Integrated Control Design for Hybrid Grid-Photovoltaic Systems in Distillation Applications: A Reference Model and Fuzzy Logic Approach

This paper presents a novel hybrid structural control solution designed for distillation systems that utilize a solar source alongside an electrical grid. The power conversion architecture incorporates a reversible bridge rectifier and a quadratic boost converter. The hybrid photovoltaic grid configuration offers several benefits, including source complementarity, enhanced dependability, and energy availability aligned with power requirements. Leveraging a photovoltaic source operating at maximum power facilitates energy conservation. On the control front, an adaptive technique based on a reference model is proposed. Fuzzy logic governs the quadratic boost converter, simplifying the management of its complex nonlinear nature. The control strategy aims to maximize solar power utilization, minimize harmonic components in the grid current, synthesize an adaptive controller, and achieve a near-unit power factor on the grid. The simulation results for a steady distillation system demonstrate promising findings. Despite variations in irradiation, load power, and grid drops, the system maintains a minimal bus voltage ripple, remaining close to the intended value. Optimization of the panel-generated power leads to improved PV source utilization and enhanced system efficiency. Furthermore, the combination with an electrical grid achieves a low rate of grid current distortion and a unitary power factor.

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Publication Details

Journal
Sustainability
Published
2024-08-25
DOI
https://doi.org/10.3390/su16177304
Citations
4
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.41

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article

Integrated Control Design for Hybrid Grid-Photovoltaic Systems in Distillation Applications: A Reference Model and Fuzzy Logic Approach

Baheej Alghamdi, Habib Kraiem, Safeer Ullah, Youssef Mchaouar et al.
4 citations
Sustainability
Photovoltaic System Optimization Techniques
0.41
article

Integrated Control Design for Hybrid Grid-Photovoltaic Systems in Distillation Applications: A Reference Model and Fuzzy Logic Approach

Baheej Alghamdi, Habib Kraiem, Safeer Ullah, Youssef Mchaouar, Hassan Abouobaida, Hisham Alghamdi, Younes Abouelmahjoub
article en
4 citations

Abstract

This paper presents a novel hybrid structural control solution designed for distillation systems that utilize a solar source alongside an electrical grid. The power conversion architecture incorporates a reversible bridge rectifier and a quadratic boost converter. The hybrid photovoltaic grid configuration offers several benefits, including source complementarity, enhanced dependability, and energy availability aligned with power requirements. Leveraging a photovoltaic source operating at maximum power facilitates energy conservation. On the control front, an adaptive technique based on a reference model is proposed. Fuzzy logic governs the quadratic boost converter, simplifying the management of its complex nonlinear nature. The control strategy aims to maximize solar power utilization, minimize harmonic components in the grid current, synthesize an adaptive controller, and achieve a near-unit power factor on the grid. The simulation results for a steady distillation system demonstrate promising findings. Despite variations in irradiation, load power, and grid drops, the system maintains a minimal bus voltage ripple, remaining close to the intended value. Optimization of the panel-generated power leads to improved PV source utilization and enhanced system efficiency. Furthermore, the combination with an electrical grid achieves a low rate of grid current distortion and a unitary power factor.

SustainabilityVol. 16(17)
Northern Border University (SA), Quaid-i-Azam University (PK), King Abdulaziz University (SA), Chouaib Doukkali University (MA), Najran University (SA)
Northern Borders University, Northern Border University
Affordable and clean energy
Openalex Percentile: Top 48%
Photovoltaic System Optimization Techniques
0.41
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