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Appl. Sci. 2015, 5(4), 1134-1163; doi:10.3390/app5041134

An Efficient Power Scheduling Scheme for Residential Load Management in Smart Homes

1
COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
2
Internetworking Program, Faculty of Engineering, Dalhousie University, Halifax, Nova Scotia B3J 4R2, Canada
3
Computer Information Science (CIS), Higher Colleges of Technology, Fujairah Campus 4114, The United Arab Emirates (UAE)
4
University of Alberta, Edmonton, Alberta T6G 2J8, Canada
5
College of Applied Medical Sciences, Department of Biomedical Technology, King Saud University, Riyadh 11633, Saudi Arabia
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Minho Shin
Received: 11 September 2015 / Revised: 29 October 2015 / Accepted: 30 October 2015 / Published: 12 November 2015
(This article belongs to the Special Issue Smart Grid: Convergence and Interoperability)
View Full-Text   |   Download PDF [1011 KB, uploaded 12 November 2015]   |  

Abstract

In this paper, we propose mathematical optimization models of household energy units to optimally control the major residential energy loads while preserving the user preferences. User comfort is modelled in a simple way, which considers appliance class, user preferences and weather conditions. The wind-driven optimization (WDO) algorithm with the objective function of comfort maximization along with minimum electricity cost is defined and implemented. On the other hand, for maximum electricity bill and peak reduction, min-max regret-based knapsack problem (K-WDO) algorithm is used. To validate the effectiveness of the proposed algorithms, extensive simulations are conducted for several scenarios. The simulations show that the proposed algorithms provide with the best optimal results with a fast convergence rate, as compared to the existing techniques. View Full-Text
Keywords: demand response; energy management; time of use pricing; swarm optimization; knapsack; smart grid demand response; energy management; time of use pricing; swarm optimization; knapsack; smart grid
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

Rasheed, M.B.; Javaid, N.; Ahmad, A.; Khan, Z.A.; Qasim, U.; Alrajeh, N. An Efficient Power Scheduling Scheme for Residential Load Management in Smart Homes. Appl. Sci. 2015, 5, 1134-1163.

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