Research On Nonparametric Vine Copula Model Of Dependent Random Variables In Power System Reliability Assessment

With the continuous development of social economy,the power system presents a large-scale,high-interconnect tendency.Reliability assessment can be used to analyze the power supply capability and weakness of power system,and has gradually become an effective tool for planning and operation.There are plenty of uncertainties during the operation of power system,such as wind speed and bus load.Accurately modeling the variation of these uncertainties and establish an effective probabilistic model to improve the accuracy and practicability of reliability assessment is of significant importance.The study is carried out for probabilistic modeling methods considering the randomness/dependence of multiple wind speeds at wind farms and bus loads,and finally they are applied into the power system reliability evaluation.In consideration of the weakness of the current models in dependence modeling of wind speed,a nonparametric canonical/drawable vine Copula model for multiple wind speeds is proposed in this paper.Based on the Copula theory,the marginal distribution and dependence structure of multiple wind speeds are separated.Then,the dependence structure of multiple wind speeds is decomposed based on the pair copula decomposition,which avoids the problem of modeling complexity.Canonical and drawable vines are used to decompose the dependence structure to pair copula,and a non-parametric kernel density estimation method based on probability space transformation is proposed for Copula estimation,which avoids the prior assumption for Copula type the problem that the distribution range of the estimated Copula exceed its feasible domain in traditional non-parametric estimation.In addition,a weight sampling method is proposed for the model to efficiently generate dependent wind speeds.The accuracy and effectiveness of the model is validated by analyzing the RTS79 system with multiple wind farms.Except the wide application of wind power,load is another common uncertainty in power system,and its fluctuation also has an effect on system reliability.Therefore,it is necessary to consider multiple load at the same time.Based on the improvement on the aforementioned model,a nonparametric regular vine Copula model(NRVCM)for multivariate is proposed.The model is more general in terms of decomposition,by which a proper decomposition can be selected according to the dependence between variables.Meanwhile,the model overcomes the dimension hazard problem of the multivariate kernel density estimation technique.Multiple loads and wind speeds are modeled for reliability assessment in modified RBTS and RTS79.The results show that the model can be better applied to the dependence modeling of multivariate,and the necessity to comprehensively consider the dependence between various uncertainties such as loads and wind speeds.