An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes
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COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
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University of Engineering and Technology Peshawar, Bannu 28100, Pakistan
3
Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia
*
Author to whom correspondence should be addressed.
Energies 2017, 10(9), 1258; https://doi.org/10.3390/en10091258
Received: 29 June 2017
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Revised: 11 August 2017
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Accepted: 16 August 2017
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Published: 24 August 2017
(This article belongs to the Special Issue From Smart Metering to Demand Side Management)
Smart grid is an emerging technology which is considered to be an ultimate solution to meet the increasing power demand challenges. Modern communication technologies have enabled the successful implementation of smart grid (SG), which aims at provision of demand side management mechanisms (DSM), such as demand response (DR). In this paper, we propose a hybrid technique named as teacher learning genetic optimization (TLGO) by combining genetic algorithm (GA) with teacher learning based optimization (TLBO) algorithm for residential load scheduling, assuming that electric prices are announced on a day-ahead basis. User discomfort is one of the key aspects which must be addressed along with cost minimization. The major focus of this work is to minimize consumer electricity bill at minimum user discomfort. Load scheduling is formulated as an optimization problem and an optimal schedule is achieved by solving the minimization problem. We also investigated the effect of power-flexible appliances on consumers’ bill. Furthermore, a relationship among power consumption, cost and user discomfort is also demonstrated by feasible region. Simulation results validate that our proposed technique performs better in terms of cost reduction and user discomfort minimization, and is able to obtain the desired trade-off between consumer electricity bill and user discomfort.
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Keywords:
demand side management; demand response; home energy management system; meta-heuristic techniques
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MDPI and ACS Style
Manzoor, A.; Javaid, N.; Ullah, I.; Abdul, W.; Almogren, A.; Alamri, A. An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes. Energies 2017, 10, 1258. https://doi.org/10.3390/en10091258
AMA Style
Manzoor A, Javaid N, Ullah I, Abdul W, Almogren A, Alamri A. An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes. Energies. 2017; 10(9):1258. https://doi.org/10.3390/en10091258
Chicago/Turabian StyleManzoor, Awais, Nadeem Javaid, Ibrar Ullah, Wadood Abdul, Ahmad Almogren, and Atif Alamri. 2017. "An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes" Energies 10, no. 9: 1258. https://doi.org/10.3390/en10091258
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