基于灰色关联分析及BP算法的用电量预测  

Forecasting of electricity consumption based on grey correlation analysis and the BP algorithm

作　　者：荆红莉[1] 周艳萍[1] 蒋晓雁[1] 

机构地区：[1]榆林学院能源工程学院,榆林719000

出　　处：《国外电子测量技术》2017年第12期109-112,共4页Foreign Electronic Measurement Technology

摘　　要：用电量是电力系统规划及地区资源配置的重要影响因素,为了提高用电量预测的精度,提出将灰色关联分析法与BP神经网络相结合进行用电量预测。利用灰色关联分析法对影响用电量的主要因素进行分析,确定了3个影响因素并将其作为BP网络的输入参数,建立了用电量BP神经网络预测模型;在MATLAB环境下对模型进行训练测试,结果表明该系统收敛速度快、预测精度高,可为用电量的预测提供参考方法。The use of electricity is an important factor in the planning of the power system and the allocation of regional resources to improve the accuracy of the forecast. in this paper, the grey correlation analysis method combined with BP neural network is used to the analysis of electricity consumption forecast. First, using the grey correlation analysis meth- od to analyze the main factors influencing the electricity consumption, through the correlation coefficient to determine the main factors influencing the power consumption; second , the identified three influence factors as the input parameters of BP network to establish the model of f electricity consumption prediction model . through the application of model test, the results show that the method has faster convergence speed and higher prediction accuracy, can be used as a reference method for prediction of power.

关 键 词：灰色关联分析 BP神经网络 用电量预测 

分 类 号：TM74[电气工程—电力系统及自动化]