Uncertainty analysis method and device for short-term wind power prediction

Abstract

The invention provides an uncertainty analysis method and device for short-term wind power prediction and relates to the technical field of wind farm power prediction. The method includes a step of taking normalized and preprocessed numerical weather forecast data and wind farm single wind turbine power data as an input and an output respectively and training a radial basis neural network model byinput data and output data in a training data set, a step of predicting short-term wind power in the test data set according to the trained radial basis neural network model and generating short-termwind power prediction output data, a step of determining a short-term wind power prediction error according to the short-term wind power prediction output data and test output data in the test data set and establishing a segmented cloud model of a prediction error of each short-term wind power segment, and a step of calculating upper and lower interval limit values of the short-term wind power prediction output data according to the segmented cloud model to be an uncertainty analysis result of short-term wind power prediction.

Description

technical field [0001] The present invention relates to the technical field of wind farm power prediction, in particular to an uncertainty analysis method and device for short-term wind power prediction, in particular to an uncertainty analysis method and device for short-term wind power prediction based on a segmented cloud model. Background technique [0002] Wind power, also known as wind power, is an environmentally friendly energy that is being valued by many countries. At present, the installed capacity of wind power is increasing rapidly, which also has a negative impact on the safety, stability and economic operation of the power system. The important reason is that wind power has random fluctuations and uncertainties, and wind power forecasting is one of the effective methods to deal with random fluctuations and uncertainties. However, wind power forecasting errors are unavoidable, and its accuracy is difficult to reach the level of power system load forecasting ac...

AI Technical Summary

Problems solved by technology

[0004] At present, some achievements have been made in the field of uncertainty research of wind power prediction, but the methods described above still have the following problems: ① The reliability and accuracy need to be further improved; ② The practical performance needs to be improved, such as developing a method that is applicable to The prediction model based on numerical weather prediction is also applicable to the prediction model based on historical data; ③The above existing methods need to assume that the prediction error obeys the Gaussian distribution, but it does not meet the actual situation

Images