Abstract
Saudi Arabia has high per capita electricity usage, amounting to around 9000 kWh/year. The residential sector accounts for almost 52% of the total national electricity consumption and the energy demand from it is expected to double by 2025. The associated environmental and economic pressures advocate for an improvement in energy consumption patterns by means of energy efficiency strategies. Currently, sustainable measures including energy conservation are not among the priorities of the building sector stakeholders such as architects, investors, developers and contractors. For a sustainable built environment, the conventional design process has to be modified and building energy modeling (BEM) needs to be incorporated in it from the early stages. This study measures the energy and environmental savings achievable through incorporating BEM in decision making from an early stage of the design process. An industry survey is carried out to determine the current scope of BEM and to figure out the concerned technical and non-technical barriers restricting industry professionals from using BEM in Saudi Arabia's residential building designs. Possible solutions are discussed to overcome these barriers. Energy and environmental advantages are measured in the residential sector by comparing an existing residential villa energy consumption and simulating it into different scenarios with energy efficient design solutions.
Original language | English |
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Title of host publication | 2017 5th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 309-314 |
Number of pages | 6 |
ISBN (Electronic) | 9781538617755 |
DOIs | |
State | Published - 27 Sep 2017 |
Publication series
Name | 2017 5th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2017 |
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Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- building energy modeling
- design process
- energy efficiency
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Artificial Intelligence
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering