With increasing concern related to carbon dioxide emission, concept of Zero Energy Building (ZEB) appears. Electric Vehicles are also considered environment friendly automobiles to reduce greenhouse gas emission. With global trends above, Building energy system should consider ZEB concept and electricity demand for EVs charging. Therefore, this thesis suggests reasonable problem-solving method to find the best optimal energy system design to meet ZEB condition. EVs charging demand is predicted from the fittest Machine Learning regression model. This result combined with Hourly Building Energy demand from EnergyPlus simulator. Last Genetic Algorithm and PROBID method will be applied to meet two objective functions : Annual Total Cost and Self-Energy Sufficiency ratio.
Keywords Renewable energy, energy system optimization, NSGA2, Zero Energy Building, Electric Vehicle, Energyplus