A Review of Modern Wind Power Generation Forecasting Technologies

Abstract

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. In order to meet the demand for accessing large-scale wind power into the electricity grid and to further improve the accuracy of short-term wind power prediction, it is necessary to develop models for accurate and precise short-term wind power prediction based on advanced algorithms for studying the output power of a wind power generation system. This paper summarizes the contribution of the current advanced wind power forecasting technology and delineates the key advantages and disadvantages of various wind power forecasting models. These models have different forecasting capabilities, update the weights of each model in real time, improve the comprehensive forecasting capability of the model, and have good application prospects in wind power generation forecasting. Furthermore, the case studies and examples in the literature for accurately predicting ultra-short-term and short-term wind power generation with uncertainty and randomness are reviewed and analyzed. Finally, we present prospects for future studies that can serve as useful directions for other researchers planning to conduct similar experiments and investigations.

Selecting the Best Permanent Magnet Synchronous Machine Design for Use in a Small Wind Turbine

“…Advancements in wind power-generation technologies are crucial for grid dispatching and energy distribution. Artificial intelligence techniques such as artificial neural networks (ANN) and support-vector machines (SVMs) have been widely used in wind energy forecasting [6,7]. The development of accurate and precise short-term wind power prediction models based on these advanced algorithms is necessary to accommodate large-scale wind power into the electricity grid.…”

Review of AI-Based Wind Prediction within Recent Three Years: 2021–2023

“…Many methods have been proposed for WSP/WPP, which can be classified into several groups according to different classification criteria [9], as shown in Figure 2. According to the time scale [10], they are divided into ultra-short-term (a few seconds to 30 min ahead), short-term (30 min to 6 h ahead), medium-term (6 h to 1 day ahead) and long-term (1 day to 1 week or more ahead) models [11][12][13]. This classification reflects a focus on the time span of predictions and provides more specific time frameworks for different application scenarios.…”

A Multi-Type Dynamic Response Control Strategy for Energy Consumption

“…In light of the comprehensive, in-depth implementation of the dual-carbon plan, it can be observed that the development of power systems has been focused primarily on the advancement of new energy development, the significant improvement of energy utilization efficiency, and the optimization and upgrading of the energy consumption structure. Nevertheless, the year-on-year growth of new energy installed capacity and the comprehensive grid connection of large-scale regional new energy stations, as evidenced in the literature [1][2][3], indicate that the stochasticity and volatility of new energy outputs are gradually becoming a significant threat to system stability. Furthermore, the literature [4][5][6] the phenomenon of wind and light being abandoned.…”