Energy-aware meeting scheduling algorithms for smart buildings

Majumdar, Abhinandan; Albonesi, David H.; Bose, Pradip

doi:10.1145/2422531.2422560

Cited by 27 publications

(14 citation statements)

References 6 publications

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“…The scheduling-based control model makes the process of maintaining the operation of electrical devices through the schedules entered into the system [11,12], and energy efficiency is performed using remote control [10].…”

Section: Related Workmentioning

confidence: 99%

“…In [10], an automation system has been built based on user schedule using a wireless sensor actuator network (WSAN) in an office environment. The scheduling-based control model has been also developed with smart meeting scheduling [11], and monitoring and controlling systems in an office environment to minimize operational costs [12]. The meeting scheduling algorithm in the room has made the automation system aware of energy consumption because is able to automate meeting scheduling based on the time and space capacity [11].…”

Section: Introductionmentioning

confidence: 99%

“…The scheduling-based control model has been also developed with smart meeting scheduling [11], and monitoring and controlling systems in an office environment to minimize operational costs [12]. The meeting scheduling algorithm in the room has made the automation system aware of energy consumption because is able to automate meeting scheduling based on the time and space capacity [11]. Monitoring and control of devices using operating schedules within buildings have been able to perform energy efficiency in accordance with user-defined policies to minimize operating costs of devices in an office environment [12].…”

Section: Introductionmentioning

confidence: 99%

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Design of Control Model for Multi-User Preference and Activity in Smart Building System for Energy Saving

Fauzi¹,

Sulistyo²,

Widyawan³

2018

IJIES

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Abstract:The environmental adaptability of the smart building is required for energy efficiency. The schedulingbased control model that widely implemented, have a user dependence and assumes maximum occupancy regardless of the occupant's desire in the energy usage requirement during the activity (i.e., ignoring user preferences). In this paper, we present our study on a building control model based on user preference, presence, location, and activity. We present it in a formal model, including conflict resolution techniques on multi-user preference (minimum, maximum, and average preference models). The contribution of this study is the optimization of control model for energy efficiency that also meet multi-user preference. The evaluation of the proposed control model is done through simulation and is compared with the scheduling-based control models. The results show that the minimum, maximum, and average preferences have an energy consumption of 73.5 kWh/day, 44.5 kWh/day, and 58.9 kWh/day, respectively, which are more efficient than the scheduling-based control model. If the Euclidean distance is used to estimate the error value between temperature and light actuation to multi-user preference, the lowest error is the average preference.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design of Control Model for Multi-User Preference and Activity in Smart Building System for Energy Saving

Fauzi¹,

Sulistyo²,

Widyawan³

2018

IJIES

View full text Add to dashboard Cite

show abstract

“…Majumdar et al [16] evaluate the performance of a number of scheduling algorithms that they run through the energy simulation software EnergyPlus [3]. Some criteria considered in their algorithms include minimizing the number of rooms, minimizing time between meetings in the same room, and minimizing room size.…”

Section: Related Workmentioning

confidence: 99%

Large Neighborhood Search for Energy Aware Meeting Scheduling in Smart Buildings

Lim

Briel

Thiébaux

et al. 2015

Integration of AI and OR Techniques in Constraint Programming

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Abstract. One of the main inefficiencies in building management systems is the widespread use of schedule-based control when operating heating, ventilation and air conditioning (HVAC) systems. HVAC systems typically operate on a pre-designed schedule that heats or cools rooms in the building to a set temperature even when rooms are not being used. Occupants, however, influence the thermal behavior of buildings. As a result, using occupancy information for scheduling meetings to occur at specific times and in specific rooms has significant energy savings potential. As shown in Lim et al. [15], combining HVAC control with meeting scheduling can lead to substantial improvements in energy efficiency. We extend this work and develop an approach that scales to larger problems by combining mixed integer programming (MIP) with large neighborhood search (LNS). LNS is used to destroy part of the schedule and MIP is used to repair the schedule so as to minimize energy consumption. This approach is far more effective than solving the complete problem as a MIP problem. Our results show that solutions from the LNS-based approach are up to 36% better than the MIP-based approach when both given 15 minutes.

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“…We have a previous study [13] where we observe that the cool air in a room will not dissipate immediately after a class and class schedules should take such advantage. A followup work develops more refined schedules [14]. These studies only consider the thermal storage of a room, which is small and less practical in real world.…”

Section: Related Workmentioning

confidence: 99%

Minimizing Building Electricity Costs in a Dynamic Power Market: Algorithms and Impact on Energy Conservation

Pan

Wang

Cao

et al. 2013

2013 IEEE 34th Real-Time Systems Symposium

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Abstract-Energy is a global concern and the electricity bills nowadays are leading to unprecedented costs. Electricity price is market-based and dynamic. In this paper, we investigate how to cut the electricity bills of commercial buildings in a dynamic power market. The building thermal systems (e.g., air-conditioning), which dominate electricity bills, has a special property of thermal storage, i.e., the energy will not immediately dissipate from thermal air/water. Intuitively, with storage, the energy can be "stored" in the thermal system, making it possible to purchase electricity in low price and use it at appropriate time. The building thermal supply and electricity purchasing surely depends on human activities that the building should support such as class and meeting schedules. To minimize electricity bills, we develop a holistic planning of electricity purchasing schedule with thermal storage management, and appropriate room assignment schedules for classes/meetings usage.The computing algorithms require inputs of physical modeling on energy consumption. We develop wireless sensing systems to collect fine-grained data which are used to assist the cross-disciplinary physical modeling. We conduct validation through real experiments. We formulate an optimization problem and show that it is NP-complete. Our primary focus is to minimize electricity bills, which matches the incentives of the commercial buildings. We show that this does not coincide with energy conservation. We further investigate the relationship of minimization of electricity bills and minimization of energy consumption. We develop algorithms for our problem and our evaluation shows that we can achieve a 40% cost reduction.

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Energy-aware meeting scheduling algorithms for smart buildings

Cited by 27 publications

References 6 publications

Design of Control Model for Multi-User Preference and Activity in Smart Building System for Energy Saving

Design of Control Model for Multi-User Preference and Activity in Smart Building System for Energy Saving

Large Neighborhood Search for Energy Aware Meeting Scheduling in Smart Buildings

Minimizing Building Electricity Costs in a Dynamic Power Market: Algorithms and Impact on Energy Conservation

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