With the increasing scale of distributed generator supplied in the distribution network

it is of great significance to take into account the uncertain factors seriously and make a refined budget in planning. A planning method of distribution transformer considering its life cycle cost and the uncertainty output of photovoltaic generation is proposed. Firstly

Cholesky decomposition method is used to remove the correlation of historical data in each of the random variables. Secondly

the probability distribution of photovoltaic and load is determined by the modeling method of nonparametric kernel density estimation. At the same time

a method is presented to select the appropriate capacity of transformer risks based on the chance constraint theory. And then the three-point estimation method is proposed to calculate the probability flow of the distribution network. Finally

an uncertainty distribution transformer planning model based on life cycle theory is constructed and solved by the particle swarm optimization algorithm. The example shows the method proposed in this paper is reasonable. The simulation results show that it can effectively compensate for the boundary in capacity and model selection of distribution transformer. The life cost cycle of the distribution transformer has been made more refined

improving the economy of the distribution planning.