Weather sensitive load power estimation method based on nonlinear association model

Abstract

The invention discloses a weather sensitive load power estimation method based on a nonlinear association model. The weather sensitive load power estimation method based on the nonlinear association model comprises the steps of: firstly, pre-processing the load power and the weather data, secondly, forming a longitudinal data sample by adopting the load power and the weather data at same times insimilar days and different months, then, establishing a load-weather nonlinear association model, and finally, identifying model parameters by adopting longitudinal sample data, and calculating the weather sensitive load power in the total load power. According to the weather sensitive load power estimation method based on the nonlinear association model disclosed by the invention, influence of electricity usage habits of users on the load power can be eliminated by adoption of the longitudinal data sample; furthermore, the cumulative effect of the temperature and the sendible temperature areconsidered; the load-weather nonlinear association model is constructed; therefore, the correlation between the load power and the weather factor can be accurately described; and furthermore, the disadvantage that the reference load difference in different seasons is not considered in the traditional method can be effectively avoided.

Description

technical field [0001] The invention belongs to the field of power system load forecasting and load power models, and in particular relates to a method for estimating weather-sensitive load power of a load-weather nonlinear correlation model. Background technique [0002] With the intensification of global warming and the continuous improvement of people's living standards, the power consumption of weather-sensitive loads dominated by air conditioners has been increasing year by year. In 2017, in some areas such as Beijing, air conditioners accounted for more than half of the power consumption in summer. Researching on the estimation of weather-sensitive load power can not only improve the accuracy of the load power model, provide regulation basis for the safe and stable operation of the power grid in summer, but also provide a basis for the evaluation of demand-side response capability, which is of great significance. [0003] At present, on the issue of weather-sensitive l...

AI Technical Summary

Problems solved by technology

However, in reality, due to the complexity and time-varying nature of the load, the summer reference load curve may not be completely consistent with the spring and autumn load curve, which will adversely affect the accuracy of meteorologically sensitive load estimation.

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