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Applied Sciences
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Performance Analysis of Photovoltaic Systems
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Performance Analysis of Photovoltaic Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (1 November 2020) | Viewed by 26587

Special Issue Editors

Prof. Dr. Wilfried Van Sark

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Guest Editor
Copernicus Institute of Sustainable Development, Utrecht University, Princetonlaan 8, 3584 CB Utrecht, The Netherlands
Interests: integration of PV in society in particular in buildings (BIPV) and the (local) electricity grid; simulation and performance analysis of PV systems and modules, shading analyses and shad-resilience options, for land-based and water-based PV systems; forecasting of PV power with AI approaches and sky-imagers; market and footprint analysis of PV systems and circularity approaches
Special Issues, Collections and Topics in MDPI journals
Dr. David Moser

E-Mail Website
Guest Editor
Institute for Renewable Energy, EURAC Research
Interests: photovoltaics; building integrated photovoltaic; solar resources; electric storage; energy scenarios and policies
Prof. Dr. Angele Reinders

E-Mail Website
Guest Editor
1. Department of Design, Production and Management, Faculty of Engineering Technology, University of Twente, 7500 AE Enschede, The Netherlands
2. Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
Interests: sustainable energy systems; product design; photovoltaics; smart energy products; smart grids; PV modules; PV performance; electricity; innovation; and sustainable development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

For this Special Issue of the journal Applied Sciences, authors are invited to submit manuscripts covering research about the analysis of the performance and reliability of PV systems. Manuscripts can be focused on monitoring methods, methods, and results applied to PV operational data analysis, climate-dependent PV performance, PV data banks, assessments of metadata of installed PV systems, comparison of simulations of PV performance with operational data, machine learning and artificial intelligence methods for operational performance and reliability assessments, and other topics that come up in this context.

The aim of this Special Issue is to encourage scientists to publish their experimental and theoretical results, in as much detail as possible so that they can be reproduced. If possible, a validation of simulated results should be included in a manuscript. Manuscripts containing interdisciplinary research results are particularly welcome in this Special Issue; for instance, about PV system performance in the context of bankability, operational issues, design features, and user and grid interactions. There is no restriction on the length of the papers.

Prof. Dr. Wilfried van Sark
Dr. David Moser
Prof. Dr. Angele Reinders
Guest Editor

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. Applied Sciences 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 2400 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.

Published Papers (6 papers)

