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A novel TCSC planning model based on line flow equations via MILP

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

As a useful tool for combinatorial optimisation over continuous and discrete variables, the mixed-integer linear programming (MILP) approach can address complex control and planning models providing high computational efficiency as well as robust behavior. On power system planning, previous work using MILP employed conventional dc load flow model neglecting reactive power, power loss and transformer tap ratios. In this paper, a novel thyristor-controlled series compensator (TCSC) allocation model is proposed based on recently reported line flow equations and basic linearisation rule of binary-continuous products. The objectives of the planning strategy are to improve system loadability by choosing proper locations and settings of devices. Simulation results are presented and discussed for IEEE 9- and 118-bus systems. © 2007 IEEE.
Original languageEnglish
Title of host publication2007 IEEE Power Engineering Society General Meeting, PES
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE Power Engineering Society General Meeting, PES - Tampa, FL, United States
Duration: 24 Jun 200728 Jun 2007

Publication series

Name2007 IEEE Power Engineering Society General Meeting, PES

Conference

Conference2007 IEEE Power Engineering Society General Meeting, PES
PlaceUnited States
CityTampa, FL
Period24/06/0728/06/07

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Evolutionary algorithms
  • Flexible ac transmission system
  • Line flow based equations
  • Linear programming
  • Loadability
  • Mixed-integer linear programming

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