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Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 21039

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Special Issue Editors

Prof. Dr. George E. Georghiou

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FOSS Research Centre for Sustainable Energy, PV Technology Laboratory, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus
Interests: photovoltaics; microgrids; predictive maintenance; data quality; nanogrids; storage systems
Special Issues, Collections and Topics in MDPI journals

Dr. George Makrides

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PV Technology Laboratory, FOSS Research Center for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus
Interests: photovoltaics; microgrids; predictive maintenance; data quality; nanogrids; storage systems
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Dr. Joshua S. Stein

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Sandia National Laboratory, Albuquerque, NM 87123, USA
Interests: PV system modeling
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Dr. Marios Theristis

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Photovoltaic Systems Evaluation Laboratory (PSEL), Sandia National Laboratories, Albuquerque, NM, USA
Interests: photovoltaics; O&M; PV performance; failure diagnosis; reliability; degradation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Increasing the lifetime and reducing performance degradation of PV systems is vital for making PV the most cost-competitive energy resource and to transform our energy systems. To achieve this goal, we must improve the durability and reliability of PV modules and BOS equipment and respond quickly and intelligently to operational issues. New materials and manufacturing methods can increase the lifetime of PV modules in the field, but may need to be optimized for different climates. Advanced monitoring techniques and fault detection protocols significantly improve the availability of grid-connected photovoltaic (PV) systems, hence lowering investment cost, levelized cost of energy (LCOE), benefiting PV competitiveness.

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:

New materials and module designs for increased PV module lifetimes
Advanced monitoring of grid-connected photovoltaic systems
Enhanced data analytic methods for PV monitoring
Degradation rate estimation procedures
Failure detection and classification techniques for grid-connected PV systems
Modeling of PV system performance
Reliability modeling of PV systems

Prof. Dr. George E. Georghiou
Dr. George Makrides
Dr. Joshua S. Stein
Dr. Marios Theristis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

photovoltaic (PV)
emerging PV
monitoring
modeling
degradation
failure diagnosis
O&M
reliability

Published Papers (6 papers)

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Research

19 pages, 4056 KiB

Open AccessArticle

Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

by Michiel van Noord, Tomas Landelius and Sandra Andersson

Energies 2021, 14(6), 1574; https://0-doi-org.brum.beds.ac.uk/10.3390/en14061574 - 12 Mar 2021

Cited by 10 | Viewed by 2986

Abstract

Snow-induced photovoltaic (PV)-energy losses (snow losses) in snowy and cold locations vary up to 100% monthly and 34% annually, according to literature. Levels that illustrate the need for snow loss estimation using validated models. However, to our knowledge, all these models build on limited numbers of sites and winter seasons, and with limited climate diversity. To overcome this limitation in underlying statistics, we investigate the estimation of snow losses using a PV system’s yield data together with freely available gridded weather datasets. To develop and illustrate this approach, 263 sites in northern Sweden are studied over multiple winters. Firstly, snow-free production is approximated by identifying snow-free days and using corresponding data to infer tilt and azimuth angles and a snow-free performance model incorporating shading effects, etc. This performance model approximates snow-free monthly yields with an average hourly standard deviation of 6.9%, indicating decent agreement. Secondly, snow losses are calculated as the difference between measured and modeled yield, showing annual snow losses up to 20% and means of 1.5–6.2% for winters with data for at least 89 sites. Thirdly, two existing snow loss estimation models are compared to our calculated snow losses, with the best match showing a correlation of 0.73 and less than 1% bias for annual snow losses. Based on these results, we argue that our approach enables studying snow losses for high numbers of PV systems and winter seasons using existing datasets. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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14 pages, 4258 KiB

Open AccessArticle

Thermally Conductive Backsheets (TCB) of PV Modules: Positive Impacts on Performance, Lifetime and LCOE

by Ashwini Pavgi, Jaewon Oh and GovindaSamy TamizhMani

Energies 2021, 14(5), 1252; https://0-doi-org.brum.beds.ac.uk/10.3390/en14051252 - 25 Feb 2021

Cited by 4 | Viewed by 1819

Abstract

The operating temperatures of photovoltaic (PV) modules can be impacted by the selection of specific packaging materials, e.g., backsheets and encapsulants. This research focuses on the evaluation of operating temperature reduction of one-cell modules by comparing conventional Tedlar/polyester/Tedlar (TPT) backsheet with novel thermally conductive backsheets (TCBs) materials. A large number of one-cell modules with two TCB types (TCB_A and TCB_B) and baseline TPT type were fabricated and installed in three different climatic conditions of the hot-dry desert in Arizona (high and low wind speed locations) and North Carolina (temperate with low wind speed location). In this study, these two TCBs were compared with conventional TPT backsheet in terms of performance, lifetime and levelized cost of energy (LCOE). The field results were analyzed for thermal performance of TCBs compared to TPT at three sites for two and half years. This study concludes that the thermal and electrical performances of the PV modules can be improved by using TCB_A in hot and dry climate sites and TCB_B at temperate climate sites. Therefore, the lifetime of TCB-based modules is expected to be higher than TPT-based modules. Using backsheet-specific power degradation levels and assuming the same cost for both types of backsheets, the LCOE of modules using TCBs is estimated to be lower than that of TPT. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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15 pages, 4939 KiB