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Research

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20 pages, 120738 KiB  
Article
Energy Balance, Cost and Architectural Design Features of 24 Building Integrated Photovoltaic Projects Using a Modelling Approach
by Cihan Gercek, Mirjana Devetaković, Aleksandra Krstić-Furundžić and Angèle Reinders
Appl. Sci. 2020, 10(24), 8860; https://doi.org/10.3390/app10248860 - 10 Dec 2020
Cited by 5 | Viewed by 3213
Abstract
This paper presents the energy balance, architectural design features and cost aspects of 24 building integrated photovoltaic (BIPV) projects in three different contexts, namely BIPV in residential, office and historical buildings. These BIPV projects have been modelled and evaluated for different geographic locations [...] Read more.
This paper presents the energy balance, architectural design features and cost aspects of 24 building integrated photovoltaic (BIPV) projects in three different contexts, namely BIPV in residential, office and historical buildings. These BIPV projects have been modelled and evaluated for different geographic locations because the European Energy Performance of Buildings Directive (2018/844/EU) has resulted in country-specific regulations and situations aimed towards the reduction in energy consumption, and hence the CO2 emissions of built environments. Moreover, the geographical variation of irradiation affects the performance of different BIPV projects on different locations. The results of our study show that the return of investment of BIPV projects across 12 countries took (on average) 13.3 years. Furthermore, the residential projects —as compared to non-residential buildings—were mostly energy plus buildings with an average self-sufficiency of 110% due to their low energy consumption. In conclusion, most BIPV projects resulted in realistic energy performances (on average: 761 kWh/kWp.year), low payback times (10 years for residential and office buildings), and modelled unique design features. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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29 pages, 15049 KiB  
Article
Validation of Bifacial Photovoltaic Simulation Software against Monitoring Data from Large-Scale Single-Axis Trackers and Fixed Tilt Systems in Denmark
by Nicholas Riedel-Lyngskær, Djaber Berrian, Daniel Alvarez Mira, Alexander Aguilar Protti, Peter Behrensdorff Poulsen, Joris Libal and Jan Vedde
Appl. Sci. 2020, 10(23), 8487; https://doi.org/10.3390/app10238487 - 27 Nov 2020
Cited by 19 | Viewed by 5727
Abstract
The size and number of utility-scale bifacial photovoltaic (PV) installations has proliferated in recent years but concerns over modeling accuracy remain. The aim of this work is to provide the PV community with a validation study of eight tools used to simulate bifacial [...] Read more.
The size and number of utility-scale bifacial photovoltaic (PV) installations has proliferated in recent years but concerns over modeling accuracy remain. The aim of this work is to provide the PV community with a validation study of eight tools used to simulate bifacial PV performance. We simulate real 26 kilowatt-peak (kWp) bifacial arrays within a 420-kWp site located in northern Europe (55.6° N, 12.1° E). The substructures investigated include horizontal single-axis trackers (HSATs) and fixed tilt racks that have dimensions analogous to those found in utility-scale PV installations. Each bifacial system has a monofacial reference system with similar front side power. We use on-site solar radiation (global, diffuse, and beam) and albedo measurements from spectrally flat class A sensors as inputs to the simulation tools, and compare the modeled values to field measurements of string level power, rear and front plane of array irradiance, and module temperature. Our results show that state-of-the-art bifacial performance models add ~0.5% uncertainty to the PV modeling chain. For the site investigated, 2-D view factor fixed tilt simulations are within ±1% of the measured monthly bifacial gain. However, simulations of single-axis tracker systems are less accurate, wherein 2-D view factor and 3-D ray tracing are within approximately 2% and 1% of the measured bifacial gain, respectively. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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15 pages, 1677 KiB  
Article
Autonomous Monitoring of Line-to-Line Faults in Photovoltaic Systems by Feature Selection and Parameter Optimization of Support Vector Machine Using Genetic Algorithms
by Aref Eskandari, Jafar Milimonfared, Mohammadreza Aghaei and Angèle H.M.E. Reinders
Appl. Sci. 2020, 10(16), 5527; https://doi.org/10.3390/app10165527 - 10 Aug 2020
Cited by 23 | Viewed by 2841
Abstract
Photovoltaic (PV) monitoring and fault detection are very crucial to enhance the service life and reliability of PV systems. It is difficult to detect and classify the faults at the Direct Current (DC) side of PV arrays by common protection devices, especially Line-to-Line [...] Read more.
Photovoltaic (PV) monitoring and fault detection are very crucial to enhance the service life and reliability of PV systems. It is difficult to detect and classify the faults at the Direct Current (DC) side of PV arrays by common protection devices, especially Line-to-Line (LL) faults, because such faults are not detectable under high impedance fault and low mismatch conditions. If these faults are not diagnosed, they may significantly reduce the output power of PV systems and even cause fire catastrophe. Recently, many efforts have been devoted to detecting and classifying LL faults. However, these methods could not efficiently detect and classify the LL faults under high impedance and low mismatch. This paper proposes a novel fault diagnostic scheme in accordance with the two main stages. First, the key features are extracted via analyzing Current–Voltage (I–V) characteristics under various LL fault events and normal operation. Second, a genetic algorithm (GA) is used for parameter optimization of the kernel functions used in the Support Vector Machine (SVM) classifier and feature selection in order to obtain higher performance in diagnosing the faults in PV systems. In contrast to previous studies, this method requires only a small dataset for the learning process and it has a higher accuracy in detecting and classifying the LL fault events under high impedance and low mismatch levels. The simulation results verify the validity and effectiveness of the proposed method in detecting and classifying of LL faults in PV arrays even under complex conditions. The proposed method detects and classifies the LL faults under any condition with an average accuracy of 96% and 97.5%, respectively. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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22 pages, 4965 KiB  
Article
Operational Performance and Degradation of PV Systems Consisting of Six Technologies in Three Climates
by Kunaifi Kunaifi, Angèle Reinders, Sascha Lindig, Magnus Jaeger and David Moser
Appl. Sci. 2020, 10(16), 5412; https://doi.org/10.3390/app10165412 - 05 Aug 2020
Cited by 13 | Viewed by 4052
Abstract
In Indonesia, the solar photovoltaic (PV) market is rapidly growing. However, studies on the outdoor performance of PV systems in this tropical rainforest country is lacking. In this work, we compare the performance of PV systems in Indonesia with PV systems in Australia [...] Read more.
In Indonesia, the solar photovoltaic (PV) market is rapidly growing. However, studies on the outdoor performance of PV systems in this tropical rainforest country is lacking. In this work, we compare the performance of PV systems in Indonesia with PV systems in Australia (arid, desert, hot) and Italy (temperate, dry summer, hot summer). Monitoring data from 2008 to 2019, ranging from two to nine years, from fifteen PV systems of six technologies were analyzed. The performance of the PV systems was presented using their performance ratio (PR) and performance loss rate (PLR). PR was calculated using IEC standard 61724, and PLR was calculated using seasonal and trend decomposition, applying locally weighted scatterplot smoothing (STL decomposition) and the year-on-year approach from NREL/RdTools. The results showed that the CIGS (copper indium gallium selenide) system had the highest average PR value of 0.88 ± 0.04. The lowest average PR was found in the a-Si (amorphous silicon) PV systems (0.78 ± 0.05). The p-Si (polycrystalline silicon) systems in the Cfb (temperate, no dry season, warm summer) climate of Italy had a higher average PR of 0.84 than those operated in climates BWh (arid, desert, hot) of Australia and Af (tropical, rainforest) of Indonesia, with the same value of 0.81. The p-Si systems showed the lowest PLR, with a value of −0.6%/year. The fastest degradation was experienced by a-Si modules at −1.58%/year. The methodological differences in the calculation of PLR using both tested approaches resulted in a significant difference in the degradation value, which demands standardization of the term and calculation methodology. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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Review

