A decision-making method for optimal sizing of a sustainable residential building via a multi-objective optimization method

Grid uncertainty, the availability of renewable sources, and power shortages are significant drawbacks for hybrid renewable energy systems. To address these issues, a two-step multi-objective optimization approach with a rule-based battery sizing can be used to identify the best energy management scenario, and appropriate energy storage solutions can help mitigate these disadvantages. In this study, a high-rise residential building was modeled using EnergyPlus software. A variable temperature setpoint for the heating, ventilation and cooling (HVAC) system was implemented to maintain thermal comfort and achieve energy savings. Simulation results were then imported into Python, where a multi-objective optimization approach was applied to integrate renewable energy solutions. A multi-criteria decision-making (MCDM) method was used to identify the optimal solution among various alternatives. The findings show that battery sizing is crucial for optimizing the hybrid energy system, as excess electricity can be sold to the grid. Additionally, the study found that the annual total cost of the optimized hybrid renewable energy system for renewable energy generation in three selected cities is $0.18/kWh, $0.2/kWh, and $0.17/kWh for Tabriz, Tehran, and Yazd, respectively. Moreover, the proposed hybrid renewable energy system (HRES) for Tabriz, Tehran, and Yazd can potentially sell 30%, 24%, and 23% of their annual renewable energy generation to the grid.