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Residential Area Power Management Using Genetic Algorithm and Biogeography Based Optimization in Smart Grid

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Advances in Network-Based Information Systems (NBiS 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

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Abstract

For residential consumers demand of energy is a main issue. To resolve this issue different techniques are being proposed. In this paper, our focus is on shifting the load from on-peak hours to off-peak hours to minimize peak to average ratio (PAR) and electricity cost. To fulfill these requirements, we adapt two heuristic algorithms, genetic algorithm (GA) and biogeography based optimization (BBO) algorithm. For energy pricing, we use real time pricing (RTP) scheme. Results demonstrate that the proposed algorithm minimize the PAR and electricity bill.

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Author information

Authors and Affiliations

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

    Rubab Maroof, Hasan Nasir Khan, Khadija Ambreen, Hina Iftikhar, Salma Asif & Nadeem Javaid

Authors
  1. Rubab Maroof
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  2. Hasan Nasir Khan
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  3. Khadija Ambreen
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  4. Hina Iftikhar
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  5. Salma Asif
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  6. Nadeem Javaid
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Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

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

    Leonard Barolli

  2. Rissho University, Tokyo, Japan

    Tomoya Enokido

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

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© 2018 Springer International Publishing AG

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Maroof, R., Khan, H.N., Ambreen, K., Iftikhar, H., Asif, S., Javaid, N. (2018). Residential Area Power Management Using Genetic Algorithm and Biogeography Based Optimization in Smart Grid. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_68

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  • DOI: https://doi.org/10.1007/978-3-319-65521-5_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

  • eBook Packages: EngineeringEngineering (R0)

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