Adaptive Neuro-Fuzzy Voltage Control for LCL-Filter Grid-Connected Converter

Olwie, Safa S.; Humod, Abdulrahim T.; Hasan, Fadhil A.

doi:10.30684/etj.2022.132342.1115

	Adaptive Neuro-Fuzzy Voltage Control for LCL-Filter Grid-Connected Converter
Engineering and Technology Journal
Article 5, Volume 41, Issue 2, February 2023, Pages 316-332 PDF (2.59 M)
Document Type: Research Paper
DOI: 10.30684/etj.2022.132342.1115
Authors
Safa S. Olwie^* ¹; Abdulrahim T. Humod²; Fadhil A. Hasan³
¹Department of Electrical Engineering, University of Technology -Baghdad- Iraq
²b Department of Electrical Engineering, University of Technology, Baghdad - Iraq
³Department of Electrical Engineering, University of Technology ,Baghdad - Iraq
Abstract
Inductance – Capacitance – Inductance (LCL) filter is a very attractive candidate for renewable energy system applications due to its high efficiency. High attenuation of the switching frequency harmonics, small size, low fee, and improving the overall harmonic distortion (THD). This paper presents how voltage is affected by increased loads or voltage sag. Therefore it is necessary to control it with certain controllers. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used as an intelligent controller, the voltage constraint as training data for ANFIS obtained from PI. The filter works in a good connection between the inverter and the grid and rewords unwanted harmonics from using the inverter. The mathematical models for the LCL filter are investigated. The proposed approach shows more effective results than previous performance for voltage controlling and harmonic reduction. It gives overshoot (0.5%), steady state error (0.005), settling time (0.03 sec), rise time (0.005 sec), and improving THD 8.67% to 2.33% by comparing these results of ANFIS respectively with the results of PI which gave(3%),(0.01),(0.2sec)and( 0.02sec).
Highlights
This paper presents how voltage is affected by increased loads or voltage sag. The Adaptive neuro-Fuzzy Inference System (ANFIS) is used as an Intelligent controller. The mathematical models for the LCL filter are investigated. The proposed approach shows more effective results than previous performance for voltage controlling and harmonic reduction.
Keywords
Distributed power generation; LCL filter; mathematical models of LCL filter; PI control; ANFIS

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