An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
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- 作者：Jing Zhaoa ; b ; Zhen-Hai Guoa ; Zhong-Yue Sud ; Zhi-Yuan Zhaod ; Xia Xiaoa ; Feng Liuc ; b ; liuf13@lzu.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Avg. ; Average ; CS ; Cuckoo search ; CS-FS-WRF-E ; Cuckoo Search-Fuzzy System-WRF ensemble ; CS-M-WRF-E ; Cuckoo search-Mean-WRF ensemble ; CST ; China Standard Time ; FS-WRF-E ; Fuzzy System-WRF ensemble ; GFS ; Global Forecast System Model ; MAE ; Mean Absolute Error ; Med. ; Median ; MSE ; Mean Square Error ; M-WRF-E ; Mean-WRF Ensemble ; NWP ; Numerical Weather Prediction ; UTC ; Coordinated Universal Time ; Var. ; Variance ; WRF ; Weather Research and Forecasting
- 刊名：Applied Energy
- 出版年：2016
- 出版时间：15 January 2016
- 年：2016
- 卷：162
- 期：Complete
- 页码：808-826
- 全文大小：6632 K
文摘
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The creative Fuzzy System is used to obtain the feature of WRFs’ outputs.
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This system can reduce the NWP uncertainties and improve the forecasting accuracy.
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The evolutionary algorithm, CS, can correct WRF’s forecasting values.
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This novelty model outperforms other approaches in different wind farms.
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The method is used for operational wind forecast within acceptable computations.