Electric Power System Based On Data Mining Analysis And Application Of Load Density Space

At present, the world’s energy problems are more and more attention, a gradual increase in demand for electricity today, in order to balance the needs of users, a reasonable allocation of power resources, it is necessary to maximize the economic benefits, the supply of electric power distribution system presents graded, space power system load density gradually regularize.Within an area of the grid for rational planning can improve the economics of the power grid, and regional development have a very significant impact.Based on the analysis of data mining technology and space load density, determined the basic spatial load density index, and thus within the area of network planning to provide guidance. This paper first describes the system load density of space research background and significance of the power, and the space density of loads and loads of space were introduced to define the status of the data mining technology and its application for the relevant instructions; describes the common spatial load forecasting methods, including the consumption of industrial output method, electricity elasticity coefficient method, the partition load density, time series method, from a variety of regression models; made a number of specific indicators of spatial load density for different plots, which specific targets are not the same. Gives the space load density forecasting general steps, using data mining techniques in clustering analysis of the data has been pre-treated to an unknown mall, for example, load analysis and forecasting of the space density of the mall, and finally, a brief introduction space load density forecasting in regional power grid planning. The results show that:the use of cluster analysis of data mining methods to establish effective load indicator system that can effectively load density in a region of space or a building to predict, and improve data support network planning.