| Title: | Performance Enhancement of Grid Connected Multilevel Inverter Based Wind Energy Conversion System with LVRT Capability Using Optimized Type 2 ANFIS Based DVR |
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| Authors: | ID Sajan, Ch. (Author)
ID Satish Kumar, P. (Author)
ID Virtič, Peter (Author) |
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| Files: |  Sajan_2024_Performance_Enhancement_of_Grid_Connected.pdf (2,47 MB)
MD5: CA7B2E0B45989A27469278FEDB363EB8
 https://doi.org/10.14445/23488379/IJEEE-V11I10P124
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FE - Faculty of Energy Technology
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| Abstract: | A Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System (WECS) holds significant importance in the realm of Renewable Energy Sources (RES) for several reasons. The permanent magnets in the generator eliminate the need for a separate excitation system, leading to improved efficiency in power conversion. This makes PMSG-based WECS an effective and reliable source of wind energy electricity. The motivation behind the proposed conceptual framework stems from the need to overcome the limitations related to the integration of RES into the power grid, specifically focusing on voltage stability and Low Voltage Ride Through (LVRT) capability of PMSG based WECS. A Dynamic Voltage Restorer (DVR), empowered by an energy storage device, is used to mitigate voltage fluctuations and disturbances. The input DC voltage to the DVR is intricately regulated by a Type 2 Adaptive Neuro Fuzzy Inference System (ANFIS) Controller optimized using the Seagull algorithm, exhibiting intelligent adaptability to dynamic conditions. The rectified output from the WECS transforms an Isolated Flyback converter. Subsequently, a 31-Level Cascaded H-Bridge Multilevel Inverter (CHBMLI) along with a Proportional-Integral (PI) controller aids in generating high-quality AC output. By addressing challenges related to voltage stability and the ability to ride through low-voltage conditions, the proposed work contributes to enhanced grid stability. The use of advanced control techniques, including the Type 2 ANFIS Controller optimized by the Seagull algorithm, adds a layer of intelligent adaptability to changing environmental and grid conditions. A lower Total Harmonic Distortion (THD) Value of 1.29% is shown during the validation of the created system utilizing MATLAB/Simulink, assuring significant LVRT capabilities. |
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| Keywords: | Permanent Magnet Synchronous Generator (PMSG), Wind Energy Conversion System (WECS), Renewable Energy Sources (RES), Low Voltage Ride Through (LVRT), Type 2 Adaptive Neuro Fuzzy Inference System, 31-Level CHBMLI, Proportional-Integral (PI) |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 16.08.2024 |
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| Article acceptance date: | 17.10.2024 |
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| Publication date: | 30.10.2024 |
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| Publisher: | Seventh Sense Research Group |
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| Year of publishing: | 2024 |
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| Number of pages: | Str. 231-248 |
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| Numbering: | Letn. 11, št. 10 |
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| PID: | 20.500.12556/DKUM-93738  |
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| UDC: | 621.3 |
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| ISSN on article: | 2348-8379 |
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| COBISS.SI-ID: | 232277763 |
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| DOI: | 10.14445/23488379/IJEEE-V11I10P124 |
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| Publication date in DKUM: | 06.11.2025 |
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| Views: | 132 |
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| Downloads: | 10 |
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| Metadata: |    |
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| Categories: | Misc.
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