Paper Conference
2018 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA
 
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An Intelligent Knowledge-Based Energy Retrofit Recommendation System for Residential Buildings at an Urban Scale
Usman Ali, Mohammad Haris Shamsi, Cathal Hoare, Eleni Mangina, James O'DonnellUniversity College Dublin, IrelandAbstract: Buildings play a significant role in driving the urban demand and supply of energy. Research conducted in the urban buildings sector indicates that there is a considerable potential to achieve significant reductions in energy consumption and greenhouse gas emissions. These reductions are possible through retrofitting existing buildings into more efficient and sustainable buildings. Building retrofitting poses a huge challenge for owners and city planners because they usually lack expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper proposes a new methodology based on machine learning algorithms to develop an intelligent knowledge-based recommendation system which has the ability to recommend energy retrofit measures. The proposed methodology is based on the following four steps: archetypes development, knowledge-base development, recommendation system development and building retrofitting or performance analysis. A case study of Irish buildings dataset shows that the proposed system can provide effective energy retrofits recommendation and improve building energy performance. Pages: 84 - 91 Paper:simbuild2018_C013