Probability forecasting method and system for wind power

Abstract

The invention provides a probability forecasting method and system for wind power, and the method comprises the steps: extracting a wind speed sample from a pre-established wind speed probability density function model, inputting the wind speed sample into a pre-established wind speed and wind power conversion model, and obtaining the sample data of the wind power; performing kernel density estimation on the sample data of the wind power to obtain a kernel density estimation fitting probability density function of the wind power; and based on the kernel density estimation fitting probability density function, extracting a probability forecasting result from a preset confidence interval. The method comprises the following steps: extracting a wind speed sample from a pre-established wind speed probability density function model and inputting the wind speed sample into a pre-established wind speed-wind power conversion model; according to the method, the weather uncertainty information provided by the ensemble forecasting is fully utilized, the continuous probability density distribution function reflecting the wind power uncertainty can be provided, and the accuracy of the probability forecasting result is effectively improved by utilizing the set confidence interval.

Description

technical field [0001] The invention relates to the field of new energy power generation, in particular to a method and system for probabilistic forecasting of wind power. Background technique [0002] Wind energy resources have the characteristics of volatility and intermittency, and it is difficult to predict them accurately. When considering wind power variables in the power market and power dispatching, it is necessary to consider its uncertainty distribution to make more reasonable decisions, thereby improving economic benefits. Improve the safety factor. The uncertainty of numerical weather prediction data is an important factor causing the uncertainty of wind power forecasting. The ensemble numerical weather prediction service provides information containing the uncertainty of weather forecast factors from the perspective of NWP data production mechanism. This information is determined by multiple In practical applications, due to the huge production and calculation ...

AI Technical Summary

Problems solved by technology

The uncertainty of numerical weather prediction data is an important factor causing the uncertainty of wind power forecasting. The ensemble numerical weather prediction service provides information containing the uncertainty of weather forecast factors from the perspective of NWP data production mechanism. This information is determined by multiple In practical applications, due to the huge production and calculation costs of ensemble forecasts and the limited number of ensemble members, compared with complex weather systems, the ability to directly describe the probabilistic forecast results is very limited

Images