MULTI-OBJECTIVE OPTIMIZATION FOR ACHIEVING A ZERO-ENERGY BUILDING: APPLICATION OF BIOCLIMATIC GUIDELINES IN AN EDUCATIONAL BUILDING
Zero energy balance; University campus; Computer simulation; Multi-objective optimization; Genetic algorithm.
University campuses can be compared to small towns due to their substantial building sizes, the large number of users, and the diversity of functions they perform. Various factors, such as the type of teaching, the area of occupation, and the building envelope, contribute to the high energy demand of higher education institutions. As a result, campuses have the potential to meet their own energy needs by implementing efficiency measures and generating renewable energy. From this perspective, Zero Energy Buildings (ZEBs) are a promising strategy for optimizing energy consumption, since they are efficient buildings and generate their own energy, while ensuring good comfort conditions for users of university campuses. In this context, the aim of this research is to determine the impact of bioclimatic guidelines for obtaining a ZEB, by means of multi-objective optimization, from an existing educational building in Brasília, DF. The method of this work is based on an optimization whose objectives are to minimize the hours of discomfort and reduce energy expenditure on artificial lighting, through an automation system. The simulations were conducted in three stages. The first uses an evolutionary algorithm to find optimal thermal comfort solutions. The second stage uses new optimization processes, without an algorithm. This stage analyzes the visual comfort of the classrooms and also includes the use of air conditioning to compensate for the hours of heat discomfort and compare the energy consumption of the optimal scenarios. Finally, photovoltaic energy generation is simulated, and the energy balance of the optimal scenario is analyzed. The results of the research showed that the implementation of bioclimatic strategies associated with the use of efficient air conditioning systems and the integration of automation resources for the lighting systems contributed to improving the building's performance. The optimum scenario found improved the annual Performance of Occupant Comfort (POC) by 50% and energy demand by 51%, as well as promoting adequate illuminance levels without glare. The combination of these factors led the building towards achieving a zero energy balance, with a positive extrapolation of the results to the campus.