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Scheduling for electricity cost in a smart grid

Author

Listed:
  • Mihai Burcea

    (University of Liverpool)

  • Wing-Kai Hon

    (National Tsing Hua University)

  • Hsiang-Hsuan Liu

    (University of Liverpool
    National Tsing Hua University)

  • Prudence W. H. Wong

    (University of Liverpool)

  • David K. Y. Yau

    (Singapore University of Technology and Design)

Abstract

We study an offline scheduling problem arising in demand response management in a smart grid. Consumers send in power requests with a flexible set of timeslots during which their requests can be served. For example, a consumer may request the dishwasher to operate for 1 h during the periods 8am to 11am or 2pm to 4pm. The grid controller, upon receiving power requests, schedules each request within the specified duration. The electricity cost is measured by a convex function of the load in each timeslot. The objective of the problem is to schedule all requests with the minimum total electricity cost. As a first attempt, we consider a special case in which the power requirement and the duration a for which a request needs service are both unit-size. For this problem, we present a polynomial time offline algorithm that gives an optimal solution and shows that the time complexity can be further improved if the given set of timeslots forms a contiguous interval.

Suggested Citation

  • Mihai Burcea & Wing-Kai Hon & Hsiang-Hsuan Liu & Prudence W. H. Wong & David K. Y. Yau, 2016. "Scheduling for electricity cost in a smart grid," Journal of Scheduling, Springer, vol. 19(6), pages 687-699, December.
    • Handle: RePEc:spr:jsched:v:19:y:2016:i:6:d:10.1007_s10951-015-0447-8
    DOI: 10.1007/s10951-015-0447-8
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    References listed on IDEAS

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    1. Paul C. Bell & Prudence W. H. Wong, 2015. "Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines," Journal of Combinatorial Optimization, Springer, vol. 29(4), pages 739-749, May.
    2. Minoux, M., 1984. "A polynomial algorithm for minimum quadratic cost flow problems," European Journal of Operational Research, Elsevier, vol. 18(3), pages 377-387, December.
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