Research On Probabilistic Power Flow Algorithm Considering The Correlation Of Distributed Generation

With the increasing of energy crisis and environmental degradation problems,new energy access based on wind power and photovoltaic has brought more uncertainties to the planning and operation of distribution networks.Traditional deterministic power flow calculations make it difficult to fully include changes with random factors that do not reflect the actual overall operating conditions of the system.Therefore,the introduction of probabilistic power flow comprehensively considers the influence of various uncertain factors on the operational characteristics of the system tidal current,and calculates the probability and statistical information of the node voltage and the branch flow.Besides,related researches show that similar geographical locations and meteorological conditions lead to certain correlation between the output of power stations.If the correlation is neglected,it will bring a big error to the power flow calculation results of the power system.As a result,in order to solve the problem that the traditional three-point estimation method cannot directly deal with the deficiency of the correlation random variables,this paper proposes a probabilistic power flow algorithm that takes into account the correlation of distributed power generation.Based on the traditional Nataf transformation,a polynomial normal is introduced.The correlation of input random variables is quickly decoupled,and then transformed into independent input random variables.Point estimation method and semi-invariant theory are also applied to obtain statistical information and probability distribution of node voltage or branch power.Firstly,by introducing present situation of the research of three types of probabilistic power flow methods,the point estimation method is selected as the basis of the probabilistic power flow calculation.The mathematical research basis of the probabilistic power flow calculation and the related theory of point estimation method are introduced in detail.Then,the probabilistic power flow calculation model with distributed power supply based on point estimation method is established.The wind power and photovoltaic output probability models are given respectively.The IEEE33 node example system is applied to Calculate effectiveness and computational efficiency of probability estimation method of the distributed power supply.Finally,an improved Nataf transform is proposed to process the input random variable correlation and the C-type Gram-Charlier series expansion,and the flow of the probabilistic load flow analysis algorithm considering the distributed power supply correlation is presented.The simulation calculation of the IEEE34 node system is carried out.The results of the proposed method are used to analyze the results of the load-flow correlation and the results of the probabilistic power flow algorithm under the correlation of distributed power output,and the results of the Monte Carlo simulation method are used as reference.The validity and accuracy of the probabilistic power flow algorithm for distributed power generation correlation are compared with the traditional Nataf transform,which verifies the fastness and effectiveness of the improved Nataf transform.The influence of the change of correlation coefficient on the overall operating state of the system is analyzed.The results show that as the correlation degree increases,the probability of the system node voltage exceeding the limit will become larger,and its volatility will be further enhanced,taking into account the correlation of the output.The results of probability estimation can be more accurate.