کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6733378 | 504055 | 2014 | 41 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Big meter data analysis of the energy efficiency potential in Stockholm's building stock
ترجمه فارسی عنوان
تجزیه و تحلیل داده های بزرگ سنجی از پتانسیل بهره وری انرژی در سهام ساختمان استکهلم
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کلمات کلیدی
یکپارچه سازی، اطلاعات بزرگ، برنامه ریزی اقدامات اقلیمی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
The City of Stockholm is making substantial efforts towards meeting its climate change commitments including a GHG emission target of 3Â tonnes per capita by 2020 and making its new eco-district Stockholm Royal Seaport a candidate of Clinton Climate Initiative's Climate Positive Program. Towards achieving these policies, this study evaluated the energy efficiency potential in the city, in collaboration with the district heating and electricity utility Fortum. Drawing on their vast billing meter data on the housing stock in Stockholm, a new understanding of energy use in the city emerged. Analysis of the energy efficiency potential of different building vintages revealed that the retrofitting potential of the building stock to current building codes would reduce heating energy use by one third. In terms of market segmentation, the greatest reduction potential in total energy was found to be for buildings constructed between 1946 and 1975. This is due to the large number of buildings constructed during that era and their poor energy performance. However, the least energy-efficient buildings were those built between 1926 and 1945 in contradiction to commonly held beliefs. These findings indicate the need for a shift in public policy towards the buildings with highest retrofitting potential.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 78, August 2014, Pages 153-164
Journal: Energy and Buildings - Volume 78, August 2014, Pages 153-164
نویسندگان
Hossein Shahrokni, Fabian Levihn, Nils Brandt,