摘要
综合能源服务是国网近些年主要工作之一,如何利用电网系统现有数据,提升服务质量,是目前亟需解决的问题,文章运用企业所属的行业用电同比增长、运行容量、电压、用电属性、是否高耗能行业及企业用电量增长幅度,结合神经网络算法,建立潜在电能替代企业识别模型,利用模型选取可能性高的企业,进行定向营销,提高营销成功率,实现综合能源主动服务。
Comprehensive energy service is one of the main works of State Grid in recent years.How to use the existing data of power grid system to improve the service quality is a problem that needs to be solved urgently.In this paper,the data of the yearon-year growth of power consumption,operation capacity,voltage,power consumption attribute of the industry,high energy consumption industry or not and the growth rate of power consumption of the enterprise are employed.By using the neural network algorithm,we establish the potential electric energy substitution enterprise identification model.We use the model to select the enterprises with high possibility,carry out directional marketing,improve the success rate of marketing,and realize the comprehensive energy active service.
作者
史焕弘
沈华胄
符煌莹
沈艳阳
Huanhong Shi;huazhou shen;huangying fu;yanyang shen(State Grid Zhejiang Xiangshan power supply company,Ningbo,Zhejiang,315100)
出处
《信息通信》
2020年第3期98-99,共2页
Information & Communications
基金
国网宁波供电公司集体企业项目“综合能源主动服务与客户关系管理方法咨询”。
关键词
综合能源
神经网络
主动服务
Comprehensive energy
Neural network
Active service