Wind power plant power prediction method considering atmospheric disturbance effect

Abstract

The invention relates to a wind power plant power prediction method considering an atmospheric disturbance effect. The method comprises the following steps of regarding an atmosphere nonlinear Lorenz system as a disturbance model, defining atmosphere nonlinear disturbance variables to eliminate nonlinear factors contained in original air speed data, and optimizing the input of a power prediction model, so that the wind power prediction with higher accuracy can be realized. According to the wind power plant power prediction method considering the atmospheric disturbance effect, on the basis of a conventional power prediction method, a power prediction disturbance formula is utilized to carry out nonlinear disturbance correction on a wind speed prediction result, and the influence of some nonlinear disturbance factors existing in original wind speed on the prediction result is eliminated, so that the aim of accurately predicting wind power is achieved. The experiment result shows that according to the method, the prediction accuracy of wind energy can be greatly improved, and the development of wind power industry is greatly promoted.

Description

technical field [0001] The invention relates to a method capable of accurately predicting the wind speed of a wind farm, belonging to the technical field of power generation. Background technique [0002] The development and utilization of new energy is an important way to solve the current global energy shortage and the deterioration of the ecological environment. Wind energy is a clean renewable energy with abundant resources and wide distribution. Wind power generation can realize large-scale and effective utilization of wind energy resources. According to statistics from the Global Wind Energy Association, by the end of 2013, the cumulative installed wind power capacity in the world had reached 318,117MW, an increase of more than five times compared with the statistical data 10 years ago. During the operation of wind farms, wind is one of the most critical meteorological factors affecting power changes. The unique random fluctuation and intermittency of wind energy mak...

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Problems solved by technology

[0004] Most of the existing wind power prediction technologies rely on improving various numerical algorithms to improve the prediction accuracy. At present, there is no prediction method that takes into account the influence of the nonlinear characteristics of the atmospheric system on the power prediction results, so it is impossible to obtain higher wind power prediction results. The prediction accuracy of

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