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Enhancing Optimal Automatic Generation Control in a Multi-Area Power System with Diverse Energy Resources

  • Ragini Patel*
  • , Chaojie Li
  • , Lasantha Meegahapola
  • , Brendan McGrath
  • , Xinghuo Yu
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

New power system control methodologies have recently been proposed that combine economic dispatch (ED) and automatic generation control (AGC) in order to maintain economic operation when the generation mix incorporates a high penetration of renewable energy sources. The theoretical framework that underpins these techniques assumes that an aggregated control area (CA) model can be defined, assuming that the dynamic response of the entire CA is dominated by a single energy source, typically a steam-turbine generator. This paper investigates a combined AGC and ED control methodology for a power system with CAs containing multiple hybrid energy resources that cannot be simply aggregated into a single equivalent source. An optimization approach is then used to develop a control law and parameter design algorithm for each energy source, which accounts for their individual dynamics while aggregating the generators output to match with the target output of the CA. The performance of the proposed AGC and ED controller is demonstrated using simulation studies of an interconnected power system, conducted within the DIgSILENT power factory platform. This model incorporates non-linear network system dynamics and control loops within automatic voltage regulators and power system stabilizers. The study results indicate that the proposed AGC optimal control strategy offers superior performance compared to traditional and recently published economic AGC strategies, particularly when the generation mix includes both dispatchable conventional sources and a high penetration of non-dispatchable or semi-dispatchable sources such as wind. © 2019 IEEE.
Original languageEnglish
Pages (from-to)3465-3475
Number of pages11
JournalIEEE Transactions on Power Systems
Volume34
Issue number5
Online published1 Apr 2019
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Funding

This work was supported in part by the Australian Research Council Discovery Program under Grant #DP170102303. Paper no. TPWRS-00856-2018.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • Automatic generation control (AGC)
  • combined-cycle gas turbines (CCGTs)
  • generation portfolio
  • interconnected power network
  • optimal control
  • renewable energy resources (RESs)
  • steam turbines

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