Multi objective optimization for energy-cost efficiency of passive and active systems in buildings using genetic algorithm
The current research seeks practical solutions to questions of which passive and active energy systems are more productive in terms of energy-cost efficiency and where the optimal investment points are. It takes a holistic approach to investigate the building as a whole and integrate the knowledge of saving strategies in both operating and embodied energy consumption. The project also benefits from Genetic Algorithm as an optimization method to minimize energy consumption and CO2 emissions in building envelope as well as the HVAC systems while minimizing the costs.