Abstract
•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 21,096GWh until 2030. Using a CO2 emission factor of 4.49×10−4metrictons CO2/kWh, the total carbon footprint saving from all power plants is estimated to be 9491,264t of CO2. This work evolves a new forecasting methodology to predict buildings’ cooling energy consumption involving the use of novel cooling technologies.