基于关联分析的城市用电负荷研究

结合电力行业数据的特殊性构建数据库,将关联规则数据挖掘分析方法应用于城市负荷分析中.采用FP-Growth算法对国内48个城市的负荷数据进行挖掘,分析各相关因素对电力负荷的影响,得出了电量及电量增长率与GDP增长率、第二产业比重、中心性等级、行政级别等相关因素的强关联规则.所获得的分析结果符合实际而且能够给出各因素的数值参考范围.

Analysis of Urban Power Load Based on Association Rules

In the light of the characteristics of the data on power load,a database is constructed and the association rules data mining method is applied to the urban power load analysis.The FP-Growth algorithm corresponding to the FP-Tree structure(frequent pattern tree)is then used to analyze the influence of correlative factors on power load through an analysis of the load data on 48 cities in China.The results reveal the relations between annual power consumption and correlative factors such as the GDP growth rate,the proportion of the second industry,the center hierarchy,the executive category of a city,etc.The results agree with practice while giving a specific numerical interval of factors.