Forecasting long-term electricity demand for cooling of Singapore's buildings incorporating an innovative air-conditioning technology

Seung Jin Oh, Kim Choon Ng, Thu Kyaw, Wongee Chun, Kian Jon Ernest Chua

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)183-193
Number of pages11
JournalEnergy and Buildings
Volume127
DOIs
Publication statusPublished - Sep 1 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Forecasting long-term electricity demand for cooling of Singapore's buildings incorporating an innovative air-conditioning technology'. Together they form a unique fingerprint.

  • Cite this