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Energy efficiency-based course timetabling for university buildings

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  • Song, Kwonsik
  • Kim, Sooyoung
  • Park, Moonseo
  • Lee, Hyun-Soo

Abstract

With increasing concern for energy savings in universities, operational solutions, such as control strategies and occupant interventions, have been recommended to reduce energy use, due to the limited responsibilities of faculties and students for energy saving. Additionally, the energy-efficient allocation of classrooms can contribute to achieving further energy saving, because they have different spatial and functional capacities, which result in variation in energy use. In this context, course timetabling can be regarded as a basic source of allocating specific classrooms to lectures. However, there have been few attempts to consider spatial and functional capacities related to energy use in classrooms. Further, little is known about investigating the impact of course timetabling on energy consumption in classrooms. Therefore, this research proposes an energy efficiency-based course timetabling algorithm that identifies an optimal timetable in terms of energy use. The experimental results using the proposed algorithms make it evident that the optimal timetable produces 4% energy saving during cooling and heating season compared to the existing timetable. In addition, more energy savings up to 5.0% are achieved by mitigating hard constraints. The developed algorithm allows for administration staff and facility managers to schedule a course timetable that achieves energy savings in university buildings.

Suggested Citation

  • Song, Kwonsik & Kim, Sooyoung & Park, Moonseo & Lee, Hyun-Soo, 2017. "Energy efficiency-based course timetabling for university buildings," Energy, Elsevier, vol. 139(C), pages 394-405.
    • Handle: RePEc:eee:energy:v:139:y:2017:i:c:p:394-405
    DOI: 10.1016/j.energy.2017.07.176
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    References listed on IDEAS

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    2. Sara Tavakoli & Wipa Loengbudnark & Melissa Eklund & Alexey Voinov & Kaveh Khalilpour, 2023. "Impact of COVID-19 Pandemic on Energy Consumption in Office Buildings: A Case Study of an Australian University Campus," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    3. Song, Kwonsik & Jang, Youjin & Park, Moonseo & Lee, Hyun-Soo & Ahn, Joseph, 2020. "Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings," Energy, Elsevier, vol. 206(C).
    4. Raphael Medeiros Alves & Francisco Cunha & Anand Subramanian & Alisson V. Brito, 2022. "Minimizing energy consumption in a real-life classroom assignment problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1149-1175, December.
    5. Piotr Kosiński & Aldona Skotnicka-Siepsiak, 2022. "Possibilities of Adapting the University Lecture Room to the Green University Standard in Terms of Thermal Comfort and Ventilation Accuracy," Energies, MDPI, vol. 15(10), pages 1-23, May.
    6. Xu, Fangyuan & Wu, Wanli & Zhao, Fei & Zhou, Ya & Wang, Yongjian & Wu, Runji & Zhang, Tao & Wen, Yongchen & Fan, Yiliang & Jiang, Shengli, 2019. "A micro-market module design for university demand-side management using self-crossover genetic algorithms," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Kwonsik Song & Yonghan Ahn & Joseph Ahn & Nahyun Kwon, 2019. "Development of an Energy Saving Strategy Model for Retrofitting Existing Buildings: A Korean Case Study," Energies, MDPI, vol. 12(9), pages 1-17, April.
    8. Guerrieri, M. & La Gennusa, M. & Peri, G. & Rizzo, G. & Scaccianoce, G., 2019. "University campuses as small-scale models of cities: Quantitative assessment of a low carbon transition path," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
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