Visual Vocabulary Based Photovoltaic Health Monitoring System Using Infrared Thermography

Waqas Ahmed,Amad Zafar,Muhammad Umair Ali,Sulaiman Al Hasani,Shaik Javeed Hussain

doi:10.1109/access.2022.3148138

Waqas Ahmed, Amad Zafar + Show 3 more

Open Access

https://doi.org/10.1109/access.2022.3148138

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Abstract

Photovoltaic (PV) systems have gained global acceptance in terms of green, replenishable energy resources to meet energy demand with no emissions. However, PV systems are susceptible to operational and environmental stresses. Moreover, PV panels monitoring is necessary to keep their performance and efficiency intact due to their lack of supervisory control. Therefore, this study monitors PV panels based on health into three sub-classes: healthy, hotspot, and faulty through infrared thermography. First, Thermographs key points are selected using an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> uniform pixel grid, and speed-up robust features (SURF) are extracted from grid intersection points. Afterward, due to its simplicity, the k-mean clustering algorithm creates single-level clusters based on actual observations similarities and similar observations closeness within-cluster and dissimilarity to other clusters observations are used to transform features into visual words. Finally, shallow classifiers are utilized because of low training time and high prediction speed. After extensive testing and compressive analysis, the proposed approach was found economical, fast, and showed high testing accuracy of 97% through a multi-class shallow classifier (support vector machine) with low computational complexity and less storage size. Thus, this approach can monitor megawatt PV systems with high accuracy and keep performance and emissions mitigation potential high while lowering payback time.

Highlights

Energy is an essential entity in the modern era
While its major production technologies involve dreadful gas emissions such as CO2, NOx, water vapors, etc., known as greenhouse gases (GHG), they are responsible for global warming and climate change
Green renewable energy resources such as solar photovoltaic (PV) systems, wind energy systems, etc., have gained wider acceptance across the globe as the energy security resources owing to energy needs and climatic concerns

Summary

Introduction

Energy is an essential entity in the modern era. While its major production technologies involve dreadful gas emissions such as CO2, NOx, water vapors, etc., known as greenhouse gases (GHG), they are responsible for global warming and climate change. Green renewable energy resources such as solar photovoltaic (PV) systems, wind energy systems, etc., have gained wider acceptance across the globe as the energy security resources owing to energy needs and climatic concerns. Green renewable energy resources, such as PV systems, have a global potential of 1500-50,000 EJ per year [1,2,3,4]. The energy sector has become the leading contributor to global climate change, with 60% of global GHG emissions [5]. Research has focused on green renewable energy resources in multiple aspects

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