Grant: Alliance Grants

Reducing energy use in existing buildings is key to meeting climate change mitigation goals. Climate change disproportionally affects disadvantaged peoples, and retrofits can improve their housing conditions. Better computer models of how our buildings are performing are needed to give robust design solutions and evidence-based policies. Data-driven methods that use machine-learning have great potential as our buildings provide lots of data, but little is currently used for reducing emissions. These can be combined with existing models based on physics, and also used to speed up the simulation process.The ReBuild Initiative is an industry-government-academia consortium that will undertake 16 research activities that encompass the breadth and complexity of the challenge, each co-designed with a partner organization to address their needs. It is important to find synergies between the methods used by professionals, service providers and policy-makers. These collaborations will help refine and address key questions in data-driven building energy retrofits such as: Which machine learning methods are effective in tackling each problem? How can these methods integrate with existing simulation-based approaches? What datasets are needed to power them, and how can they be evaluated? How should these developments be leveraged and deployed to deliver improved tools, analyses and policy measures?The goals of the Initiative are: (a) to develop new methods and tools for building energy retrofit decisions using data-driven approaches, (b) to facilitate the exchange of knowledge, data and software between academia, industry and government partners, and (c) to influence future policy and regulation in Canada regarding existing buildings. Web-based tools will be tested and applied by partners to improve profitability, market penetration and efficiency. It will inform the development of a code for existing buildings and other policies at municipal, provincial and federal levels. It will also train a cohort of skilled workers with expertise to apply cutting-edge methods to pressing problems in industry, government and academia.