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Power Management in Smart Grid for Residential Consumers

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 13))

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Abstract

In this paper we have studied the power management for residential area. A proper load management brought fruitful results in term of Peak to Average Ratio (PAR) reduction and electricity cost. In order to achieve these objectives, we provide an energy management structure to perform scheduling on the basis of Genetic Algorithm (GA) and Fish Swarm Optimization (FSO). Time Of Use (TOU) pricing scheme has been used to calculate electricity cost. After experiments a noticeable difference has been found in the performance of our proposed algorithms GA and FSO. GA provides us better results in term of energy consumption and PAR reduction as compared to FSO. However, FSO performs more efficiently than GA in term of electricity cost reduction.

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Authors and Affiliations

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

    Muhammad Shahid Saeed, Adia Khalid, Anila yasmeen, Muhammad Awais Younas & Nadeem Javaid

  2. National University of Science and Technology, Islamabad, 44000, Pakistan

    Zunaira Nadeem

  3. University of Engineering and Technology, Lahore, 54890, Pakistan

    Syed Zain Raza

Authors
  1. Muhammad Shahid Saeed
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  2. Adia Khalid
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  3. Anila yasmeen
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  4. Zunaira Nadeem
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  5. Muhammad Awais Younas
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  6. Syed Zain Raza
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  7. Nadeem Javaid
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Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Open University of Catalonia, Barcelona, Spain

    Santi Caballé

  3. Fukuoka Institute of Technology (FIT), Fukuoka, Japan

    Leonard Barolli

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Saeed, M.S. et al. (2018). Power Management in Smart Grid for Residential Consumers. In: Xhafa, F., Caballé, S., Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-69835-9_39

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  • DOI: https://doi.org/10.1007/978-3-319-69835-9_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69834-2

  • Online ISBN: 978-3-319-69835-9

  • eBook Packages: EngineeringEngineering (R0)

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