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Power grid data intelligent management and application under the background of big data

With the popularization of new technologies such as big data, cloud computing and the Internet of things in the construction of smart grid, power data is showing explosive growth. Traditional power enterprises rely on manpower to collect data and recover arrears. During the period of COVID-19, the closed management of government departments, the arrears of electricity customers and no power outages made the recovery work more difficult. In this paper, through the mining and analysis of customers’ historical payment data, historical electricity and other data, using the deep learning algorithm in the field of artificial intelligence, this paper constructs a mathematical model and formulates the prevention and control strategy of electricity charge recovery risk of business travel alienation. The application results show that the new strategy can effectively reduce the amount of customer arrears and comprehensively improve the lean, digital and intelligent management level of power supply enterprises.