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Heuristic algorithm based dynamic scheduling model of home appliances in smart grid

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Heuristic algorithm based dynamic scheduling model of home appliances in smart grid. / Khan, Inam Ullah; Ma, Xiandong; Taylor, C. James; Javaid, N; Gamage, Kelum.

24th International Conference on Automation and Computing. IEEE, 2019.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Khan, IU, Ma, X, Taylor, CJ, Javaid, N & Gamage, K 2019, Heuristic algorithm based dynamic scheduling model of home appliances in smart grid. in 24th International Conference on Automation and Computing. IEEE, 24th International Conference on Automation and Computing, Newcastle, United Kingdom, 6/09/18. https://doi.org/10.23919/IConAC.2018.8749110

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Author

Khan, Inam Ullah ; Ma, Xiandong ; Taylor, C. James ; Javaid, N ; Gamage, Kelum. / Heuristic algorithm based dynamic scheduling model of home appliances in smart grid. 24th International Conference on Automation and Computing. IEEE, 2019.

Bibtex

@inproceedings{7e5439335ca84f7e9ec79a0b5d00afd8,
title = "Heuristic algorithm based dynamic scheduling model of home appliances in smart grid",
abstract = "Smart grid provides an opportunity for customers as well as for utility companies to reduce electricity costs and regulate generation capacity. The success of scheduling algorithms mainly depends upon accurate information exchange between main grids and smart meters. On the other hand, customers are required to schedule loads, respond to energy demand signals, participate in energy bidding and actively monitor energy prices generated by the utility company. Strengthening communication infrastructure between the utility company and consumers can serve the purpose of consumer satisfaction. We propose a heuristic demand side management model for scheduling smart home appliances in an automated manner, to maximise the satisfaction of the consumers associated with it. Simulation results confirm that the proposed hybrid approach has the ability to reduce the peak-to-average ratio of the total energy demand and reduce the total cost of the energy without compromising user comfort.",
keywords = "demand side management, appliance scheduling, critical peak pricing, household energy management",
author = "Khan, {Inam Ullah} and Xiandong Ma and Taylor, {C. James} and N Javaid and Kelum Gamage",
note = "{\textcopyright}2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; 24th International Conference on Automation and Computing ; Conference date: 06-09-2018 Through 07-09-2018",
year = "2019",
month = jul,
day = "1",
doi = "10.23919/IConAC.2018.8749110",
language = "English",
isbn = "9781538648919",
booktitle = "24th International Conference on Automation and Computing",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Heuristic algorithm based dynamic scheduling model of home appliances in smart grid

AU - Khan, Inam Ullah

AU - Ma, Xiandong

AU - Taylor, C. James

AU - Javaid, N

AU - Gamage, Kelum

N1 - ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/7/1

Y1 - 2019/7/1

N2 - Smart grid provides an opportunity for customers as well as for utility companies to reduce electricity costs and regulate generation capacity. The success of scheduling algorithms mainly depends upon accurate information exchange between main grids and smart meters. On the other hand, customers are required to schedule loads, respond to energy demand signals, participate in energy bidding and actively monitor energy prices generated by the utility company. Strengthening communication infrastructure between the utility company and consumers can serve the purpose of consumer satisfaction. We propose a heuristic demand side management model for scheduling smart home appliances in an automated manner, to maximise the satisfaction of the consumers associated with it. Simulation results confirm that the proposed hybrid approach has the ability to reduce the peak-to-average ratio of the total energy demand and reduce the total cost of the energy without compromising user comfort.

AB - Smart grid provides an opportunity for customers as well as for utility companies to reduce electricity costs and regulate generation capacity. The success of scheduling algorithms mainly depends upon accurate information exchange between main grids and smart meters. On the other hand, customers are required to schedule loads, respond to energy demand signals, participate in energy bidding and actively monitor energy prices generated by the utility company. Strengthening communication infrastructure between the utility company and consumers can serve the purpose of consumer satisfaction. We propose a heuristic demand side management model for scheduling smart home appliances in an automated manner, to maximise the satisfaction of the consumers associated with it. Simulation results confirm that the proposed hybrid approach has the ability to reduce the peak-to-average ratio of the total energy demand and reduce the total cost of the energy without compromising user comfort.

KW - demand side management

KW - appliance scheduling

KW - critical peak pricing

KW - household energy management

U2 - 10.23919/IConAC.2018.8749110

DO - 10.23919/IConAC.2018.8749110

M3 - Conference contribution/Paper

SN - 9781538648919

BT - 24th International Conference on Automation and Computing

PB - IEEE

T2 - 24th International Conference on Automation and Computing

Y2 - 6 September 2018 through 7 September 2018

ER -