Why PV panels must be recycled at the end of their economic life span? A case study on recycling together with the global situation

ARTAŞ, Sultan Büşra; KOCAMAN, Emrullah; Bilgiç, Hasan Hüseyin; Tutumlu, Hakan; Yağlı, Hüseyin; Yumrutaş, Recep

doi:10.1016/j.psep.2023.03.053

Cited by 26 publications

(2 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PV panel overlay detection offers a huge commercial opportunity [130]. As the global demand for clean energy continues to increase, the installation scale of PV power generation systems is also growing rapidly [131]. Hence, the demand for PV panel overlay inspection technology has also increased.…”

Section: Opportunities and Challenges Of Overlay Detectionmentioning

confidence: 99%

A Survey of Photovoltaic Panel Overlay and Fault Detection Methods

Yang,

Sun,

Zou

et al. 2024

Energies

View full text Add to dashboard Cite

Photovoltaic (PV) panels are prone to experiencing various overlays and faults that can affect their performance and efficiency. The detection of photovoltaic panel overlays and faults is crucial for enhancing the performance and durability of photovoltaic power generation systems. It can minimize energy losses, increase system reliability and lifetime, and lower maintenance costs. Furthermore, it can contribute to the sustainable development of photovoltaic power generation systems, which can reduce our reliance on conventional energy sources and mitigate environmental pollution and greenhouse gas emissions in line with the goals of sustainable energy and environmental protection. In this paper, we provide a comprehensive survey of the existing detection techniques for PV panel overlays and faults from two main aspects. The first aspect is the detection of PV panel overlays, which are mainly caused by dust, snow, or shading. We classify the existing PV panel overlay detection methods into two categories, including image processing and deep learning methods, and analyze their advantages, disadvantages, and influencing factors. We also discuss some other methods for overlay detection that do not process images to detect PV panel overlays. The second aspect is the detection of PV panel faults, which are mainly caused by cracks, hot spots, or partial shading. We categorize existing PV panel fault detection methods into three categories, including electrical parameter detection methods, detection methods based on image processing, and detection methods based on data mining and artificial intelligence, and discusses their advantages and disadvantages.

show abstract

Section: Opportunities and Challenges Of Overlay Detectionmentioning

confidence: 99%

A Survey of Photovoltaic Panel Overlay and Fault Detection Methods

Yang,

Sun,

Zou

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

“…As the IRENA data show [53], this date is known to be 830,741 GWh for the year 2020, while the total PV power installed by the end of 2020 reached 710 GW globally. Assuming a lifetime of the photovoltaic panels of 25 to 30 years [54,55], the water footprint of PV power (during the whole lifetime of the panel) can be estimated, see Equation ( 3):…”

Section: Large Carbon Emissions Associatedmentioning

confidence: 99%

Green Hydrogen: Resources Consumption, Technological Maturity, and Regulatory Framework

Rey,

Segura,

Andújar

2023

Energies

View full text Add to dashboard Cite

Current climate crisis makes the need for reducing carbon emissions more than evident. For this reason, renewable energy sources are expected to play a fundamental role. However, these sources are not controllable, but depend on the weather conditions. Therefore, green hydrogen (hydrogen produced from water electrolysis using renewable energies) is emerging as the key energy carrier to solve this problem. Although different properties of hydrogen have been widely studied, some key aspects such as the water and energy footprint, as well as the technological development and the regulatory framework of green hydrogen in different parts of the world have not been analysed in depth. This work performs a data-driven analysis of these three pillars: water and energy footprint, technological maturity, and regulatory framework of green hydrogen technology. Results will allow the evaluation of green hydrogen deployment, both the current situation and expectations. Regarding the water footprint, this is lower than that of other fossil fuels and competitive with other types of hydrogen, while the energy footprint is higher than that of other fuels. Additionally, results show that technological and regulatory framework for hydrogen is not fully developed and there is a great inequality in green hydrogen legislation in different regions of the world.

show abstract