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Volumn 37, Issue 8, 2009, Pages 3268-3273

Conservation vs. renewable energy: Cases studies from Hawaii

Author keywords

Building energy efficiency; Renewable energy; Retrofit

Indexed keywords

BUILDING ENERGY EFFICIENCY; COMMERCIAL BUILDING; ELECTRICITY DEMANDS; ELECTRICITY SAVING; ENERGY EFFICIENT; ENERGY SAVING; FOSSIL FUEL SOURCES; HONOLULU , HAWAII; PAYBACK PERIODS; PHOTOVOLTAIC SYSTEMS; POLICY MAKERS; PV SYSTEM; RENEWABLE ENERGIES; RENEWABLE ENERGY; RETROFIT; RETROFIT PROJECT; STATE GOVERNMENTS;

EID: 65749116370     PISSN: 03014215     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enpol.2009.04.029     Document Type: Article
Times cited : (12)

References (12)
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    • Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
    • Neto A.H., and Fiorelli F.A.S. Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy and Buildings Journal 40 12 (2008) 2169-2176
    • (2008) Energy and Buildings Journal , vol.40 , Issue.12 , pp. 2169-2176
    • Neto, A.H.1    Fiorelli, F.A.S.2
  • 6
    • 0036680550 scopus 로고    scopus 로고
    • A methodology for building energy modeling and calibration in warm climates
    • Pedrini A., Westphal F.S., and Lamberts R. A methodology for building energy modeling and calibration in warm climates. Building and Environment Journal 37 (2002) 903-912
    • (2002) Building and Environment Journal , vol.37 , pp. 903-912
    • Pedrini, A.1    Westphal, F.S.2    Lamberts, R.3
  • 7
    • 0032320621 scopus 로고    scopus 로고
    • Baseline model for utility bill analysis using both weather and non weather related variables
    • Soderegger R.A. Baseline model for utility bill analysis using both weather and non weather related variables. ASHRAE Transactions 104 2 (1998) 859-870
    • (1998) ASHRAE Transactions , vol.104 , Issue.2 , pp. 859-870
    • Soderegger, R.A.1
  • 9
    • 65749114274 scopus 로고    scopus 로고
    • State of Hawaii, DBEDT, 〈http://hawaii.gov/dcca/areas/dca/HCEI/HCEI%20Summary.pdf〉.
    • State of Hawaii, DBEDT, 〈http://hawaii.gov/dcca/areas/dca/HCEI/HCEI%20Summary.pdf〉.
  • 10
    • 52149094335 scopus 로고    scopus 로고
    • Energy saving predictions from building equipment retrofits
    • Yalcintas M. Energy saving predictions from building equipment retrofits. Energy and Buildings Journal 40 12 (2008) 2111-2120
    • (2008) Energy and Buildings Journal , vol.40 , Issue.12 , pp. 2111-2120
    • Yalcintas, M.1
  • 11
    • 34250898707 scopus 로고    scopus 로고
    • An energy benchmarking model based on artificial neural network method utilizing us commercial buildings energy consumption survey (CBECS) database
    • Yalcintas M., and Ozturk A.U. An energy benchmarking model based on artificial neural network method utilizing us commercial buildings energy consumption survey (CBECS) database. International Journal of Energy Research 31 (2007) 412-421
    • (2007) International Journal of Energy Research , vol.31 , pp. 412-421
    • Yalcintas, M.1    Ozturk, A.U.2
  • 12
    • 33751034448 scopus 로고    scopus 로고
    • An energy benchmarking model based on artificial neural network method with a case example for tropical climates
    • Yalcintas M. An energy benchmarking model based on artificial neural network method with a case example for tropical climates. International Journal of Energy Research 30 (2006) 1158-1174
    • (2006) International Journal of Energy Research , vol.30 , pp. 1158-1174
    • Yalcintas, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.