EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation

Minghao Ran; Jindi Huang; Wuyong Qian; Tingting Zou; Chunyi Ji

doi:10.1016/j.heliyon.2023.e18053

EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation

Heliyon. 2023 Jul 7;9(7):e18053. doi: 10.1016/j.heliyon.2023.e18053. eCollection 2023 Jul.

Authors

Minghao Ran¹, Jindi Huang¹, Wuyong Qian¹, Tingting Zou¹, Chunyi Ji¹

Affiliation

¹ School of Business, Jiangnan University, Wuxi, Jiangsu, 214122, China.

Abstract

Wind power is the most promising renewable energy source after hydropower because of its mature technology and low price, and has great potential for carbon emission reduction. Long-term forecasts of its power generation can help power companies to develop operational plans, grid configuration and power dispatch, and can also provide a basis for the government to formulate energy and environmental policies. However, due to the characteristics of China's monsoon climate and wind power industry development, wind power generation data are characterized by nonlinear cycles and small data volume, which makes accurate prediction more difficult. To this end, this paper develops a new prediction model and applies it to the long-term prediction of wind power generation in China, and proposes some targeted policy recommendations based on the prediction results to promote the development of China's wind power industry.

Keywords: Carbon neutrality; Carbon peaking; Energy forecasting; Renewable energy; Wind power.