Ascertainment of Photovoltaic System Generation Access Capacity Based on Probabilistic Power Flow and Improved Genetic Algorithm

In recent years with the distributed generation (DG) technology like photovoltaic system generation (PVS) widely applied, some system problems such as voltage exceeding is gradually remarkable. The PVS access node and capacity will influence the voltage exceeding probability. In order to make full use of PVS and make sure the voltage exceeding probability limit within a certain range to ensure the power quality, the suitable PVS access node and capacity is needed. Base on this, the objective function and its constraint conditions of the suitable PVS access node and capacity are established. This problem becomes a nonlinear combinatorial optimization problem. This paper use improved genetic algorithm to solve this problem. And the solution of voltage exceeding probability uses the combined Cumulants and the Gram-Charlier expansion method.