학술논문
Short-term wind power forecast based on Long Short Term Memory
Document Type
Conference
Author
Source
2023 9th International Conference on Computer and Communications (ICCC) Computer and Communications (ICCC), 2023 9th International Conference on. :2555-2559 Dec, 2023
Subject
Language
ISSN
2837-7109
Abstract
As the impact of climate change on the environment increases, the demand for new energy sources is growing. In the development of renewable energy, wind power generation is an important technology that can use wind energy to generate electricity. However, due to its unstable nature, the forecasting of wind power generation has become one of the most important problems in wind farm management. In this paper, historical wind power data is selected as input to establish a wind power prediction model based on Long Short Term Memory (LSTM). By training LSTM model, the prediction of wind power in next 12 hours is realized. Result shows that the model has certain feasibility and accuracy, can accurately predict the future short-term wind power generation, and has a wide range of application value.