Multi-objective optimization of energy consumption, cost and emission for a residential building

In this research, a multi-objective optimization was conducted to minimize three objectives including: energy consumption, life-cycle cost (LCC) and emissions for a residential building. A single-family residential building was chosen and modelled as a case study for the parametric study. This paper examined several design variables, namely: roof and wall materials, window specifications, building orientation, daylighting control, coefficient of performance (COP) values and HVAC system type. In order to conduct multi-objective optimization, EnergyPlus software is integrated with jEPlus+EA software. Firstly, EnergyPlus was used as an energy modeling tool to measure the value of each objective function. Furthermore, jEPlus+EA was utilized to control both design parameters and optimization algorithm. A non-dominated sorting genetic algorithm (NSGA-II) was employed in this study to obtain optimal solutions. Results indicated that optimizing these parameters could save about 21.26 GJ (43.63 %) in energy usage, 7728.59 JD (37.6 %) in LCC, and 1143.31 kg (43.65 %) in emissions. It is concluded that design parameters related to HVAC system have the most significant impact on the three objective functions, as the HVAC system accounts for 67 % of overall energy usage. The methodology's strengths include separate optimization stages that enhance the control of outcomes. Limitations include the fact that EnergyPlus cannot simulate the effect of HVAC systems on indoor air quality as well as the time required to prepare each software tool for optimization.