Cooling/heating load management in educational buildings through course scheduling. (September 2021)

• Record Type: Journal Article
• Authors: Fathi, Amirhossein; Salehi, Mohammad; Mohammadi, Mohsen; Rahimof, Yasmin; Hajialigol, Parisa
• Is Part Of: Journal of building engineering. Volume 41(2021)
• Publication Date: 2021-09
• Subjects: Comprehensive educational timetabling -- Computational load reduction -- Academic buildings -- Energy-saving -- Load management -- Optimization model -- Shared resources; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.102405
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: This paper presents a comprehensive educational model considering share resources among several departments bounded to educational limitations for optimizing energy consumption. The thermal model calculates the load based on the ambient temperature to minimize the user's knowledge of the building's thermal model. It determines the percentage reduction of the building's heating load in case of a change in room temperature, a term's start date, and sharing classes compared to standard curricula. It employs linear Boolean optimization. Class planning is carried out concerning minimizing energy use, students' preferences, charts, educational constraints, professors' schedules, classes' numbers, and shared resources. Optimal timetabling influences on the heating load for Shiraz University's second engineering building complex are analyzed, used by Mechanical Engineering, Computer Engineering departments, and Auditorium. The effects of three scenarios and two situations on energy consumption are quantified. The results indicate the best curriculum is not affected by the scenarios. A two-week early beginning and a temperature of 23C of classes reduce energy consumption by over 50%. In deploying the optimal timetabling, the potential of diminishing the heating energy consumption is about 12% compared with conventional timetabling. Sharing resources do not always lead to a decrease in energy use, but this activity can slide it by 2.5%. These results are aligned with commercial software's outcomes. To tackle the obstacle of the computational load, reducing a matrix's dimensions is implemented. It cuts down the number of decision variables, unequal and equal constraints from 90.8%, 99.97%, and 57.81%, respectively. Graphical abstract: A mathematical programming model for saving energy consumption in educational buildings through scheduling courses in the accepted timeslots subjected to educational constraints and resource availability is developed in this study. Image 1 Highlights: Optimizing curricula, shared resources, term's date and room temperature reduce load. The mentioned strategies reduce heating load up to 50%. The optimal curriculum alone decreases the heating by 12%. The computational load as an obstacle of timetabling is significantly decreased.