Scenario Generation And Probabilistic Load Flow Considering The Correlation Between Clustered Photovoltaic And Wind Power Outptut

The access of clustered photovoltaic power stations and wind farms will bring great challenges to the power system.Scientifically describing and analyzing the uncertainty of the clustered photovoltaic output and wind power output can make the power system effectively avoid operational risks and generate huge economic benefits.Starting from the study of the correlation between clustered photovoltaic output and wind power output,the static scenario generation,dynamic scenario generation and probability flow of the clustered photovoltaic output and wind power output are studied systematically.Firstly,the spatial correlation model between the output of the photovoltaic power station and the output of the wind farm is established.Based on the model,typical static scenarios of photovoltaic and wind power output are generated.The nonparametric kernel density estimation method is used to get the cumulative distribution function of the active output of each wind farm and the output of PV power station respectively.In addition,a single Copula function is used to capture the spatially dependent structure between photovoltaic output and wind power output,and the related parameters of the single Copula function are obtained.Considering the limitation of the single copula function in describing the tail characteristics of the wind power output,the mixed copula function is used to model the actual data of the wind farm.The differences of goodness of fit between a single copula function and the mixed copula function are compared and analyzed in an example.Next,use Monte Carlo sampling technology to generate a large number of samples that meet the spatial correlation of wind power output and the spatial correlation of photovoltaic output.Choose the right number of clusters and use the improved k-means clustering method to generate typical and future scenarios of wind power and photovoltaic output.The typical scenarios are used to the optimal power flow calculation.Secondly,from the perspective of considering time correlation,a dynamic scenario generation method for photovoltaic and wind power output is established.The data set composed of data such as wind speed,light intensity,wind power output,photovoltaic output,etc.,is normalized and the data set is divided into training set and test set.The ELM method is used to make short-term predictions of wind power and photovoltaic output.Based on the generation of prediction values of photovoltaic and wind power output,the linear quantile regression method is used to generate marginal distributions at each forecast time section.Finally,the probabilistic power flow calculation based on Nataf transformation theory for wind farms and photovoltaic power station is improved.Nataf transformation is a special case of the Normal Copula function.The difficulty of Nataf transformation lies in the transformation of the random variable's correlation coefficient matrix in the primitive space and normal space.For a random variable with a certain correlation coefficient that does not obey the common probability distribution,this paper uses the double Gauss-Hermite integral and Newton difference method to obtain the correlation coefficients of the random variables in the standard normal space.The probability distribution models for long-term and short-term output of wind farms,and the photovoltaic output are established.The probability distributions of system node voltage and branch flow under different installed capacity of wind farms,different wind speed correlation coefficient and the possible broken line are compared and analyzed by multi schemes.There are also changes in system losses under different PV power stations,which provide important reference for the safe and stable operation of the actual power system.The changes of loss under different photovoltaic incorporation locations provide important reference for the safe and stable operation of the actual power system.This paper uses the idea of the 'scenario',starting from the point of analyzing the correlation of stochastic variables to generate static scenarios and dynamic scenarios for photovoltaic and wind power output respectively.The last chapter calculates the probabilistic power flow based on the static scenarios.