Multi-objective optimization methodology for net zero energy buildings

The challenge in Net Zero Energy Building (NZEB) design is to find the best combination of design strategies that will face the energy performance problems of a particular building. This paper presents a methodology for the simulation-based multi-criteria optimization of NZEBs. Its main features include four steps: building simulation, optimization process, multi-criteria decision making (MCDM) and testing solution's robustness. The methodology is applied to investigate the cost-effectiveness potential for optimizing the design of NZEBs in different case studies taken as diverse climatic zones in Lebanon and France. The investigated design parameters include: external walls and roof insulation thickness, windows glazing type, cooling and heating set points, and window to wall ratio. Furthermore, the inspected RE systems include: solar domestic hot water (SDHW) and photovoltaic (PV) array. The proposed methodology is a useful tool to enhance NZEBs design and to facilitate decision making in early phases of building design. Specifically, the non-dominated sorting genetic algorithm (NSGA-II) is chosen in order to minimize thermal, electrical demands and life cycle cost (LCC) while reaching the net zero energy balance; thus getting the Pareto-front. A ranking decision making technique Elimination and Choice Expressing the Reality (ELECTRE III) is applied to the Pareto-front so as to obtain one optimal solution.