Real-time particle swarm optimization based current harmonic cancellation

  • Authors:

  • Wenxin Liu;Il-Yop Chung;Li Liu;Siyu Leng;David A. Cartes

  • Affiliations:

  • Klipsch School of Electrical and Computer Engineering, New Mexico State University, Thomas and Brown Hall, Rm. 114, Las Cruces, NM 88003, USA;School of Electrical Engineering, Kookmin University, 861-1 Jeongneung-dong, Seongbuk-gu, Seoul, 136-702, Korea;Controls-Common, Cummins Inc., 1460N. National Rd, Columbus, IN 47201, USA;Center for Advanced Power Systems, Florida State University, 2000 Levy Avenue, Tallahassee, FL 32310, USA;Center for Advanced Power Systems, Florida State University, 2000 Levy Avenue, Tallahassee, FL 32310, USA

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2011

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Abstract

As a powerful optimization algorithm, particle swarm optimization (PSO) has been widely applied to power system researches. However, most existing applications of PSO can only be implemented offline. The difficulties of online implementation mainly come from the unavoidable lengthy simulation time to evaluate a candidate solution. Recently, PSO was implemented online that can identify parameters in a motor control systems. In this paper, the real-time PSO (RT-PSO) based identification technique is applied to cancel current harmonics in power systems. By transforming the identification problem to optimization problem, RT-PSO can simultaneously identify four parameters associated with fundamental current from measurement. In this way, there is no need to identify the fundamental frequency separately or construct fundamental signal from identified harmonic information. The identification algorithm can be applied to three-phases independently, even for unbalanced system or single-phase system. The identified fundamental signal is then used as the reference for current harmonics cancellation. The RT-PSO based harmonic cancellation is realized with an active filter and used to compensate harmonic current created by a nonlinear load. Simulation results demonstrate that the RT-PSO algorithm can provide accurate identification of the fundamental current which in turn will result in good harmonic cancellation performance. As a capable online optimization technique, RT-PSO can be extensively applied to many optimization and control problems.