Paper Conference

Proceedings of eSim 2022: 12th Conference of IBPSA-Canada


Multi-objective optimization of building retrofit strategies using staged GHG emission targets

Mohammad Derakhti, Wiliam O'Brien, Scott Bucking
Carleton Universitu, Canada

Abstract: Retrofit analysis plays a crucial role in achieving GHG emission reduction. However, due to the unique characteristics of existing buildings, it is still challenging to identify the most appropriate retrofitting scenario and its environmental impact and life cycle cost. Hence, this study investigates the impact of the different targets for GHG emissions reduction on the optimal retrofit strategies. A non-dominated sorting genetic algorithm was selected as the optimization algorithm. Annual carbon dioxide emissions and the net present value of each retrofit scenario are defined as objective functions and ensure viable solutions (GHG emissions reduction target). The results reveal that the CV(RMSE) of hourly data was decreased from 68% to 21% after employing the optimization calibration. Also, a 40% reduction in GHG emissions was accessible without changing the HVAC system. Moreover, the ground source heat pump was the most efficient option for reducing around 70% in GHG emissions.
Keywords: Retrofit analysis, Multi objective optimization, GHG emissions, Genetic algorithm