• DocumentCode
    128448
  • Title

    Coordinated control of AGC and AVC by application of Particle Swarm Optimization algorithm

  • Author

    Beisi Tan ; Wei Hu

  • Author_Institution
    Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2014
  • fDate
    9-11 June 2014
  • Firstpage
    690
  • Lastpage
    694
  • Abstract
    Automatic Generation Control (AGC) and Automatic Voltage Control (AVC) are two main control schemes in modern power grid. However, there lacks a coordination between them. Therefore, this paper puts forward a method of coordinated control of AGC and AVC by `simultaneous solution´. The control variables are selected as power outputs and voltage magnitude of the generators to represent AGC and AVC, respectively. We consider the constraints of node voltage magnitude, line power flow etc. and solve the model using Particle Swarm Optimization (PSO). This algorithm is suitable for solving multi-objective optimization problem with constraints. Simulations have been carried out on New England 39-bus system, including AGC only, AVC only and the coordinated control of AGC and AVC. The results show the effectiveness of the control strategy.
  • Keywords
    particle swarm optimisation; power generation control; power grids; voltage control; AGC only; AVC; New England 39-bus system; PSO; automatic generation control; automatic voltage control; control schemes; control strategy; coordinated control; line power flow; multiobjective optimization problem; node voltage magnitude; particle swarm optimization algorithm; power grid; Automatic generation control; Automatic voltage control; Generators; Indexes; Optimization; Reactive power; Automatic Generation Control (AGC); Automatic Voltage Control (AVC); Particle Swarm Optimization (PSO); coordinated control of multi-objective optimization; simultaneous solution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4316-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2014.6931251
  • Filename
    6931251