Analysis Of Ningbo Electric Power Load And Research On The Countermeasures Of Order

At present, Zhejiang province and Ningbo city power shortage situation is grim, the power demand side management is highly valued. Various kinds of power load original demand is the basis of demand side management, but a lot of demand is cannot be observed directly, such as of summer air conditioning load in the county, district and county according to the classification of sales of all types of users to load and cooling load. In order to make good use of the limited power resources, improve the level and effect of power demand side management, this paper has done the relevant research.According to the current situation of power demand side management and the problems faced, this paper makes a research on the domestic and foreign advanced power demand side management cases, to find ways to solve the problem, from the understanding of all kinds of power load characteristics of power load original demand as the breakthrough point, using the scheduling data,2013 and 2014 Ningbo regional electricity sales data, negative control data and the meteorological data, through the actual investigation, classification of load on Load Partition and Ningbo area step temperature air-conditioning load and Ninghai county were analyzed, obtained in 2014 2013, all kinds of original load demand data, through the spring and summer, air conditioning, power load according to time temperature model, the formation of typical curves of load and temperature some typical air conditioning load curve.This paper in the classification of load constitute analysis mainly adopts the statistical inference, clustering analysis, data mining, artificial intelligence method, data preprocessing using SQL Server2000 to establish data warehouse, through the analysis of the data warehouse to realize the analysis model; in the load forecasting mainly adopts the using support vector machine and its related theory, was established based on support vector machine summer short term electric load forecasting model, in order to participate in support vector machine model training.In addition, this paper also studies the correlation between power load and climate and the correlation between electricity and economy, to optimize the industrial structure, load forecast, give full play to the role of social economy of the electric power industry to provide decision-making reference. Finally, according to the research results of the orderly use of electricity countermeasure research, the analysis results in the formation of load characteristic data and gives the county electricity orderly plan formulation to suggest and electricity index utilization of reward and punishment evaluation method.