DocumentCode
3005427
Title
Forecasting the Global Photovoltaic Market by Using the GM(1,1) Grey Forecasting Method
Author
Huang, Chi-Yo ; Tzeng, Wei-Chang ; Liu, Yu-Wei ; Wang, Po-Yen
Author_Institution
Program of Technol. Manage., Nat. Taiwan Normal Univ., Taipei, Taiwan
fYear
2011
fDate
14-15 April 2011
Firstpage
1
Lastpage
5
Abstract
The solar photovoltaic (PV) technology is the fastest emerging energy technology during the past decade. Precise predictions of the PV market are essential for the governments´ energy policy definitions, firms´ expansion of their production of PV related equipment as well as investors´ decisions regarding to investments in PV related firms. However, an accurate prediction of the PV market is not easy. Since the solar market growth was much slower, predictions of the solar market based on the historical market data from the past decades can be misleading. Further, factors including the oil price, the emergence of other alternative energies, the demand and supply situation of the semiconductor market, etc. can influence the solar market. A suitable solar market prediction method for such a case being characterized by poor information will be very helpful. Due to the nature of the Grey theory for dealing with systems being characterized by poor information or for which information is lacking, the authors developed a GM (1,1) Grey system based forecast mechanism for the global solar market forecast. The empirical study based on a forecast of the year 2002 to 2009 global solar market with the around 5% forecast error has demonstrated the effectiveness of the forecast mechanism. In the future, the GM(1,1) based forecast mechanism can further be applied to the solar and other emerging alternative energy markets.
Keywords
grey systems; photovoltaic power systems; power generation economics; technological forecasting; PV technology; alternative energy market; global solar photovoltaic market prediction method; government energy policy; grey forecasting method; semiconductor market; supply and demand; Industries; Photovoltaic systems; Predictive models; Renewable energy resources; Technology forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Green Technologies Conference (IEEE-Green), 2011 IEEE
Conference_Location
Baton Rouge, LA
Print_ISBN
978-1-61284-713-9
Electronic_ISBN
978-1-61284-714-6
Type
conf
DOI
10.1109/GREEN.2011.5754855
Filename
5754855
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