Open AccessArticle

Field Performance of South-Facing and East-West Facing Bifacial Modules in the Arctic

by Christopher Pike, Erin Whitney, Michelle Wilber and Joshua S. Stein

Energies 2021, 14(4), 1210; https://0-doi-org.brum.beds.ac.uk/10.3390/en14041210 - 23 Feb 2021

Cited by 12 | Viewed by 6137

Abstract

This paper presents the first systematic comparison between south-facing monofacial and bifacial photovoltaic (PV) modules, as well as between south-facing bifacial and vertical east-west facing bifacial PV modules in Alaska. The state’s solar industry, driven by the high price of energy and dropping equipment costs, is quickly growing. The challenges posed by extreme sun angles in Alaska’s northern regions also present opportunities for unique system designs. Annual bifacial gains of 21% were observed between side by side south-facing monofacial and bifacial modules. Vertical east-west bifacial modules had virtually the same annual production as south-facing latitude tilt bifacial modules, but with different energy production profiles. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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12 pages, 3771 KiB

Open AccessArticle

Mitigating Potential-Induced Degradation (PID) Using SiO₂ ARC Layer

by Mahmoud Dhimish, Yihua Hu, Nigel Schofield and Romênia G. Vieira

Energies 2020, 13(19), 5139; https://0-doi-org.brum.beds.ac.uk/10.3390/en13195139 - 02 Oct 2020

Cited by 10 | Viewed by 2281

Abstract

Potential-induced degradation (PID) of photovoltaic (PV) cells is one of the most severe types of degradation, where the output power losses in solar cells may even exceed 30%. In this article, we present the development of a suitable anti-reflection coating (ARC) structure of solar cells to mitigate the PID effect using a SiO₂ ARC layer. Our PID testing experiments show that the proposed ARC layer can improve the durability and reliability of the solar cell, where the maximum drop in efficiency was equal to 0.69% after 96 h of PID testing using an applied voltage of 1000 V and temperature setting at 85 °C. In addition, we observed that the maximum losses in the current density are equal to 0.8 mA/cm², compared with 4.5 mA/cm² current density loss without using the SiO₂ ARC layer. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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18 pages, 24345 KiB

Open AccessArticle

Outdoor PV System Monitoring—Input Data Quality, Data Imputation and Filtering Approaches

by Sascha Lindig, Atse Louwen, David Moser and Marko Topic

Energies 2020, 13(19), 5099; https://0-doi-org.brum.beds.ac.uk/10.3390/en13195099 - 30 Sep 2020

Cited by 32 | Viewed by 4286

Abstract

Photovoltaic monitoring data are the primary source for studying photovoltaic plant behavior. In particular, performance loss and remaining-useful-lifetime calculations rely on trustful input data. Furthermore, a regular stream of high quality is the basis for pro-active operation and management activities which ensure a smooth operation of PV plants. The raw data under investigation are electrical measurements and usually meteorological data such as in-plane irradiance and temperature. Usually, performance analyses follow a strict pattern of checking input data quality followed by the application of appropriate filter, choosing a key performance indicator and the application of certain methodologies to receive a final result. In this context, this paper focuses on four main objectives. We present common photovoltaics monitoring data quality issues, provide visual guidelines on how to detect and evaluate these, provide new data imputation approaches, and discuss common filtering approaches. Data imputation techniques for module temperature and irradiance data are discussed and compared to classical approaches. This work is intended to be a soft introduction into PV monitoring data analysis discussing best practices and issues an analyst might face. It was seen that if a sufficient amount of training data is available, multivariate adaptive regression splines yields good results for module temperature imputation while histogram-based gradient boosting regression outperforms classical approaches for in-plane irradiance transposition. Based on tested filtering procedures, it is believed that standards should be developed including relatively low irradiance thresholds together with strict power-irradiance pair filters. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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17 pages, 3908 KiB

Open AccessArticle

Low-Cost I–V Tracer for PV Modules under Real Operating Conditions

by Manuel Cáceres, Andrés Firman, Jesús Montes-Romero, Alexis Raúl González Mayans, Luis Horacio Vera, Eduardo F. Fernández and Juan de la Casa Higueras

Energies 2020, 13(17), 4320; https://0-doi-org.brum.beds.ac.uk/10.3390/en13174320 - 20 Aug 2020

Cited by 11 | Viewed by 2525

Abstract

Solar photovoltaic technologies have undergone significant scientific development. To ensure the transfer of knowledge through the training of qualified personnel, didactic tools that can be acquired or built at a reasonable price are needed. Most training and research centres have restrictions on acquiring specific equipment due to its high cost. With this in mind, this article presents the development and transfer of a low-cost I–V curve tracer acquisition system. The device is made up of embedded systems with all the necessary hardware and software for its operation. The hardware and software presented are open source and have a low cost, i.e., the estimated material cost of the system is less than 200 euros. For its development, four institutions from three different countries participated in the project. Three photovoltaic technologies were used to measure the uncertainties related to the equipment developed. In addition, the system can be transferred for use as an academic or research tool, as long as the measurement does not need to be certified. Two accredited laboratories have certified the low uncertainties in the measurement of the proposed system. Full article

(This article belongs to the Special Issue Increasing the Lifetime of Photovoltaics Systems: Advanced Materials, Monitoring, O&M and Energy Modeling)

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