Realistic Scheduling Mechanism for Smart Homes

Danish Mahmood, Nadeem Javaid, Nabil Alrajeh, Zahoor Ali Khan, Umar Qasim, Imran Ahmed and Manzoor Ilahi
Additional contact information
Danish Mahmood: COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Nadeem Javaid: COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Nabil Alrajeh: College of Applied Medical Sciences, Department of Biomedical Technology, King Saud University, Riyadh 11633, Saudi Arabia
Zahoor Ali Khan: Internetworking Program, Faculty of Engineering, Dalhousie University, Halifax, NS B3J 4R2, Canada
Umar Qasim: Cameron Library, University of Alberta, Edmonton, AB T6G 2J8, Canada
Imran Ahmed: Institute of Management Sciences (IMS), Peshawar 25000, Pakistan
Manzoor Ilahi: COMSATS Institute of Information Technology, Islamabad 44000, Pakistan

Energies, 2016, vol. 9, issue 3, 1-28

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.

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) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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