Abstract
Recently, wind power generation systems have seen significant developments aimed at improving performance and efficiency. Permanent magnet synchronous generators (PMSG) are essential for wind power production systems because of their exceptional power density, high efficiency, and dependable operation. These properties enable PMSGs to effectively convert wind energy into electrical energy with minimal losses and high accuracy. This study proposes an enhanced control system for wind power generation using permanent magnet synchronous generators (PMSG), integrating artificial neural networks (ANN) and predictive current control (PCC) techniques to optimize efficiency and dynamic performance.
| Original language | English |
|---|---|
| Pages (from-to) | 157-181 |
| Number of pages | 25 |
| Journal | Solar Energy and Sustainable Development |
| Volume | 14 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jun 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Artificial Neural Networks (ANN)
- Grid Integration
- Maximum Power Point Tracking (MPPT)
- Permanent Magnet Synchronous Generator (PMSG)
- Predictive Current Control (PCC)
- Wind Energy Conversion System (WECS)
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Environmental Engineering
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