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Household Electrical Load Scheduling Algorithms with Renewable Energy

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Wireless Algorithms, Systems, and Applications (WASA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10874))

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Abstract

Efficient household electrical load scheduling benefits not only individual customers by reducing electricity cost but also the society by reducing the peak electricity demand and saving natural resources. In this paper, we aim to design efficient load scheduling algorithms for a household considering both real-time pricing policies and renewable energy sources. We prove that household load scheduling problem is NP-hard. To solve this problem, we propose several algorithms for different scenarios. The algorithms are lightweight and optimal or quasi-optimal, and they are evaluated through simulations.

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Notes

  1. 1.

    \(B=G_t=F_t=0\) if there is no renewable energy system.

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Author information

Authors and Affiliations

  1. School of Computer Science and Information Systems, Northwest Missouri State University, Maryville, MO, 64468, USA

    Zhengrui Qin

  2. Department of Computer Science, College of William and Mary, Williamsburg, VA, 23185, USA

    Qun Li

Authors
  1. Zhengrui Qin
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  2. Qun Li
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Corresponding author

Correspondence to Zhengrui Qin .

Editor information

Editors and Affiliations

  1. University of South Florida, Tampa, Florida, USA

    Sriram Chellappan

  2. Virginia Commonwealth University, Richmond, Virginia, USA

    Wei Cheng

  3. Georgia State University, Atlanta, Georgia, USA

    Wei Li

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Qin, Z., Li, Q. (2018). Household Electrical Load Scheduling Algorithms with Renewable Energy. In: Chellappan, S., Cheng, W., Li, W. (eds) Wireless Algorithms, Systems, and Applications. WASA 2018. Lecture Notes in Computer Science(), vol 10874. Springer, Cham. https://doi.org/10.1007/978-3-319-94268-1_32

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  • DOI: https://doi.org/10.1007/978-3-319-94268-1_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94267-4

  • Online ISBN: 978-3-319-94268-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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