Technology Research Of Correlation Of Grid Load Factors Based On The Big Data Theory

One of the most important tasks of power administration is analyzing the grid load, in order to provide a reference for the expansion and reconstruction of the grid. The accuracy of the analysis results will directly affect the economy and security of the power system operation. An accurate power load analysis can help the power generation department to grasp the development trend of power load, provide a guidance for the power gird planning and make a rational decision of the grid operation. It's beneficial to the decrease of the cost of power generation, the economic efficiency of the grid, and the profit of the whole society.The traditional load analysis, to some extent, can describe the change of load, but can't give the influence of load characteristics and meteorological condition of the area. Besides, the relationship between the load and each factor is not able to be presented. Based on the historical operation data and meteorological data of Hebei Southern Grid, Based on the process of big data, the method of data mining is used to find the information hidden behind and the rules of the impact of the load on each meteorological factor in each city of Hebei Southern Grid is summed up in this paper. Firstly, by the analysis of normal load characteristics and the search of association rules, the influence of the temperature, relative humidity, air pressure, wind force and some other meteorological factors on each city is found. Then, in consideration of the climate characteristics of Hebei Southern Grid, the traditional load decomposition model is improved to propose a load decomposition model suitable for the area of Hebei Southern Grid. The relationship model between the weather sensitive load and each meteorological factor is established based on the correlation theory and the regression theory. Finally, the grey correlation theory and the canonical correlation analysis are used for reference to obtain the comprehensive meteorological index, which makes the multiple correlation analysis of the load and various meteorological factors change to a simple Pearson correlation of the load and the comprehensive meteorological index. Compared with the other meteorological factors, the comprehensive meteorological index is proved to be superior.