An Approach for Improving Energy Efficiency in a Commercial Building with Learning Consideration and Availability Constraints
Cihan Tuğrul Çiçek
Department of Industrial Engineering, METU
Energy efficiency issues have been increasingly becoming more popular as available natural resources such as natural gas and fossils have been running out. In this study, we address the scheduling problem of the automated heating, ventilation and air conditioning (HVAC) system of a commercial building to increase the energy efficiency. We formulate the problem as a multilevel generalized assignment model to obtain the schedule of the several units of the HVAC system and to determine the running level of the units of the system through consecutive periods of a day. In our formulation, the dynamic nature of weather conditions, multi-level running structure of the HVAC, availability conditions, learning effects of the units, and the circulation of people in the building are considered. Moreover, we propose a tabu search algorithm with ejection chains to solve such a complex and large model in reasonable times, and present the computational results. Our tabu search algorithm provides satisfactory results with a significant amount of reduction in electricity consumption, without remarkably increasing the computational effort required.
Cihan Tugrul Cicek is a research assistant in the Office of Sponsored Projects of METU and a Ph.D. student at TOBB University of Economics and Technology. He received his B.S. degree from the Industrial Engineering Department of TOBB University of Economics and Technology in 2010, and his M.S. degree in Operations Research from the Industrial Engineering Department of METU in 2014. He received his second Master's Degree in Facilities and Environment Management from The Bartlett School of Architecture of University College London in the same year. He worked as the project manager in The Union of Chambers and Commodity Exchanges of Turkey between 2010 and 2017, before joining METU. His research interests are in the fields of location, multi-criteria decision making, energy efficiency and optimization.
Friday, October 27, 2017 at 4.00 pm in IE03