Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model
This article analyzes and assesses the potential for wind energy exploitation in six regions of Vietnam. The wind speed data are used to construct wind speed probability distributions (WSPDs) based on kernel density estimation (KDE). The KDE distribution, with six bandwidth selection methods, is im...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Can Tho University Publisher
2024-10-01
|
| Series: | CTU Journal of Innovation and Sustainable Development |
| Subjects: | |
| Online Access: | https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/1134 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850123303695417344 |
|---|---|
| author | Tin Trung Chau Tuan Ngoc Nguyen Ton Duc Do |
| author_facet | Tin Trung Chau Tuan Ngoc Nguyen Ton Duc Do |
| author_sort | Tin Trung Chau |
| collection | DOAJ |
| description |
This article analyzes and assesses the potential for wind energy exploitation in six regions of Vietnam. The wind speed data are used to construct wind speed probability distributions (WSPDs) based on kernel density estimation (KDE). The KDE distribution, with six bandwidth selection methods, is implemented to generate probability density functions (PDFs) for each region's data to describe wind speed characteristics. The statistical tests Cramér-Von Mises (CvM), Anderson-Darling (A-D), and Kolmogorov-Smirnov (K-S) are applied to evaluate the PDFs' goodness-of-fit performance. The analysis results present the KDE distribution using the least-squares cross-validation (LSCV), and the Scott bandwidth selection method has outstanding fitting performance. Based on these PDF distributions, the wind turbine (WT) power curve is used to estimate and predict the amount of electricity that can be produced. This study also proposes a reliable method for wind power output planning based on wind speed that can be universally applied.
|
| format | Article |
| id | doaj-art-a9deb43a4c2449a8a99b7d8d2edd9ff5 |
| institution | OA Journals |
| issn | 2588-1418 2815-6412 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Can Tho University Publisher |
| record_format | Article |
| series | CTU Journal of Innovation and Sustainable Development |
| spelling | doaj-art-a9deb43a4c2449a8a99b7d8d2edd9ff52025-08-20T02:34:38ZengCan Tho University PublisherCTU Journal of Innovation and Sustainable Development2588-14182815-64122024-10-0116Special issue: ISDS10.22144/ctujoisd.2024.319Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation modelTin Trung Chau0Tuan Ngoc Nguyen1Ton Duc Do2a:1:{s:5:"en_US";s:27:"SEDS, Nazabaryev University";}Facuty of Information Technology, University of Economics Ho Chi Minh City - Vinh Long Campus, Viet NamDepartment of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan This article analyzes and assesses the potential for wind energy exploitation in six regions of Vietnam. The wind speed data are used to construct wind speed probability distributions (WSPDs) based on kernel density estimation (KDE). The KDE distribution, with six bandwidth selection methods, is implemented to generate probability density functions (PDFs) for each region's data to describe wind speed characteristics. The statistical tests Cramér-Von Mises (CvM), Anderson-Darling (A-D), and Kolmogorov-Smirnov (K-S) are applied to evaluate the PDFs' goodness-of-fit performance. The analysis results present the KDE distribution using the least-squares cross-validation (LSCV), and the Scott bandwidth selection method has outstanding fitting performance. Based on these PDF distributions, the wind turbine (WT) power curve is used to estimate and predict the amount of electricity that can be produced. This study also proposes a reliable method for wind power output planning based on wind speed that can be universally applied. https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/1134Bandwidth selection, kernel density estimation, non-parametric distribution, wind energy, wind speed distribution |
| spellingShingle | Tin Trung Chau Tuan Ngoc Nguyen Ton Duc Do Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model CTU Journal of Innovation and Sustainable Development Bandwidth selection, kernel density estimation, non-parametric distribution, wind energy, wind speed distribution |
| title | Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model |
| title_full | Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model |
| title_fullStr | Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model |
| title_full_unstemmed | Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model |
| title_short | Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model |
| title_sort | assessing wind energy exploitation potential in several regions of viet nam using kernel density estimation model |
| topic | Bandwidth selection, kernel density estimation, non-parametric distribution, wind energy, wind speed distribution |
| url | https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/1134 |
| work_keys_str_mv | AT tintrungchau assessingwindenergyexploitationpotentialinseveralregionsofvietnamusingkerneldensityestimationmodel AT tuanngocnguyen assessingwindenergyexploitationpotentialinseveralregionsofvietnamusingkerneldensityestimationmodel AT tonducdo assessingwindenergyexploitationpotentialinseveralregionsofvietnamusingkerneldensityestimationmodel |