Research On Probabilistic Power Flow Algorithm Including Distributed Photovoltaic Output Correlation

With the integration of “carbon neutrality” into the overall layout of my country’s ecological civilization construction and the vigorous development of distributed photovoltaic power sources,a large number of photovoltaic power sources continue to penetrate into the rural power distribution network.The randomness and volatility of distributed photovoltaic power have led to the rural power distribution network.The increase in network loss and the over-limit of the voltage affect the safe and stable operation of the rural distribution network.In response to the above problems,based on the connection of photovoltaic power generation to the rural distribution network as the research background,a photovoltaic probability modeling method based on the combination of the uniform conversion method and the adaptive nuclear density estimation method is proposed,and the photovoltaic output and load correlation based on the Nataf transformation are proposed.The probabilistic power flow algorit hm studies the influence of the correlation between photovoltaic output and load on the operation of the distribution network.The main research contents are as follows:Through the existing parameter estimation and non-parametric estimation methods in photovoltaic output power modeling,the traditional method of using fixed bandwidth in the non-parametric kernel density estimation algorithm is too smooth to fit the photovoltaic power probability density curve,and different conditions The fitting ability of actual PV output data is poor,and there is a boundary deviation for actual PV output power data.Aiming at the above problems,a photovoltaic probability modeling method based on the combination of uniform conversion method and adaptive kernel density estimation method is proposed.Compare it with the statistics of other parameter estimation algorithms for goodness of fit test and error analysis.The simulation results show that this method is beneficial to reduce the boundary deviation of traditional nonparametric nuclear density estimation in constructing photovoltaic output models,and it also makes it suitable for photovoltaic power probabilistic modeling under differe nt conditions.The impact of the correlation between photovoltaic output and load on the operating characteristics of rural distribution networks with distributed photovolta ics was studied,and the shortcomings of the traditional Monte Carlo simulation method were explained.The sampling method was not accurate and the calculation was complicated.The photovoltaic output power is modeled by the improved nonparametric kernel density estimation,and the slice sampling algorithm is combined with the Latin hypercube algorithm to slice and sample the model constructed by the improved non-parametric kernel density estimation;then the data obtained by the slice sampling is used as the initial Sample,and then use Latin hypercube sampling to sample the initial sample so that the re-sampled value can cover the entire initial sample space.It can be seen from the simulation results that this method can improve the accuracy of the sampling algorithm in the probability power flow,and can cover the entire sample interval of random variables,which is suitable for the operation analysis of the distribution network with distributed power.Taking into account that the correlation between photovoltaic and load changes in different factors in the rural distribution network,which leads to the problem that the correlation coefficient matrix is indefinite,this paper is based on the Nataf transformation combined with the eigenvalue decomposition method to decompose the non-positive definite correlation coefficient matrix.It overcomes the limitation that the traditional method can only deal with the positive definite correlation coefficient matrix.Through simulation analysis,this method can save a lot of time and has good calculation accuracy.It uses error analysis to quantify and measures the statistica l accuracy of the data calculated by the two methods;and analyzes the differe nt correlation coefficients for the nodes.The influence of voltage,under the simulation of choosing different correlation coefficients,it can be seen that the influence on the voltage of each node is not big,and the standard deviation of the node voltage increases with the increase of the correlation coefficient.