کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
261973 504007 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting long-term electricity demand for cooling of Singapore’s buildings incorporating an innovative air-conditioning technology
ترجمه فارسی عنوان
پیش بینی تقاضای برق درازمدت برای خنک سازی ساختمان های سنگاپور با استفاده از تکنولوژی تهویه مطبوع نوآورانه
کلمات کلیدی
تهویه مطبوع، خنک کننده محدوده فن آوری خنک کننده رمان، مدل پیش بینی برق، رد پای کربن
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی


• Long-term electricity usage forecasting model for cooling Singapore’s buildings includes top-down and bottom-up approaches.
• A novel system integrating adsorbent dehumidifier and evaporative cooler was proposed for a high energy conservative scenario.
• Electricity demand for buildings’ cooling accounted for 31 ± 2% of the total electricity consumption in Singapore.
• The high conservative scenario forecasted the best potential of electricity saving of 21,096 GWh until 2030.
• The total carbon footprint reduction from all power plants was estimated to be 9,491,264 metric tons of CO2.

In an effort to accurately plan for investment on energy production and distribution, this paper proposes a long-term electricity consumption forecasting model for buildings’ cooling by employing a high energy conservative scenario. The key aspect of the high energy conservative scenario is to adopt an innovative adsorbent-based dehumidifier and an indirect evaporative cooling (AD-IEC) technology as opposed to conventional mechanical vapor compression system. Bottom-up equations were developed to identify the cooling load and electricity consumption of both residential and non-residential buildings for the period 2002–2013. Based on the time-series electricity consumption, a multiple linear regression model is developed to forecast electricity demand for the future period of 2014–2030. It is found that the electricity demands for cooling in the building sectors account for 31 ± 2% of the total electricity consumption in Singapore, This study concluded that the high conservative scenario realizes the best potential of electricity saving of 21,096 GWh until 2030. Using a CO2 emission factor of 4.49 × 10−4 metric tons CO2/kWh, the total carbon footprint saving from all power plants is estimated to be 9491,264 t of CO2. This work evolves a new forecasting methodology to predict buildings’ cooling energy consumption involving the use of novel cooling technologies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 127, 1 September 2016, Pages 183–193
نویسندگان
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