Particle swarm optimization based fuzzy logic MPPT inverter controller for grid connected wind turbine

K. Parvin, Yoon Khay Kit, Ker Pin Jern, M. M. Hoque, M. A. Hannan

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The wind energy source as an alternative to conventional sources to generate power has been increasingly popular due to abundant in nature and pollution free. The wind energy sources are undepletable, however, they are not able to generate as much electricity due to their intermittent nature. Therefore, a wind energy conversion system (WECS) with accurate maximum power point tracking (MPPT) inverter controller is essential in order to improve the wind energy capturing capability. This paper aims to develop an optimal Fuzzy logic MPPT inverter controller for grid connected wind turbine so that the energy capturing efficiency of the system can be maximized. In this research work, the MPPT inverter controller is designed on the basis of hill climb search method, fuzzy logic control and heuristic particle swarm optimization (PSO) algorithm. The performance of WECS is demonstrated with the generated output voltage, current and power waveforms, DC link voltage waveform, and the generator speed. According to the results obtained for both normal Fuzzy logic MPPT control and optimized Fuzzy logic MPPT control WECS, the performance of PSO optimized Fuzzy logic MPPT inverter controller has better maximum power point performance and efficiency in tracking wind energy in terms of much smooth, less distortion and fewer fluctuation outcomes at the various step wind speed conditions. The proposed optimal Fuzzy logic MPPT inverter controller have a good potentiality for WECS in sustainable grid application.

Original languageEnglish
Pages (from-to)164-174
Number of pages11
JournalInternational Journal of Renewable Energy Research
Volume9
Issue number1
Publication statusPublished - 01 Mar 2019

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Wind turbines
Particle swarm optimization (PSO)
Wind power
Fuzzy logic
Controllers
Energy conversion
Electric potential
Energy efficiency
Pollution
Electricity

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology

Cite this

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abstract = "The wind energy source as an alternative to conventional sources to generate power has been increasingly popular due to abundant in nature and pollution free. The wind energy sources are undepletable, however, they are not able to generate as much electricity due to their intermittent nature. Therefore, a wind energy conversion system (WECS) with accurate maximum power point tracking (MPPT) inverter controller is essential in order to improve the wind energy capturing capability. This paper aims to develop an optimal Fuzzy logic MPPT inverter controller for grid connected wind turbine so that the energy capturing efficiency of the system can be maximized. In this research work, the MPPT inverter controller is designed on the basis of hill climb search method, fuzzy logic control and heuristic particle swarm optimization (PSO) algorithm. The performance of WECS is demonstrated with the generated output voltage, current and power waveforms, DC link voltage waveform, and the generator speed. According to the results obtained for both normal Fuzzy logic MPPT control and optimized Fuzzy logic MPPT control WECS, the performance of PSO optimized Fuzzy logic MPPT inverter controller has better maximum power point performance and efficiency in tracking wind energy in terms of much smooth, less distortion and fewer fluctuation outcomes at the various step wind speed conditions. The proposed optimal Fuzzy logic MPPT inverter controller have a good potentiality for WECS in sustainable grid application.",
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Particle swarm optimization based fuzzy logic MPPT inverter controller for grid connected wind turbine. / Parvin, K.; Kit, Yoon Khay; Jern, Ker Pin; Hoque, M. M.; Hannan, M. A.

In: International Journal of Renewable Energy Research, Vol. 9, No. 1, 01.03.2019, p. 164-174.

Research output: Contribution to journalArticle

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