Reliability Analysis for Photovoltaic Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 10563

Special Issue Editor


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Guest Editor
Co-Director of Photovoltaics Laboratory and Lecturer in Electronics and Control Engineering, Department of Engineering and Technology, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: renewable energy; artificial intelligence; machine learning; forecasting
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Special Issue Information

Dear Colleagues,

Cutting-edge IoT-based monitoring units and globalized protocols can considerably improve the quality of operation of photovoltaics (PV) systems. Extracting useful data of PV systems can improve the reliability, durability, and lifetime performance through enhanced data analytics tools, degradation estimation procedures, and early-stage fault detection. Therefore, the aim of this Special Issue is to solicit original and high-quality research articles related to the aforementioned topics. In particular, topics of interest include but are not limited to:

  • IoT-based monitoring of photovoltaic systems;
  • Data analytics tools for PV systems performance analysis;
  • Reliability and durability metrics for PV systems;
  • PV fault detection (AI-based and mathematical methods);
  • Degradation of PV modules;
  • Power electronics reliability associated with PV systems integration.

Dr. Mahmoud Dhimish
Guest Editor

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Keywords

  • PV systems (residential and large-scale)
  • monitoring of PV systems
  • performance analysis
  • PV fault detection and classification

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Published Papers (3 papers)

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Research

20 pages, 6805 KiB  
Article
Digital System Performance Enhancement of a Tent Map-Based ADC for Monitoring Photovoltaic Systems
by Philippa Hazell, Peter Mather, Andrew Longstaff and Simon Fletcher
Electronics 2020, 9(9), 1554; https://doi.org/10.3390/electronics9091554 - 22 Sep 2020
Cited by 2 | Viewed by 2293
Abstract
Efficient photovoltaic installations require control systems that detect small signal variations over large measurement ranges. High measurement accuracy requires data acquisition systems with high-resolution analogue-to-digital converters; however, high resolutions and operational speeds generally increase costs. Research has proven low-cost prototyping of non-linear chaotic [...] Read more.
Efficient photovoltaic installations require control systems that detect small signal variations over large measurement ranges. High measurement accuracy requires data acquisition systems with high-resolution analogue-to-digital converters; however, high resolutions and operational speeds generally increase costs. Research has proven low-cost prototyping of non-linear chaotic Tent Map-based analogue-to-digital converters (which fold and amplify the input signal, emphasizing small signal variations) is feasible, but inherent non-ideal Tent Map gains reduce the output accuracy and restrict adoption within data acquisition systems. This paper demonstrates a novel compensation algorithm, developed as a digital electronic system, for non-ideal Tent Map gain, enabling high accuracy estimation of the analogue-to-digital converter analogue input signal. Approximation of the gain difference compensation values (reducing digital hardware requirements, enabling efficient real-time compensation), were also investigated via simulation. The algorithm improved the effective resolution of a 16, 20 and 24 Tent Map-stage analogue-to-digital converter model from an average of 5 to 15.5, 19.2, and 23 bits, respectively, over the Tent Map gain range of 1.9 to 1.99. The simulated digital compensation system for a seven Tent Map-stage analogue-to-digital converter enhanced the accuracy from 4 to 7 bits, confirming real-time compensation for non-ideal gain in Tent Map-based analogue-to-digital converters was achievable. Full article
(This article belongs to the Special Issue Reliability Analysis for Photovoltaic Systems)
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14 pages, 3757 KiB  
Article
Photovoltaic Degradation Rate Affected by Different Weather Conditions: A Case Study Based on PV Systems in the UK and Australia
by Mahmoud Dhimish and Abdullah Alrashidi
Electronics 2020, 9(4), 650; https://doi.org/10.3390/electronics9040650 - 16 Apr 2020
Cited by 54 | Viewed by 5021
Abstract
This article presents the analysis of degradation rate over 10 years (2008 to 2017) for six different photovoltaic (PV) sites located in the United Kingdom (mainly affected by cold weather conditions) and Australia (PV affected by hot weather conditions). The analysis of the [...] Read more.
This article presents the analysis of degradation rate over 10 years (2008 to 2017) for six different photovoltaic (PV) sites located in the United Kingdom (mainly affected by cold weather conditions) and Australia (PV affected by hot weather conditions). The analysis of the degradation rate was carried out using the year-on-year (YOY) degradation technique. It was found that the degradation rate in the UK systems varies from −1.05% and −1.16%/year. Whereas a higher degradation ranging from −1.35% to −1.46%/year is observed for the PV systems installed in Australia. Additionally, it was found that in the Australian PV systems multiple faulty PV bypass diodes are present due to the rapid change in the ambient temperature and uneven solar irradiance levels influencing the PV modules. However, in cold weather conditions (such as in the Northern UK) none of the bypass diodes were damaged over the considered PV exposure period. Furthermore, the number of PV hot spots have also been observed, where it was found that in the UK-based PV systems the number of hot spotted PV modules are less than those found in the Australian systems. Finally, the analysis of the monthly performance ratio (PR) was calculated. It was found that the mean monthly PR is equal to 88.81% and 86.35% for PV systems installed in the UK and Australia, respectively. Full article
(This article belongs to the Special Issue Reliability Analysis for Photovoltaic Systems)
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23 pages, 8522 KiB  
Article
Impacts of Array Orientation and Tilt Angles for Photovoltaic Self-Sufficiency and Self-Consumption Indices in Olive Mills in Spain
by Gabino Jiménez-Castillo, Francisco José Muñoz-Rodríguez, Antonio Javier Martinez-Calahorro, Giuseppe Marco Tina and Catalina Rus-Casas
Electronics 2020, 9(2), 348; https://doi.org/10.3390/electronics9020348 - 18 Feb 2020
Cited by 14 | Viewed by 2681
Abstract
Olive mills are extensive in the Mediterranean Basin, and Spain constitutes approximately 45% of global production. The industrial sector faces a new energetic paradigm where distributed generation provided by small renewable energy sources may reduce the dependence from fossil energy sources as well [...] Read more.
Olive mills are extensive in the Mediterranean Basin, and Spain constitutes approximately 45% of global production. The industrial sector faces a new energetic paradigm where distributed generation provided by small renewable energy sources may reduce the dependence from fossil energy sources as well as avoid energy distribution losses. Photovoltaic self-consumption systems can play an important role in confronting this challenge due to their modularity and their decreasing cost. Most of self-sufficiency energy studies are focused on building sector and discussions about the idiosyncrasy of industrial load profiles, and their matching capability with photovoltaic generation profiles can be scarcely found. This work analyzes the potential of photovoltaic self-consumption systems as a function of the array power, array tilt, and orientation angles to face the electric consumption in olive mills. Different recording intervals and reporting periods are considered. Results show that a self-sufficiency index of 40% may be achieved on olive harvest basis. Moreover, due to the load profile particularities, percentage error lower than 1.6% has been found when considering a recording interval of 60 min when matching the olive load consumption and photovoltaic generation profiles. Chosen array tilt and orientation angles may be key parameters to maximize the self-sufficiency index. Full article
(This article belongs to the Special Issue Reliability Analysis for Photovoltaic Systems)
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