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Realistic Scheduling Mechanism for Smart Homes

Author

Listed:
  • 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
    Computer Information Science (CIS), Higher Colleges of Technology, Fujairah Campus 4114, UAE)

  • 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)

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.

Suggested Citation

  • Danish Mahmood & Nadeem Javaid & Nabil Alrajeh & Zahoor Ali Khan & Umar Qasim & Imran Ahmed & Manzoor Ilahi, 2016. "Realistic Scheduling Mechanism for Smart Homes," Energies, MDPI, vol. 9(3), pages 1-28, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:202-:d:65817
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    References listed on IDEAS

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    Cited by:

    1. Nadeem Javaid & Sakeena Javaid & Wadood Abdul & Imran Ahmed & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid," Energies, MDPI, vol. 10(3), pages 1-27, March.
    2. Muhammad Awais & Nadeem Javaid & Khursheed Aurangzeb & Syed Irtaza Haider & Zahoor Ali Khan & Danish Mahmood, 2018. "Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids," Energies, MDPI, vol. 11(11), pages 1-30, November.
    3. Zafar Iqbal & Nadeem Javaid & Syed Muhammad Mohsin & Syed Muhammad Abrar Akber & Muhammad Khalil Afzal & Farruh Ishmanov, 2018. "Performance Analysis of Hybridization of Heuristic Techniques for Residential Load Scheduling," Energies, MDPI, vol. 11(10), pages 1-31, October.
    4. Bilal Hussain & Nadeem Javaid & Qadeer Ul Hasan & Sakeena Javaid & Asif Khan & Shahzad A. Malik, 2018. "An Inventive Method for Eco-Efficient Operation of Home Energy Management Systems," Energies, MDPI, vol. 11(11), pages 1-40, November.
    5. Shengli Du & Mingchao Li & Shuai Han & Jonathan Shi & Heng Li, 2019. "Multi-Pattern Data Mining and Recognition of Primary Electric Appliances from Single Non-Intrusive Load Monitoring Data," Energies, MDPI, vol. 12(6), pages 1-20, March.
    6. Sébastien Bissey & Sébastien Jacques & Jean-Charles Le Bunetel, 2017. "The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing," Energies, MDPI, vol. 10(11), pages 1-24, October.
    7. Christoforos Menos-Aikateriniadis & Ilias Lamprinos & Pavlos S. Georgilakis, 2022. "Particle Swarm Optimization in Residential Demand-Side Management: A Review on Scheduling and Control Algorithms for Demand Response Provision," Energies, MDPI, vol. 15(6), pages 1-26, March.
    8. Hafiz Majid Hussain & Nadeem Javaid & Sohail Iqbal & Qadeer Ul Hasan & Khursheed Aurangzeb & Musaed Alhussein, 2018. "An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid," Energies, MDPI, vol. 11(1), pages 1-28, January.
    9. Danish Mahmood & Nadeem Javaid & Sheraz Ahmed & Imran Ahmed & Iftikhar Azim Niaz & Wadood Abdul & Sanaa Ghouzali, 2017. "Orchestrating an Effective Formulation to Investigate the Impact of EMSs (Energy Management Systems) for Residential Units Prior to Installation," Energies, MDPI, vol. 10(3), pages 1-25, March.
    10. Muhammad Babar Rasheed & Nadeem Javaid & Ashfaq Ahmad & Mohsin Jamil & Zahoor Ali Khan & Umar Qasim & Nabil Alrajeh, 2016. "Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing," Energies, MDPI, vol. 9(8), pages 1-25, July.
    11. Sławomir Zator, 2021. "Power Scheduling Scheme for DSM in Smart Homes with Photovoltaic and Energy Storage," Energies, MDPI, vol. 14(24), pages 1-20, December.
    12. Muhammad Babar Rasheed & Nadeem Javaid & Muhammad Awais & Zahoor Ali Khan & Umar Qasim & Nabil Alrajeh & Zafar Iqbal & Qaisar Javaid, 2016. "Real Time Information Based Energy Management Using Customer Preferences and Dynamic Pricing in Smart Homes," Energies, MDPI, vol. 9(7), pages 1-30, July.
    13. Andrzej Ożadowicz, 2017. "A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies," Energies, MDPI, vol. 10(11), pages 1-22, November.
    14. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.

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