Energy optimization of building design using Genetic Algorithm and RMP ranking method

This study presents a simulation-based multi-objective optimization approach for identifying the optimal building envelope design to minimize energy consumption (for cooling and for heating), and carbon emissions. In this regard, the implemented methodology includes three basic phases: building energy simulation (EnergyPlus), optimization (non-dominant sorting genetic algorithm NSGA II), and multi-criteria
decision analysis. The methodology is applied to a single room located in Nice region, France; and the considered variable optimization parameters are: walls and roof material properties, room orientation, glazing type, WWR (window-to-wall ratio), heating and cooling set-point temperatures, ventilation and infiltration rates. The results of the optimization are obtained by means of NSGA II iterations according to the predefined
optimization objectives (cooling and heating demand), and are presented in the form of Pareto fronts. The best compromise solution was chosen by using a ranking procedure based on reference profiles recently proposed in the literature, named ranking with multiple reference profiles (RMP). Final optimal solution corresponded to WWR of 33%, an orientation
of 5°, external walls with 15 cm of EPS (outside insulation), a
roof configuration with 15 cm of PUR, double selective windows (Dbl Bronze 6mm/13mm Arg), an infiltration rate of 0.75 ac/h, and a natural ventilation rate of 3.5 vol/h.