Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

• Main Authors: Li, Ling Ling, Zhao, Xue, Tseng, Ming Lang, Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2020
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/895; https://animorepository.dlsu.edu.ph/context/faculty_research/article/1894/type/native/viewcontent
• Institution: De La Salle University

© 2019 Elsevier Ltd It is hard to predict wind power with high-precision due to its non-stationary and stochastic nature. The wind power has developed rapidly around the world as a promising renewable energy industry. The uncertainty of wind power brings difficult challenges to the operation of the...