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Total Size:
6.9 MB
Info Hash:
306C7038D93403B18E00C13EEEEF8FD92C44875E
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Added:
Aug. 13, 2025, 12:45 p.m.
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(Last updated: Aug. 13, 2025, 12:46 p.m.)
| File | Size |
|---|---|
| Mensia N. Innovative Solutions in Simulation, Modelling...Photovoltaic Sys. 2026.pdf | 6.9 MB |
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DL
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428.4 MB
[31
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10]
2023-07-01
| Uploaded by Pornlake | Size 428.4 MB | Health [ 31 /10 ] | Added 2023-07-01 |
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241.2 MB
[17
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14]
2023-07-01
| Uploaded by Pornlake | Size 241.2 MB | Health [ 17 /14 ] | Added 2023-07-01 |
NOTE
SOURCE: Mensia N. Innovative Solutions in Simulation, Modelling...Photovoltaic Sys. 2026
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COVER
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MEDIAINFO
Textbook in PDF format This book provides innovative methods for simulating, modeling, and controlling photovoltaic systems. The authors introduce a modeling strategy including eight linear models pondered by nonlinear weighting functions that are calculated dynamically based on extreme temperature and irradiance values. The authors demonstrate how the parameters of each model are harnessed to develop a partial PI controller aimed at commanding the corresponding model to achieve the desired performances swiftly and precisely. The books goes on to show how merging the gains of the partial PI controllers with the nonlinear weighting functions, the PI controller gain for the PV system can be effectively determined. The authors present the results of simulation performed in MatLAB/Simulink environment to demonstrate the model's ability to depict accurately the behavior of the PV system across all operative zones and under varying climatic conditions. Furthermore, the authors show how the results demonstrate the effectiveness of the proposed PI controller in swiftly and precisely tracking the maximum PowerPoint while maintaining stability and canceling ripples. The book is organized into three detailed chapters. It begins with a comparative analysis of traditional Maximum PowerPoint Tracking (MPPT) algorithms—Perturb & Observe and Incremental Conductance. These techniques are meticulously examined using MatLAB/Simulink simulations under both standard and varying climatic conditions. In the second chapter, a high-performance and adaptable modeling method is introduced, based on a multi-model approach specifically designed for PV water-pumping applications. This methodology represents the PV system's behavior under varying environmental conditions through a multi-model structure established using a convex polytopic transformation. The structure comprises eight linear local models, assigned using nonlinear weighting factors to ensure a dynamic and accurate representation of system performance. The simulation results highlight the model’s accuracy in capturing system behavior and optimizing energy output across a range of operating conditions. The final chapter builds on this methodology by introducing an adaptive proportional-integral controller developed within the same multi-model framework. This controller, designed for real-time implementation, showcases outstanding performance in achieving quick, stable, and precise MPP tracking while canceling output oscillations. Its scalability and compatibility with embedded platforms make it a practical and forward-thinking solution for renewable energy systems. Together, these advancements provide researchers and engineers with powerful tools to enhance the reliability, responsiveness, and efficiency of PV systems
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