AUTHOR=Liu Shu 

TITLE=Wind power short-term prediction based on digital twin technology

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1365237

DOI=10.3389/fenrg.2024.1365237

ISSN=2296-598X

ABSTRACT=Wind power generation has become an indispensable part of the power supply side of the power grid. Because of the intermittent nature of wind energy, short-term predictions of wind power control to the stable operation of power systems. By constructing the digital twin model, the real-time and highprecision prediction of wind energy is realized. Firstly, GA-SVM algorithm is used to build the model.Multi-dimensional sensors and meteorological stations of the virtual wind power generation system, collect the meteorological data of the environment, and update the meteorological history database at the same time; Secondly, bottomed on the collected meteorological data, the preliminary prediction results are obtained, by searching in the historical database, the predicted value and the actual output value of wind turbine or wind farm under similar conditions are obtained. Finally, the prediction results of the GA-SVM are modified to obtain the predicted value of the digital twin. The prediction method can greatly improve the short-term forecast accuracy of wind energy.