Photovoltaic module failures after 10 years of operation in the tropics

Luo, Wei; Clement, Carlos Enrico; Khoo, Yong Sheng; Wang, Yan; Khaing, Aung Myint; Reindl, Thomas; Kumar, Abhishek; Pravettoni, Mauro

doi:10.1016/j.renene.2021.05.145

Cited by 19 publications

(13 citation statements)

References 19 publications

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“…This deterioration is because of the same reasons explained in Section 3.1.1. However, cell 1 still provides the highest performance due to its relatively higher temperature coefficient and reference efficiency [62,63].…”

Section: Resultsmentioning

confidence: 99%

Machine Learning Performance Prediction of a Solar Photovoltaic-Thermoelectric System with Various Crystalline Silicon Cell Types

Alghamdi

Maduabuchi

Albaker

et al. 2023

International Journal of Energy Research

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Since the solar photovoltaic-thermoelectric (PV-TE) is an upcoming technology, the current literature on PV-TEs have failed to thoroughly investigate the effects of different solar cell types on the PV-TE’s performance. Such parametric study becomes necessary since the properties of the solar cell, characterized by the cell temperature coefficient and reference efficiency, determine the overall performance of the PV-TE. Further, the design information obtained from numerical solvers is minimal due to the high time and computational energy required to optimize the photovoltaic-thermoelectric (PV-TE) performance. This problem severely affects the ease with which useful design information can be drawn from current methods to design high-performance PVs. Additionally, to reduce the complexity of the existing numerical model, the previous models have introduced some principal assumptions that have significantly affected the accuracy of the numerical results. Finally, the numerical model has neglected several real-life operating conditions since they increase the model complexity. For the first time, deep neural networks are proposed to predict the photovoltaic-thermoelectric performance designed with 3 different crystalline solar cells as a perfect replacement for the inefficient numerical methods used to analyze the hybrid system. After that, the data generated by the numerical solver is fed to an optimum 3-layer deep neural network with 20 neurons per layer to forecast the hybrid system’s performance efficiently. The training of the neural network is governed by Bayesian regularization and the performance of the model is evaluated using the mean squared error, coefficient of determination, and training time. Results show that the deep neural network accurately learned the results that took the conventional numerical solver 1,600 mins to generate in just 12 min and 27 s, making the proposed network 128.51 times faster than the traditional numerical method. Furthermore, the accuracy of the network is demonstrated by the low mean squared error of 3.34 × 10 − 8 and high training and testing regression of 100% and 99.98%, respectively.

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Section: Resultsmentioning

confidence: 99%

Machine Learning Performance Prediction of a Solar Photovoltaic-Thermoelectric System with Various Crystalline Silicon Cell Types

Alghamdi

Maduabuchi

Albaker

et al. 2023

International Journal of Energy Research

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“…Now, employing the existing criteria (e.g., accelerated tests in International Electrotechnical Commisson (IEC) 61215 and International Summit on Organic Photovoltaic Stability (ISOS) protocols) for evaluation is being accepted by industry and academia. [16][17][18] IEC 61215 is an industrystandard for certification of silicon PV technology for commercial deployment, while ISOS provides guidelines on stability testing under accelerated conditions to enable comparison across various reports. [16][17][18] Several companies and research groups have announced passing partial or complete accelerating aging tests like damp-heat, and temperature cycles in IEC 61215, demonstrating the stability potential to meet the commercial requirements.…”

Section: Current Status Of Perovskite Pv Devicesmentioning

confidence: 99%

“…[16][17][18] IEC 61215 is an industrystandard for certification of silicon PV technology for commercial deployment, while ISOS provides guidelines on stability testing under accelerated conditions to enable comparison across various reports. [16][17][18] Several companies and research groups have announced passing partial or complete accelerating aging tests like damp-heat, and temperature cycles in IEC 61215, demonstrating the stability potential to meet the commercial requirements. [16,17,19,20] These accelerated tests are designed to correlate the real-world lifetime to the values obtained in the laboratory, but the experience from the silicon and thin-film PV industry has demonstrated that these tests are insufficient to predict the lifetime under real-world conditions.…”

Section: Current Status Of Perovskite Pv Devicesmentioning

confidence: 99%

“…[16][17][18] Several companies and research groups have announced passing partial or complete accelerating aging tests like damp-heat, and temperature cycles in IEC 61215, demonstrating the stability potential to meet the commercial requirements. [16,17,19,20] These accelerated tests are designed to correlate the real-world lifetime to the values obtained in the laboratory, but the experience from the silicon and thin-film PV industry has demonstrated that these tests are insufficient to predict the lifetime under real-world conditions. [11] For example, PV modules passing IEC standards do not always meet a lifetime exceeding 20 years.…”

Section: Current Status Of Perovskite Pv Devicesmentioning

confidence: 99%

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Toward the Commercialization of Perovskite Solar Modules

Zhu,

Chen,

Dai

et al. 2024

Advanced Materials

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Perovskite photovoltaic devices are undergoing rapid development and have reached a certified power conversion efficiency of 26.1% at the cell level. Tremendous efforts in material and device engineering have also increased moisture, heat, and light‐related stability. Moreover, the solution‐process nature makes the fabrication process of perovskite photovoltaic devices feasible and compatible with some mature high‐volume manufacturing techniques. All these features render perovskite solar modules suitable for terawatt‐scale energy production with a low levelized cost of electricity. In this review, we first introduce the current status of perovskite solar cells and modules and their potential applications. Then we identify critical challenges in their commercialization and propose the corresponding solutions, including developing strategies to realize high‐quality films over a large area to further improve power conversion efficiency and stability to meet the commercial demands. Finally, we put forward some potential development directions and issues requiring attention in the future, mainly focusing on further dealing with toxicity and recycling of the whole device, and the attainment of highly efficient perovskite‐based tandem modules, which could reduce the environmental impact and accelerate the LCOE reduction.This article is protected by copyright. All rights reserved

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“…Numerical simulation uses a variety of software and big databases that contain regional operational insolation data over many years. Computer simulations can also prevent design errors that are the major causes of almost all the failure modes like installation fire, anormal operation conditions or cable insulation damage [32,33].…”

Section: Introductionmentioning

confidence: 99%

Reliability-Oriented Design of a Solar-PV Deployments

2021

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Increasing restrictions on the emission of greenhouse gases by the standards and the European Union’s policy aims at increasing the share of renewable energy sources in the energy mix of the Member States. Subsequently, we observe a rapid increase in the installed capacity of the renewable energy sources. Renewable energy sources are currently the fastest growing sectors of energy generation, specifically the photovoltaic sector. In 2005, the total installed capacity in photovoltaic installations in the European Union was about 2.17 GW, while in 2019 it was already over 130 GW. Currently, due to many forms of incentive governmental measures the construction of photovoltaic installations is rapidly increasing with installations mounted on private houses and buildings. The article presents selected issues concerning the failure modes of photovoltaic installations and a comparative assessment of the estimated and the real measured electrical production of an operational photovoltaic installation. The Solar-PV power plant design approach proposed in the paper considers the failure modes to enhance the plant’s reliability.

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Photovoltaic module failures after 10 years of operation in the tropics

Cited by 19 publications

References 19 publications

Machine Learning Performance Prediction of a Solar Photovoltaic-Thermoelectric System with Various Crystalline Silicon Cell Types

Machine Learning Performance Prediction of a Solar Photovoltaic-Thermoelectric System with Various Crystalline Silicon Cell Types

Toward the Commercialization of Perovskite Solar Modules

Reliability-Oriented Design of a Solar-PV Deployments

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