TY - JOUR
T1 - Research of a combined wind speed model based on multi-objective ant lion optimization algorithm
AU - An, Yining
AU - Wang, Jianzhou
AU - Lu, Haiyan
AU - Zhao, Weigang
N1 - Publisher Copyright:
© 2021 John Wiley & Sons Ltd.
PY - 2021/12
Y1 - 2021/12
N2 - In the past few decades, wind power generation has gradually become an important source in the global energy market, which effectively meets the energy demand of human production activities. However, the instability and diffusion of wind speed bring difficulties to the wind energy development and promotion. For improving the predictive accuracy of original sequence, scholars have proposed a variety of prediction models, but many current forecasting models often neglect the importance of data processing and can be easily limited by a single model, which causes poor performances. Therefore, a combined model is built that mainly includes the complete ensemble empirical mode decomposition with adaptive noise, several single models, and multi-objective ant lion optimization algorithm. This combined model not only reduces the impact of high-frequency noise, but also extracts original sequences features as much as possible, combines the advantages of multiple single models, and greatly improves forecasting accuracy and stability.
AB - In the past few decades, wind power generation has gradually become an important source in the global energy market, which effectively meets the energy demand of human production activities. However, the instability and diffusion of wind speed bring difficulties to the wind energy development and promotion. For improving the predictive accuracy of original sequence, scholars have proposed a variety of prediction models, but many current forecasting models often neglect the importance of data processing and can be easily limited by a single model, which causes poor performances. Therefore, a combined model is built that mainly includes the complete ensemble empirical mode decomposition with adaptive noise, several single models, and multi-objective ant lion optimization algorithm. This combined model not only reduces the impact of high-frequency noise, but also extracts original sequences features as much as possible, combines the advantages of multiple single models, and greatly improves forecasting accuracy and stability.
UR - http://www.scopus.com/inward/record.url?scp=85118864801&partnerID=8YFLogxK
U2 - 10.1002/2050-7038.13189
DO - 10.1002/2050-7038.13189
M3 - Article
AN - SCOPUS:85118864801
SN - 1430-144X
VL - 31
JO - International Transactions on Electrical Energy Systems
JF - International Transactions on Electrical Energy Systems
IS - 12
M1 - e13189
ER -