Next Article in Journal
Fractionation of Lignocellulosic Residues Coupling Steam Explosion and Organosolv Treatments Using Green Solvent γ-Valerolactone
Next Article in Special Issue
Cost Analysis for a Hybrid Advanced Metering Infrastructure in Korea
Previous Article in Journal
Layout Optimisation of Wave Energy Converter Arrays
Previous Article in Special Issue
The Potential of Smart Technologies and Micro-Generation in UK SMEs
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Energies 2017, 10(9), 1258; doi:10.3390/en10091258

An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes

1
COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
2
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.
Received: 29 June 2017 / Revised: 11 August 2017 / Accepted: 16 August 2017 / Published: 24 August 2017
(This article belongs to the Special Issue From Smart Metering to Demand Side Management)
View Full-Text   |   Download PDF [1091 KB, uploaded 25 August 2017]   |  

Abstract

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. View Full-Text
Keywords: demand side management; demand response; home energy management system; meta-heuristic techniques demand side management; demand response; home energy management system; meta-heuristic techniques
Figures

Figure 1

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top