KMS Of Academy of mathematics and systems sciences, CAS
| Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information | |
| Heng, Jiani1; Hong, Yongmiao1,2; Hu, Jianming3; Wang, Shouyang1,2 | |
| 2022-01-15 | |
| Source Publication | APPLIED ENERGY
 |
| ISSN | 0306-2619 |
| Volume | 306Pages:13 |
| Abstract | As the proportion of the total installed wind capacity continues to increase, precise probabilistic and deterministic wind speed forecasting becoming increasingly significant for wind turbine stable function and operation management. It is worth noting that except for the intermittent nature of wind speed itself, the site dependence of wind energy and the heterogeneous nature of the distribution at different locations can also affect the results of wind speed forecasting. Considering this has often been overlooked in previous studies, this study attempts to introduce characteristic information of wind from wind farms into wind speed probabilistic forecasting. For the sake of acquiring a more rational descriptive statistical interpretation of wind speed, a variety of probability density functions for actual wind speed data are evaluated in this study. And then, Generalized Gaussian Process models are constructed via observation likelihood functions which are determined by obtained probability density functions. Beyond that, to enhance the robustness against model misspecification, a pseudo-likelihood for the Leave-One-Out cross-validation methodology is proposed for approximating the posterior in the Bayesian inference stage. Wind speed forecasts on 6-hour-ahead horizons from two wind farms in China illustrated that the appropriate mining of wind prior statistical characteristic information can contribute to improving the precision of probabilistic wind speed forecasting. |
| Keyword | Probabilistic and deterministic wind speed forecasting Wind characteristic information Probability density functions Generalized Gaussian process Pseudo-Likelihood |
| DOI | 10.1016/j.apenergy.2021.118029 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[71988101] ; National Natural Science Foundation of China[7210031644] ; National Natural Science Foundation of China[71701053] |
| WOS Research Area | Energy & Fuels ; Engineering |
| WOS Subject | Energy & Fuels ; Engineering, Chemical |
| WOS ID | WOS:000711972000002 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/59496 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Wang, Shouyang |
| Affiliation | 1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 3.Guangzhou Univ, Sch Econ & Stat, Guangzhou 510000, Peoples R China |
| Recommended Citation GB/T 7714 | Heng, Jiani,Hong, Yongmiao,Hu, Jianming,et al. Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information[J]. APPLIED ENERGY,2022,306:13. |
| APA | Heng, Jiani,Hong, Yongmiao,Hu, Jianming,&Wang, Shouyang.(2022).Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information.APPLIED ENERGY,306,13. |
| MLA | Heng, Jiani,et al."Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information".APPLIED ENERGY 306(2022):13. |
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