Modelling and Application of Electricity Marketing Tariff Risk Prediction Driven by New Forms of Distribution Networks

doi:10.11930/j.issn.1004-9649.202101015

Abstract

Abstract: In the era of big data, digital transformation is being carried out for electric power companies. The role of distribution network would shift from satisfying basic load requirements to providing customers with personalized solutions, proposing high requirements for electricity marketing services. Electricity fee management has long become the main evaluation indicator for marketing quality services. The goal of this work is to build a universal model of tariff risk prediction based on big data techs and provincial features. In this regard, the risk of tariff and the operation costs would be controlled.

Key words: distribution network, digital transformation, risk of electricity charge recovery, machine learning

DAI Luping, QU Qing, HUANG Lu, PAN Ye. Modelling and Application of Electricity Marketing Tariff Risk Prediction Driven by New Forms of Distribution Networks[J]. Electric Power, 2021, 54(8): 98-102.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202101015

https://www.electricpower.com.cn/EN/Y2021/V54/I8/98

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