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Volumn 35, Issue 7, 2010, Pages 2934-2938

Determining profits for solar energy with remote sensing data

Author keywords

Electricity; Optimal locations; Remote sensing; Solar energy

Indexed keywords

COSTS; ELECTRICITY; OPTIMIZATION; PROFITABILITY; REMOTE SENSING; SOLAR POWER GENERATION; SOLAR RADIATION;

EID: 77956737499     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2010.03.025     Document Type: Article
Times cited : (22)

References (10)
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    • Assessment of solar electricity potentials in North Africa based on satellite data and a geographic information system
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    • (2001) Solar Energy , vol.70 , pp. 1-12
    • Broesamle, H.1    Mannstein, H.2    Schillings, C.3    Trieb, F.4
  • 7
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    • Global aerosol data set. Max Planck Institute for Meteorology, Hamburg, report no. 243
    • Kopke P, Hess M, Schult I, Shettle EP. Global aerosol data set. Max Planck Institute for Meteorology, Hamburg, report no. 243; 1997. Available from <>. http://www.lrz-muenchen.de/%7Euh234an/www/radaer/gads.html.
    • (1997)
    • Kopke, P.1    Hess, M.2    Schult, I.3    Shettle, E.P.4
  • 9
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    • Documentation for the TIMES model: part I
    • Loulou R, Remne U, Kanudia A, Lehtila A, Goldstein G. Documentation for the TIMES model: part I; 2005. Available from <>. http://www.etsap.org/tools.htm.
    • (2005)
    • Loulou, R.1    Remne, U.2    Kanudia, A.3    Lehtila, A.4    Goldstein, G.5
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    • BP. BP statistical review of world energy
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    • (2002)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.