Conference
Identifying Main Factors of Wind Power Generation Based on Principal Component Regression: A Case Study of Xiamen
Abstract
To realize the goals of carbon reduction, it is important for understanding the driving force of the wind power industry. In this study, a principal component regression (PCR) model is employed to identify the main factors of wind power generation in the City of Xiamen. Results disclose that two principal components have a cumulative contribution rate about 95%. The economic component (contributing 81.9%) is dominated by the proportion of …
Authors
Wang B; Liu J; Li Y; Huang G; Wang G
Volume
00
Pagination
pp. 82-85
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
March 6, 2022
DOI
10.1109/icgea54406.2022.9792108
Name of conference
2022 6th International Conference on Green Energy and Applications (ICGEA)