A novel data-driven life-cycle optimisation approach is proposed for building retrofitting. The innovation points include big-data information, integrated retrofitting design, and life-cycle optimisation through a comprehensive assessment of the economy, energy and environment. The optimal retrofitting plan is selected to maximise its life-time cost-saving, energy reduction and carbon reduction. The proposed retrofitting optimisation approach is tested on a real-world building. The standard retrofitting options include roof insulation, wall insulation, wind turbine, solar heater, biomass boiler, combined heat and power system and photovoltaic panel. The historical energy consumption, building information, historical weather data, and inventory data is adopted in the data-driven model to replicate the real-world case. Although building retrofitting would increase economic, energy and environmental effects at the beginning of its life-cycle due to increased investment cost, embodied energy and carbon of retrofitting materials, the overall life-cycle cost, energy and carbon would be lower than those non-retrofitted buildings. It is found that envelope insulation has the lowest unit return cost, energy and carbon, followed by the solar heater, combined heat and power system, biomass boiler, wind turbine and photovoltaic panel. Through the optimal retrofitting plan, 39% life-time cost-saving, 55% life-time energy reduction and 59% life-time carbon reduction can be achieved at an investment cost of £1.32 × 106.
Luo, X., & Oyedele, L. O. (2021). A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment. Journal of Building Engineering, 43, https://doi.org/10.1016/j.jobe.2021.102934