The role of AI planning as a decision support tool in power substation management

  • Authors:

  • Keith Bell;Amanda Coles;Andrew Coles;Maria Fox;Derek Long

  • Affiliations:

  • Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK. E-mail: keith.bell@eee.strath.ac.uk;(Correspd. E-mail: andrew.coles@cis.strath.ac.uk) Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK. E-mails: {firstname.lastname}@cis.strath.ac.uk;Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK. E-mails: {firstname.lastname}@cis.strath.ac.uk;Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK. E-mails: {firstname.lastname}@cis.strath.ac.uk;Department of Computer and Information Sciences, University of Strathclyde, Glasgow, UK. E-mails: {firstname.lastname}@cis.strath.ac.uk

  • Venue:
  • AI Communications
  • Year:
  • 2009

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Abstract

The management of power substations is a challenging task, with two opposing criteria: to reduce wear-and-tear on equipment and to ensure the voltage remains within a specified range. At present, a two-stage process is used. Voltage targets are determined for each time of day by electrical engineers using a time-consuming and costly manual process. Then, a reactive control system at the substation is used to satisfy these targets. In this article, we present a novel application of AI planning as part of an intelligent automated system for devising voltage targets. Within the system, both the cost and fault-tolerance implications of voltage target decisions are considered, and hence an efficient and effective set of voltage targets is produced. Using AI planning affords a great deal of flexibility and we show how the system can handle known exogenous events for a given day to reduce forecasted operational costs.