Incorporating occupancy data in scheduling building equipment: A simulation optimization framework

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Abstract

A common energy-conservation method involves specifying a schedule in the building automation system (BAS) so that equipment enter a sleep mode or low power mode during predetermined off-shift hours generally defined based on the expected or perceived occupancy schedule. This paper proposes a binary programing optimization model that incorporates actual occupancy patterns for different zones in the building as well as equipment interdependence to systematically determine the optimal schedule for each equipment while maintaining a minimum required service level to meet occupant needs. The model is then integrated into a simulation optimization framework, where historical or simulated occupancy data are used to determine the optimal frequency of schedule updates and the best design option for new buildings or retrofit projects. Through a real-world case study of a university building, we illustrate how the proposed approach harnesses historical occupancy data to select the best option for re-purposing the zones/spaces in the building. The results provide important practical insights by showing the significant potential to improve common practice that typically uses the exact same schedule for all equipment in the BAS. The results further show that the choice of the design option depends on the minimum required service level. The paper also illustrates the importance of updating equipment schedules in response to possible seasonal changes in occupancy patterns throughout the year. All codes and datasets are made available in an open repository to facilitate adoption by practitioners and enable reproducibility of the results for researchers.
Original languageEnglish (US)
JournalEnergy and Buildings
StatePublished - 2020

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Scheduling
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Energy conservation

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title = "Incorporating occupancy data in scheduling building equipment: A simulation optimization framework",
abstract = "A common energy-conservation method involves specifying a schedule in the building automation system (BAS) so that equipment enter a sleep mode or low power mode during predetermined off-shift hours generally defined based on the expected or perceived occupancy schedule. This paper proposes a binary programing optimization model that incorporates actual occupancy patterns for different zones in the building as well as equipment interdependence to systematically determine the optimal schedule for each equipment while maintaining a minimum required service level to meet occupant needs. The model is then integrated into a simulation optimization framework, where historical or simulated occupancy data are used to determine the optimal frequency of schedule updates and the best design option for new buildings or retrofit projects. Through a real-world case study of a university building, we illustrate how the proposed approach harnesses historical occupancy data to select the best option for re-purposing the zones/spaces in the building. The results provide important practical insights by showing the significant potential to improve common practice that typically uses the exact same schedule for all equipment in the BAS. The results further show that the choice of the design option depends on the minimum required service level. The paper also illustrates the importance of updating equipment schedules in response to possible seasonal changes in occupancy patterns throughout the year. All codes and datasets are made available in an open repository to facilitate adoption by practitioners and enable reproducibility of the results for researchers.",
author = "Avinash Pallikere and Robin Qiu and Parhum Delgoshaei and Ashkan Negahban",
year = "2020",
language = "English (US)",
journal = "Energy and Buildings",
issn = "0378-7788",
publisher = "Elsevier BV",

}

TY - JOUR

T1 - Incorporating occupancy data in scheduling building equipment: A simulation optimization framework

AU - Pallikere, Avinash

AU - Qiu, Robin

AU - Delgoshaei, Parhum

AU - Negahban, Ashkan

PY - 2020

Y1 - 2020

N2 - A common energy-conservation method involves specifying a schedule in the building automation system (BAS) so that equipment enter a sleep mode or low power mode during predetermined off-shift hours generally defined based on the expected or perceived occupancy schedule. This paper proposes a binary programing optimization model that incorporates actual occupancy patterns for different zones in the building as well as equipment interdependence to systematically determine the optimal schedule for each equipment while maintaining a minimum required service level to meet occupant needs. The model is then integrated into a simulation optimization framework, where historical or simulated occupancy data are used to determine the optimal frequency of schedule updates and the best design option for new buildings or retrofit projects. Through a real-world case study of a university building, we illustrate how the proposed approach harnesses historical occupancy data to select the best option for re-purposing the zones/spaces in the building. The results provide important practical insights by showing the significant potential to improve common practice that typically uses the exact same schedule for all equipment in the BAS. The results further show that the choice of the design option depends on the minimum required service level. The paper also illustrates the importance of updating equipment schedules in response to possible seasonal changes in occupancy patterns throughout the year. All codes and datasets are made available in an open repository to facilitate adoption by practitioners and enable reproducibility of the results for researchers.

AB - A common energy-conservation method involves specifying a schedule in the building automation system (BAS) so that equipment enter a sleep mode or low power mode during predetermined off-shift hours generally defined based on the expected or perceived occupancy schedule. This paper proposes a binary programing optimization model that incorporates actual occupancy patterns for different zones in the building as well as equipment interdependence to systematically determine the optimal schedule for each equipment while maintaining a minimum required service level to meet occupant needs. The model is then integrated into a simulation optimization framework, where historical or simulated occupancy data are used to determine the optimal frequency of schedule updates and the best design option for new buildings or retrofit projects. Through a real-world case study of a university building, we illustrate how the proposed approach harnesses historical occupancy data to select the best option for re-purposing the zones/spaces in the building. The results provide important practical insights by showing the significant potential to improve common practice that typically uses the exact same schedule for all equipment in the BAS. The results further show that the choice of the design option depends on the minimum required service level. The paper also illustrates the importance of updating equipment schedules in response to possible seasonal changes in occupancy patterns throughout the year. All codes and datasets are made available in an open repository to facilitate adoption by practitioners and enable reproducibility of the results for researchers.

M3 - Article

JO - Energy and Buildings

JF - Energy and Buildings

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