Real-time Predictive Method for Intelligent Monitoring and Management of Distributed Power Access

Currently, existing predictive methods are difficult to adapt to increasingly complex distributed power access and consumption, owing to the rapid growth of distributed accessing power grid scale and the uncertainty of time and space in new energy generation, such as poverty-alleviating photovoltaic (PV) and wind energy. In this paper, a real-time predictive method for intelligent monitoring and management of distributed power access is proposed. Firstly, the Voronoi algorithm is employed to divide the substation power supply area. Then, distributed power saturation is divided into four levels according to the penetration value associated with time matching of the network source and the under-construction capacity. Finally, the distributed power real-time intelligent warning method based on image processing is proposed. And the feasibility of this method was verified through two examples. This innovative partitioning method can overcome the shortcomings of the existing warning methods. Moreover, under the current situation of large-scale photovoltaic poverty alleviation in China, this method also can achieve coordinated optimization between distributed power supply and differentiated regional grid.