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Energy Sources, Part B: Economics, Planning, and Policy Volume 3, 2008 - Issue 4
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Original Articles

Analysis of Time-varying Turbulence in Geographically-dispersed Wind Energy Markets

B. T. Ewing Rawls College of Business & Wind Science and Engineering Research Center, Texas Tech University, Lubbock, Texas, USA
,
J. B. Kruse Center for Natural Hazards Research, East Carolina University, Greenville, North Carolina, USA
&
M. A. Thompson Hull College of Business, Augusta State University, Augusta, Georgia, USA
Pages 340-347 | Published online: 26 Sep 2008

Citations (11)

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Read on this site (3)

Heping Liu, Jing Shi & Ergin Erdem. (2013) An Integrated Wind Power Forecasting Methodology: Interval Estimation Of Wind Speed, Operation Probability Of Wind Turbine, And Conditional Expected Wind Power Output Of A Wind Farm. International Journal of Green Energy 10:2, pages 151-176.
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J.E. Payne & B. Carroll. (2009) Modeling Wind Speed and Time-varying Turbulence in Geographically Dispersed Wind Energy Markets in China. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 31:19, pages 1759-1769.
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J.E. Payne. (2009) Further Evidence on Modeling Wind Speed and Time-Varying Turbulence. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 31:13, pages 1194-1203.
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Articles from other publishers (8)

Lingyun Liu, Jianli Zhou, Haoxin Dong, Yao Tao, Yunna Wu & Yang Wang. (2020) Investment Risk Assessment of Dispersed Wind Power in Low Wind Speed Area Using a Hybrid Multi-Criteria Decision-Making Approach Based on Hesitant Fuzzy Linguistic Environment. Mathematical Problems in Engineering 2020, pages 1-23.
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Huaiwei Sun, Dong Yan, Na Zhao & Jianzhong Zhou. (2015) Empirical investigation on modeling solar radiation series with ARMA–GARCH models. Energy Conversion and Management 92, pages 385-395.
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Xuejun Chen, Shiqiang Jin, Shanshan Qin & Laping Li. (2015) Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search. Mathematical Problems in Engineering 2015, pages 1-18.
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Ergin Erdem, Jing Shi & Ying She. 2014. International Congress on Energy Efficiency and Energy Related Materials (ENEFM2013). International Congress on Energy Efficiency and Energy Related Materials (ENEFM2013) 65 73 .
Heping Liu, Jing Shi & Xiuli Qu. (2013) Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines. Energy Conversion and Management 67, pages 8-17.
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Beth Andrews. (2012) RANK-BASED ESTIMATION FOR GARCH PROCESSES. Econometric Theory 28:5, pages 1037-1064.
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Qing Cao, Bradley T. Ewing & Mark A. Thompson. (2012) Forecasting wind speed with recurrent neural networks. European Journal of Operational Research 221:1, pages 148-154.
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Heping Liu, Ergin Erdem & Jing Shi. (2011) Comprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed. Applied Energy 88:3, pages 724-732.
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