Considering fairness in the load shedding scheduling problem

  • RG Rakotonirainy Department of Statistical Sciences, University of Cape Town https://orcid.org/0000-0002-1672-2695
  • I Durbach Center for Statistics in Ecology, the Environment, and Conservation, Department of Statistical Sciences, University of Cape Town
  • J Nyirenda Department of Statistical Sciences, University of Cape Town

Abstract

Every day national power system networks provide thousands of MW of electric power from generating units to consumers, requiring different operations and planning to ensure secure systems. Where demand exceeds supply, load shedding - controlled, enforced reduction in supply - is necessary to prevent system collapse. Should load shedding need to be implemented, a planned schedule is necessary to allocate geographic areas on the required period of shedding. The problem of how to construct a schedule that fairly allocates load shedding responsibilities over geographic areas with minimum economic impacts is addressed in this paper. Two programming models are proposed. The first model consists of a linear integer programming model in which the objective is to minimise the economic cost subject to different fairness allocation constraints, while the second model involves formulation of the problem as a goal programming model in which different conflicting goals are simultaneously optimised. Several case studies are conducted in the context of a realistic, but hypothetical, scenario to explore the possible solutions that the proposed models provide. Results show that a fair schedule requires a high cost whereas lower cost can only be achieved with some sacrifices to the fairness of the schedule.

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Author Biographies

RG Rakotonirainy, Department of Statistical Sciences, University of Cape Town
Lecturer, Department of Statistical Sciences, Uiniversity of Cape Town
I Durbach, Center for Statistics in Ecology, the Environment, and Conservation, Department of Statistical Sciences, University of Cape Town
Associate Professor, Department of Statistical Sciences, University of Cape Town
J Nyirenda, Department of Statistical Sciences, University of Cape Town
Senior Lecturer, Department of Statistical Sciences, University of Cape Town
Published
2019-12-20
Section
Research Articles