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Home Energy Management Using Hybrid Meta-heuristic Optimization Technique

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Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 773))

Abstract

Home energy management systems have been widely used for energy management in smart homes. Management of energy in smart home is a difficult task and requires efficient scheduling for smart appliances in a home. A meta-heuristic optimization technique is proposed in this paper. The proposed Harmony Search Gray Wolf Optimization (HSGWO) is a hybrid of Harmony Search Algorithm (HSA) and Gray Wolf Optimization (GWO). The pricing signal used for the calculation of electricity cost is Real Time Pricing (RTP). The basic aim of this paper is to reduce electricity cost, Peak to Average Ratio (PAR) and maximization of user comfort. Simulation results show that HSGWO performs better as compared to HSA and GWO. The findings demonstrate that there is a trade off between electricity cost and user comfort.

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Author information

Authors and Affiliations

  1. Department of Computing and Technology, Abasyn University, Islamabad, 44000, Pakistan

    Orooj Nazeer & Zeeshan Khurshid

  2. COMSATS Institute of Information Technology, Islamabad, 44000, Pakistan

    Nadeem Javaid

  3. University of Poonch, Rawalakot, 12350, Azad Kashmir, Pakistan

    Adnan Ahmed Rafique

  4. Allama Iqbal Open University, Islamabad, 44000, Pakistan

    Sajid Kiani

  5. Government College of Technology (TEVTA), Rawalakot, 12350, Azad Kashmir, Pakistan

    Yasir Javaid

Authors
  1. Orooj Nazeer
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  2. Nadeem Javaid
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  3. Adnan Ahmed Rafique
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  4. Sajid Kiani
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  5. Yasir Javaid
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  6. Zeeshan Khurshid
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Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  3. Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan

    Nadeem Javaid

  4. Rissho University, Tokyo, Japan

    Tomoya Enokido

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Nazeer, O., Javaid, N., Rafique, A.A., Kiani, S., Javaid, Y., Khurshid, Z. (2019). Home Energy Management Using Hybrid Meta-heuristic Optimization Technique. In: Barolli, L., Xhafa, F., Javaid, N., Enokido, T. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2018. Advances in Intelligent Systems and Computing, vol 773. Springer, Cham. https://doi.org/10.1007/978-3-319-93554-6_58

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