Wind Power Forecasting Based on Prophet Model

• Published in: 2022 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia) pp. 1544 - 1548
• Main Authors: Zheng, Yahan, Liu, Yize, Jiang, Zhaojun, Tang, Qingwei, Xiang, Yue
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08-07-2022
• Subjects: Data models; Machine learning algorithms; Neural networks; Predictive models; Prophet; the long short-term memory neural network forecasting model; Time series analysis; wind power forecasting; Wind power generation
• DOI: 10.1109/ICPSAsia55496.2022.9949918

In order to improve the accuracy of wind power forecasting, a wind power time series forecasting model based on Prophet al-gorithm is established. The wind power data of a region from 2018 to 2020 are used for forecasting, and compared with the long short- term memory neural network forecasting model to explore the feasibility of the model in wind power forecasting.