The Calculation Of Probabilistic Power Flow Considering Multiple Balance Points And The Improvement Of Its Output Distribution

There are many uncertainties in power system,especially with the increasing permeability of renewable energy,such as solar power generation,wind power generation and so on,and the uncertainty of power system is further enhanced.Probabilistic load flow calculation is an algorithm which can take into account the influence of many uncertain factors in the power system.It uses probability distribution characteristics to describe the random characteristics of output variables vividly,which is more consistent with the actual operation and further satisfies the system prediction and planning.In this paper,the probabilistic load flow considering a variety of input random variables is taken as the research object,and the methods of combining cumulant method with many approximate methods are used to calculate the probabilistic load flow,and on the basis of the conventional load flow model,The multi-balanced bus load flow model is introduced into probabilistic load flow calculation.The probability distribution model of input random variables and probabilistic load flow model are established.in this paper,the input random variables are considered and their related probability distribution models are determined according to the actual operation and related data.The probability distribution characteristic of the output random variable of the probability load flow calculated by the method of the saddle point approximation is introduced.The Cumulant Method combine with Cornish-Fisher series expansion(CMCF)?Cumulant Method combine with Gram-Charlier series expansion(CMGC)? Monte Carlo method(MC)are compared.The effectiveness and accuracy of the Cumulant Method combine with Saddle Point approximation(CMSP)are verified by an example.At the same time,the effect of different random variables in the power system is verified.The results of the example show that the CMSP algorithm is more accurate than the CMGC and CMCF.The influence of different random variables on the power system is verified by changing the input random variables and using the CMSP to calculate the probabilistic load flow.The numerical results show that adding random variables of photovoltaic and wind power generation output on the basis of random load can increase the average voltage amplitude of most nodes of the system by a small range.Especially,the closer the node to the node with random variables,the greater the fluctuation of voltage amplitude and the larger the increase of voltage amplitude.On the basis of the calculation of the probability flow of the normal load flow model,a multi-balanced bus load flow model is proposed,and the sensitivity matrix is corrected.By using the CMSP to calculate the probability load flow,the rationality and practicability of the model are verified,and the feasibility,validity and calculation accuracy of the CMSP algorithm in the probabilistic load flow calculation based on the model are also verified.The results of the example show that the multi-balanced bus load flow model can make the power output range of the generator at the balance bus more reasonable and meet the actual operation condition,and the CMSP algorithm is feasible and effective in the multi-balanced bus probability load flow calculation,and the calculation accuracy is high.