Voltage security-constrained optimal generation rescheduling for available transfer capacity enhancement in deregulated electricity markets

  • Oludamilare Bode Adewuyi
  • , Mikaeel Ahmadi
  • , Isaiah Opeyemi Olaniyi
  • , Tomonobu Senjyu
  • , Temitayo Olayemi Olowu
  • , Paras Mandal

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Modern utilities are forced to operate very close to their loadable limits (maximum capacity) due to geographical, economical and some technical reasons. The deregulation of the power industry, the competitive nature of modern electricity markets and the continuous quest for modernization of cities and hamlets all over the world has also led to fast increase in the load demand. The stability of power systems all over the world are threatened with recurrent occurrences of voltage stability issues. Hence, Inter-zonal energy transactions between willing supplier and buyers need to be done with adequate consideration for power system security. In this work, a voltage security-constrained optimal generator active and reactive power rescheduling is carried out using the IEEE 30 and IEEE 57 bus systems. The simultaneous maximization of available transfer capacity (ATC) and voltage stability margin (VSM), using the weighted sum approach, is the objective function. Credible optimal power flow and power system security constraints are considered. Three variants of particle swarm optimization in MATLAB® are used in this work for analyzing the results for objectivity. The technical and economic benefits of the optimal generator rescheduling on the system’s ATC, VSM, line losses, line flow and voltage profile are adequately analyzed.

Original languageEnglish
Article number4371
JournalEnergies
Volume12
Issue number22
DOIs
StatePublished - Nov 17 2019
Externally publishedYes

Keywords

  • Available transfer capacity
  • Critical boundary index
  • Deregulated electricity market
  • Particle swarm optimization
  • Voltage security-constrained OPF
  • Weighted sum algorithm

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