Wind power prediction and power generation

What is wind power prediction?

Wind power prediction involves applying state-of-the-art algorithms to the field of wind power generation so that wind power generation can be better connected to the electricity grid, and key technologies have developed rapidly.

How to forecast wind power generation?

According to different modeling methods, wind power generation forecasting can be divided into physical methods, statistical methods, artificial intelligence methods, and deep learning methods.

When was wind power predicted?

First, in 1984, Brown et al 13 developed a simple time-series based approach by employing utility's power curve for wind power prediction. Since then, a variety of prediction approaches and models have been employed for WF with different success rates.

How to predict wind power output?

The prediction of wind power output is part of the basic work of power grid dispatching and energy distribution. At present, the output power prediction is mainly obtained by fitting and regressing the historical data. The medium- and long-term power prediction results exhibit large deviations due to the uncertainty of wind power generation.

How to improve wind power forecasting accuracy?

(5) WRF based on other initialization times and longer ahead-time. The error transfer mechanism from wind speed forecasting (WSF) to wind power forecasting (WPF) is applied for the improvement of WPF. The forecasting accuracy of short-term WPF is enhanced by correcting NWP data.

Can deep learning predict wind power generation?

In recent years, with the increasing proportion of wind power generation, the impact of wind power generation on grid security is also growing. This makes the prediction accuracy of wind power generation higher and higher. This paper utilizes the LSTM model of the deep learning domain to predict wind power generation.