Short-term wind power prediction method

Abstract

The invention discloses a short-term wind power prediction method, which comprises the following steps: collecting wind power data, and dividing the wind power data into a training set and a test set; constructing a first fusion model and a second fusion model based on an SVM kernel function and a Stacking ensemble learning algorithm, and training the first fusion model by taking the training set as input to obtain a target training set; inputting the test set into the trained first fusion model to obtain a target test set; and inputting the target training set and the target test set into the second fusion model to obtain a wind power prediction result. According to the method, the output power of the wind power plant is predicted, the uncertainty risk can be reduced, better combined dispatching of the wind power generation system is achieved, and guarantee is provided for safety, stability and electric energy quality of an electric power system.

Description

technical field [0001] The invention belongs to the field of wind power measurement, in particular to a short-term wind power prediction method. Background technique [0002] As energy and environmental issues become increasingly prominent, the research and utilization of renewable energy has become a hot issue of widespread concern to the whole society. As one of the important renewable energy sources that are safe, reliable, pollution-free, do not consume fuel, and can be connected to the grid, wind power has developed rapidly worldwide in recent years. The world's wind power has been developing rapidly since 1990. On February 14, 2018, the Global Wind Energy Council released the 2017 global wind power development statistics: In 2017, the new capacity of the global wind power market exceeded 52.57GW, and the global cumulative capacity reached 539.58GW. In 2017, China's new wind power generation capacity was 19.5GW, accounting for 37% of the world's total new wind power ge...

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Problems solved by technology

[0003] However, wind has the characteristics of uncertainty and non-stationarity, so wind energy is a source of fluctuating electric energy. In the power system, the non-schedulability of wind power generation will pose a threat to the safety and stability of the power system and power quality.

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