Dynamic Assessment Combined Model of Power Distribution Operational Risk
There exist two problems in power distribution network operational risks assessment:high expert evaluation subjectivity and invalid data processing.Therefore,this paper presents a distribution network operational risk prediction model based on the dynamic Bayesian network of BP neural network.First,BP neural network group is used to train and test the evaluation properties in order to avoid the high subjectivity in the index weight setting of fuzzy comprehensive evaluation and in the expert evaluation index values.Then the output of multiple BP neural network is fusion processed and the observed data with large differences are excluded.Finally,the time-sliced observed data matrix with missing data is inputted to dynamic Bayesian network with variable structures.The dynamic evolution on time series of the index membership degree is analyzed for the early warning of dynamic evaluation of distribution network operation risk.Finally,the comparison with the fuzzy comprehensive evaluation in the example analysis proves the validity and feasibility of the proposed model.
power distribution operationstructure-variable dynamic bayesian networksrisk warningmissing data
NETL
NSTL
万方数据
维普
