Abstract
At present, due to the fact that large-scale distributed photovoltaics can access distribution networks and that there is a mismatch between load demand and photovoltaic output time, it is difficult for traditional distributed photovoltaic planning to meet the partition-based control of high permeability photovoltaic grid-connected operations. As a solution to this problem, this paper proposes a planning method for photovoltaic storage partitions. First of all, a partitioning method for electrical distance modularity based on voltage/active power and voltage/reactive power is presented, along with a modified AP-TD-K-medoids trilevel clustering algorithm that was designed to cluster and partition the distribution network. In addition, according to the partitioning results, a bilevel co-ordination planning model for distributed photovoltaic storage was developed. The upper level aimed to minimize the annual comprehensive cost for which the decision variables are the photovoltaic capacity, energy storage capacity, and power of each partition. The lower level aimed to minimize system network losses, and the decision variables for this are the photovoltaic installation capacity and energy storage installation location of the intrapartition node. Finally, we adopted the particle swarm algorithm with bilevel iterative adaptive weight to solve the planning model, and the simulation was carried out on the distribution system of the IEEE33 nodes. The results show the rationality of the model and the effectiveness of the solution method.