Sensorless finite set predictive current control with MRAS estimation for optimized performance of standalone DFIG in wind energy systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256274" target="_blank" >RIV/61989100:27240/24:10256274 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/24:10256274
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590123024018656?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123024018656?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rineng.2024.103622" target="_blank" >10.1016/j.rineng.2024.103622</a>
Alternative languages
Result language
angličtina
Original language name
Sensorless finite set predictive current control with MRAS estimation for optimized performance of standalone DFIG in wind energy systems
Original language description
This paper introduces a sensorless control strategy combining Finite-Set Predictive Current Control (FSPCC) and Model Reference Adaptive System (MRAS) estimation to enhance the performance of standalone Doubly-Fed Induction Generators (DFIG) in wind energy systems. Addressing the challenges of cost and reliability, the proposed approach eliminates mechanical speed sensors by employing MRAS for real-time rotor speed and position estimation. FSPCC predicts rotor current one step ahead (K + 1), enabling precise control, optimal switching state selection, and improved current regulation with reduced ripple. The significance of this study lies in its potential to advance standalone wind energy systems by providing a robust, efficient, and reduced cost and effective solution for sensorless operation. The proposed strategy was experimentally validated using a 3 kW DFIG coupled with a turbine emulator, connected to a three-phase resistive load, and managed via a DS1104 control board. The system was tested under diverse operational conditions, including sudden load variations and dynamic speed changes, simulating real-time wind energy scenarios. The results demonstrate exceptional robustness and adaptability, with accurate speed estimation, effective voltage regulation, stable current waveforms, and enhanced power quality. The system also exhibited improved reactive power handling, ensuring smooth transitions under fluctuating loads and mitigating power oscillations. By addressing critical challenges in standalone DFIG applications, this work highlights the importance of integrating FSPCC and MRAS as a promising control solution. The results confirm its potential to improve system stability, efficiency, and reliability, offering significant advancements in renewable energy technologies and optimizing the performance of wind energy conversion systems. Also, this combination isn't applied before in the field in can be applied in many other fields like electric vehicles, robotics, aerospace systems and marines.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Results in Engineering
ISSN
2590-1230
e-ISSN
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Volume of the periodical
24
Issue of the periodical within the volume
December 2024
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
1-17
UT code for WoS article
001386053500001
EID of the result in the Scopus database
2-s2.0-85211473195