Micro-Grid Wind Energy Conversion Systems: Conventional and Modern Embedded Technologies - A Review
This study assesses the effectiveness of an electric microgrid wind energy conversion system using both traditional techniques and contemporary embedded systems, such as artificial neural network-based control mechanisms and fuzzy logic control. The text compares and lists the advantages and disadv...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
UJ Press
2024-12-01
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| Series: | Journal of Digital Food, Energy & Water Systems |
| Subjects: | |
| Online Access: | https://journals.uj.ac.za/index.php/DigitalFoodEnergy_WaterSystems/article/view/3341 |
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| Summary: | This study assesses the effectiveness of an electric microgrid wind energy conversion system using both traditional techniques and contemporary embedded systems, such as artificial neural network-based control mechanisms and fuzzy logic control. The text compares and lists the advantages and disadvantages of various types of wind turbines (WTs). Moreover, this control falls into one of two groups: conventional power control or non-traditional power control. On the other side, conventional control describes methods of control such as manually controlling the turbine rotor's rotation speed and using computational analysis. The current work, in contrast, investigates and evaluates contemporary embedded control techniques used in wind energy conversion systems (WECS), including maximum power point tracking, Artificially intelligent control systems, in relation to the control mechanism, provide complete control over the pitch angle, power coefficient, and tip speed ratio for the best possible wind energy extraction. This makes a direct comparison possible. Nonetheless, there are a few drawbacks and difficulties with the two widely utilized contemporary techniques for power quality extractions: artificially intelligent neural networks and their embedded control systems. However, combining contemporary technology with integrated artificial intelligence controllers may be a workable strategy to lessen and even eliminate these difficulties, as well as advantageous for upcoming studies.
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| ISSN: | 2709-4510 2709-4529 |