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Energies 2016, 9(3), 202; doi:10.3390/en9030202

Realistic Scheduling Mechanism for Smart Homes

1
COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
2
College of Applied Medical Sciences, Department of Biomedical Technology, King Saud University, Riyadh 11633, Saudi Arabia
3
Internetworking Program, Faculty of Engineering, Dalhousie University, Halifax, NS B3J 4R2, Canada
4
Computer Information Science (CIS), Higher Colleges of Technology, Fujairah Campus 4114, UAE
5
Cameron Library, University of Alberta, Edmonton, AB T6G 2J8, Canada
6
Institute of Management Sciences (IMS), Peshawar 25000, Pakistan
*
Author to whom correspondence should be addressed.
Academic Editor: Nyuk Hien Wong
Received: 16 January 2016 / Revised: 17 February 2016 / Accepted: 26 February 2016 / Published: 15 March 2016
(This article belongs to the Special Issue Energy Efficient Building Design 2016)
View Full-Text   |   Download PDF [3132 KB, uploaded 16 March 2016]   |  

Abstract

In this work, we propose a Realistic Scheduling Mechanism (RSM) to reduce user frustration and enhance appliance utility by classifying appliances with respective constraints and their time of use effectively. Algorithms are proposed regarding functioning of home appliances. A 24 hour time slot is divided into four logical sub-time slots, each composed of 360 min or 6 h. In these sub-time slots, only desired appliances (with respect to appliance classification) are scheduled to raise appliance utility, restricting power consumption by a dynamically modelled power usage limiter that does not only take the electricity consumer into account but also the electricity supplier. Once appliance, time and power usage limiter modelling is done, we use a nature-inspired heuristic algorithm, Binary Particle Swarm Optimization (BPSO), optimally to form schedules with given constraints representing each sub-time slot. These schedules tend to achieve an equilibrium amongst appliance utility and cost effectiveness. For validation of the proposed RSM, we provide a comparative analysis amongst unscheduled electrical load usage, scheduled directly by BPSO and RSM, reflecting user comfort, which is based upon cost effectiveness and appliance utility. View Full-Text
Keywords: Home Energy Management System (HEMS); appliance scheduling; Binary Particle Swarm Optimization (BPSO); user comfort; appliance classification; Demand Response (DR) programs; time of use pricing; Demand Side Management (DSM) Home Energy Management System (HEMS); appliance scheduling; Binary Particle Swarm Optimization (BPSO); user comfort; appliance classification; Demand Response (DR) programs; time of use pricing; Demand Side Management (DSM)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mahmood, D.; Javaid, N.; Alrajeh, N.; Khan, Z.A.; Qasim, U.; Ahmed, I.; Ilahi, M. Realistic Scheduling Mechanism for Smart Homes. Energies 2016, 9, 202.

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