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An Inventive Method for Eco-Efficient Operation of Home Energy Management Systems

Author

Listed:
  • Bilal Hussain

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Nadeem Javaid

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Qadeer Ul Hasan

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Sakeena Javaid

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Asif Khan

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Shahzad A. Malik

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

Abstract

A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is proposed to develop a scheme for eco-efficient operation of HEMS. The proposed method provides the trade-off between the net cost of energy ( C E n e t ) and the time-based discomfort ( T B D ) due to shifting of home appliances (HAs). At step-1, primary trade-offs for C E n e t , T B D and minimal emissions T E M i s s are generated through a heuristic method. This method takes into account photovoltaic availability, the state of charge, the related rates for the storage system, mixed shifting of HAs, inclining block rates, the sharing-based parallel operation of power sources, and selling of the renewable energy to the utility. The search has been driven through multi-objective genetic algorithm and Pareto based optimization. A filtration mechanism (based on the trends exhibited by T E M i s s in consideration of C E n e t and T B D ) is devised to harness the trade-offs with minimal emissions. At step-2, a constraint filter based on the average value of T E M i s s is used to filter out the trade-offs with extremely high values of T E M i s s . At step-3, another constraint filter (made up of an average surface fit for T E M i s s ) is applied to screen out the trade-offs with marginally high values of T E M i s s . The surface fit is developed using polynomial models for regression based on the least sum of squared errors. The selected solutions are classified for critical trade-off analysis to enable the consumer choice for the best options. Furthermore, simulations validate our proposed method in terms of aforementioned objectives.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3091-:d:181559
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    References listed on IDEAS

    as
    1. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    2. Muqaddas Naz & Zafar Iqbal & Nadeem Javaid & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes," Energies, MDPI, vol. 11(2), pages 1-25, February.
    3. 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.
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