Assessment of energy saving in residential buildings using energy efficiency measures under Cairo climatic conditions

Document Type : Original Article

Authors

1 Mechanical Power Engineering Department, Faculty of Engineering at El-Mattaria, Helwan University, Masaken El-Helmia P.O., Cairo 11718, Egypt.

2 Mechanical Power Engineering Department, Faculty of Engineering at El-Mattaria, Helwan University, Masaken El-Helmia P.O., Cairo 11718, Egypt. . High Institute for Engineering and Technology-Obour, k21 Cairo/Belbies Rd, Egypt.

Abstract

 
This paper investigates the residential building energy needs in Egypt. Firstly, the energy needs of residential building are evaluated in compliance with Energy Efficiency Residential Building Code as a base case. Then, Energy Efficiency Measures (EEMs) defined as measures that reduce energy consumption whilst maintaining the same or better indoor climate conditions are implemented as a modified case using building simulation technique. The considered EEMs include adding thermal insulation to the exterior walls, adding external shading, using lighting fixture with high efficacy and using window glazing type with high thermal and radiation characteristic. Finally, a comparison between the base and modified cases is made.The reported results showed that the thermal cooling demand, heating demand and total electricity demand of the base case are 130 kWh/m2.a, 6.5 kWh/m2a and 114 kWh/m2.a, respectively. It is found that as the overall heat transfer coefficient of external wall decreases from 1.7 W/m2K to 0.58W/m2K causes the cooling and heating demands to decrease by 7% and 60%, respectively. Adding shading with a projection factor of 0.9 for all external windows decreases the cooling demands by 13%. Using double glazing decreases the cooling and heating demands by 14% and 30%, respectively. Installing LED lighting type reduces the annual space cooling demand and electricity consumption by 17% and 26%, respectively. The values of each EEM which are the lowest energy needs, combining to get the optimized case in which the cooling demand, total electricity and the heating demand decrease by 34%, 17% and 11% respectively.