIMER(belief rule base inference methodology using evidential reasoning)方法解决底层输入指标类型多样、评估信息不完全问题。实例分析结果表明:该方法具有较好的解释性和可追溯性,对于土建工程和阵地管理中的安全工作具有一定的借鉴意义。展开更多
A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural n...A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural network (GRNN) with incorporation of feature extraction method using principle component analysis. In the risk based security assessment formulation, the failure rate associated to weather condition of each line was used to compute the probability of line outage for a given weather condition and the extent of security violation was represented by a severity function. For low voltage and line overload, continuous severity function was considered due to its ability to zoom in into the effect of near violating contingency. New severity function for voltage collapse using the voltage collapse prediction index was proposed. To reduce the computational burden, a new contingency screening method was proposed using the risk factor so as to select the critical line outages. The risk based security assessment method using GRNN was implemented on a large scale 87-bus power system and the results show that the risk prediction results obtained using GRNN with the incorporation of principal component analysis give better performance in terms of accuracy.展开更多
文摘针对阵地建设安装工程安全风险评估的问题,依据证据推理算法,提出一种阵地建设安装工程安全风险评估方法。将安全风险影响因素逐级分解至指标层,并对指标间的相关关系进行梳理,构建阵地建设安装工程安全风险评估指标体系,根据风险评估结果,运用RIMER(belief rule base inference methodology using evidential reasoning)方法解决底层输入指标类型多样、评估信息不完全问题。实例分析结果表明:该方法具有较好的解释性和可追溯性,对于土建工程和阵地管理中的安全工作具有一定的借鉴意义。
文摘A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural network (GRNN) with incorporation of feature extraction method using principle component analysis. In the risk based security assessment formulation, the failure rate associated to weather condition of each line was used to compute the probability of line outage for a given weather condition and the extent of security violation was represented by a severity function. For low voltage and line overload, continuous severity function was considered due to its ability to zoom in into the effect of near violating contingency. New severity function for voltage collapse using the voltage collapse prediction index was proposed. To reduce the computational burden, a new contingency screening method was proposed using the risk factor so as to select the critical line outages. The risk based security assessment method using GRNN was implemented on a large scale 87-bus power system and the results show that the risk prediction results obtained using GRNN with the incorporation of principal component analysis give better performance in terms of accuracy.
