Adaptive Regulated Sparsity Promoting Approach for Data-Driven Modeling and Control of Grid-Connected Solar Photovoltaic Generation Article Swipe

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Zhongtian Zhang , Javad Khazaei , Rick S. Blum ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2404.19028

This paper aims to introduce a new statistical learning technique based on sparsity promoting for data-driven modeling and control of solar photovoltaic (PV) systems. Compared with conventional sparse regression techniques that might introduce computational complexities when the number of candidate functions increases, an innovative algorithm, named adaptive regulated sparse regression (ARSR) is proposed that adaptively regulates the hyperparameter weights of candidate functions to best represent the dynamics of PV systems. Utilizing this algorithm, open-loop and closed-loop models of single-stage and two-stage PV systems are obtained from measurements and are utilized for control design purposes. Moreover, it is demonstrated that the proposed data-driven approach can successfully be employed for fault analysis studies, which distinguishes its capabilities compared with other data-driven techniques. Finally, the proposed approach is validated through real-time simulations.

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Photovoltaic System

Computer Science

Electronic Engineering

Electrical Engineering

Engineering

Artificial Intelligence

Mathematics

Geometry

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Photovoltaic system Grid Computer science Control (management) Electronic engineering Distributed computing Electrical engineering Engineering Artificial intelligence Mathematics Geometry

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2404.19028
PDF: https://arxiv.org/pdf/2404.19028
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4396821304

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OpenAlex ID: https://openalex.org/W4396821304

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DOI: https://doi.org/10.48550/arxiv.2404.19028

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Title: Adaptive Regulated Sparsity Promoting Approach for Data-Driven Modeling and Control of Grid-Connected Solar Photovoltaic Generation

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-04-29

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Authors: Zhongtian Zhang, Javad Khazaei, Rick S. Blum

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Landing page: https://arxiv.org/abs/2404.19028

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PDF URL: https://arxiv.org/pdf/2404.19028

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OA URL: https://arxiv.org/pdf/2404.19028

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Concepts: Photovoltaic system, Grid, Computer science, Control (management), Electronic engineering, Distributed computing, Electrical engineering, Engineering, Artificial intelligence, Mathematics, Geometry

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Cited by: 0

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Related works (count): 10

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