Optimization of a university timetable considering building energy efficiency: An approach based on the building controls virtual test bed platform using a genetic algorithm

Abstract It is difficult to prompt students to take energy saving behaviors proactively owing to their limited responsibilities for energy saving; thus, administrators are required to actively adopt management means to reduce building energy consumption. Reasonable arrangement of course timetables by administrators can greatly promote energy efficiency in university buildings, as the energy consumption of teaching buildings is closely related to factors such as occupancy time and number of users. Hence, this study develops a co-simulation method based on the Building Controls Virtual Test Bed (BCVTB) platform using genetic algorithm to optimize university timetable considering building energy efficiency. The timetable of a university teaching building in Xi'an, China, from September 2019 to January 2020, is simulated using the proposed method. According to the simulation results, the occupancy of classrooms in the optimized timetable is relatively concentrated timewise. As more courses are allocated in the afternoon, the operating time of lighting during the daytime would decrease accordingly. Therefore, the lighting power consumption is reduced. In addition, the cooling load of the teaching building is increased and the heating load of the teaching building decreases. The results indicate that the utilization of the proposed course timetabling method can reduce the energy consumption of teaching buildings by approximately 3.6% in the autumn semester. The developed method helps administrators arrange a timetable to achieve energy efficiency in university buildings. Moreover, it is helpful for the design and operation management of teaching buildings.