Power load prediction method for residential user

Abstract

The invention discloses a power load prediction method for a residential user, and aims to solve the problem of relatively tedious operation of making an electrical appliance work plan by the user during participation in power demand response. By adopting a point-to-point multiple method, electric appliances are classified into three types according to an electric appliance usage law; the first type is an electric appliance used in the whole day, and for the electric appliance used in the whole day, the power consumption of the electric appliance in the next day is predicted according to the power consumption per hour of the electric appliance in the first three days; the second type is an electric appliance used irregularly and relatively stable in power, and for the electric appliance used irregularly and relatively stable in power, the usage time of the electric appliance is predicted according to usage records of the user in the same day of the last week and the recent three days; and the third type is an electric appliance relatively great in power change and used irregularly, and for the electric appliance relatively great in power change and used irregularly, the usage time and the power consumption of the electric appliance are predicted according to the usage records of the user in the same day of the last week and the recent three days. According to the method, the usage behaviors and the power consumption of the electric appliances in a user family can be effectively predicted; the method has the characteristics of small required historical data quantity and easy realization; and the workload of making the electric appliance work plan by the user is effectively reduced.

Description

technical field [0001] The invention relates to a method for predicting electric load of residential users. Background technique [0002] As the electricity consumption of residential users increases year by year, the peak-to-valley difference in power load gradually increases, which is not conducive to the economic operation of the power grid. To solve this problem, electricity demand response projects based on time-of-use electricity prices are widely implemented. However, in the process of residential users actively participating in power demand response, formulating electrical work plans is a relatively cumbersome task, which is not conducive to the promotion of demand response load automatic control systems. Therefore, it is necessary to help users formulate electrical work plans through load forecasting to reduce user workload. [0003] Although there have been many studies on load forecasting, these studies are more to provide guidance for power grid operation, focu...

AI Technical Summary

Problems solved by technology

[0003] Although there have been many studies on load forecasting, these studies are more to provide guidance for power grid operation, focusing on improving the accuracy of load forecasting, requiring a large amount of historical load data or weather data as system input, the method is complicated and the calculation is large,...

Images