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22 pages, 42296 KiB  
Review
Photovoltaics on Landmark Buildings with Distinctive Geometries
by Mirjana Devetaković, Djordje Djordjević, Milan Radojević, Aleksandra Krstić-Furundžić, Bogdan-Gabriel Burduhos, Georgios Martinopoulos, Mircea Neagoe and Gabriele Lobaccaro
Appl. Sci. 2020, 10(19), 6696; https://doi.org/10.3390/app10196696 - 25 Sep 2020
Cited by 12 | Viewed by 6321
Abstract
This review study, framed in the Work group 4 “Photovoltaic in built environment” within the COST Action PEARL PV, CA16235, aims to examine applications of integrated and applied photovoltaic technologies on ten landmark buildings characterised by distinctive geometries, highlighting the aesthetics of their [...] Read more.
This review study, framed in the Work group 4 “Photovoltaic in built environment” within the COST Action PEARL PV, CA16235, aims to examine applications of integrated and applied photovoltaic technologies on ten landmark buildings characterised by distinctive geometries, highlighting the aesthetics of their architecture and quality of PV integration based on a proposed set of seven criteria. The selected building samples cover a large design diversity related to the quality of PV systems integration into building envelope that could serve as a basis for general guidelines of best architectural and technological practice. After introducing the problem and defining the research methodology, an analysis of ten landmark buildings is presented, as representative models of aesthetics of their architecture, photovoltaic integration and implementation and energy performance. The study concludes with the main characteristics of photovoltaic integration on landmark buildings. The paper is intended to support both engineers and architects in comprehending the convergent development of contemporary architecture and photovoltaic technology, as well as the need for a closer collaboration, sometimes resulting in architectural masterworks that promote the diffusion of photovoltaics to the public. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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Other

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9 pages, 430 KiB  
Conference Report
Training and Testing of a Single-Layer LSTM Network for Near-Future Solar Forecasting
by Naylani Halpern-Wight, Maria Konstantinou, Alexandros G. Charalambides and Angèle Reinders
Appl. Sci. 2020, 10(17), 5873; https://doi.org/10.3390/app10175873 - 25 Aug 2020
Cited by 23 | Viewed by 3255
Abstract
Increasing integration of renewable energy sources, like solar photovoltaic (PV), necessitates the development of power forecasting tools to predict power fluctuations caused by weather. With trustworthy and accurate solar power forecasting models, grid operators could easily determine when other dispatchable sources of backup [...] Read more.
Increasing integration of renewable energy sources, like solar photovoltaic (PV), necessitates the development of power forecasting tools to predict power fluctuations caused by weather. With trustworthy and accurate solar power forecasting models, grid operators could easily determine when other dispatchable sources of backup power may be needed to account for fluctuations in PV power plants. Additionally, PV customers and designers would feel secure knowing how much energy to expect from their PV systems on an hourly, daily, monthly, or yearly basis. The PROGNOSIS project, based at the Cyprus University of Technology, is developing a tool for intra-hour solar irradiance forecasting. This article presents the design, training, and testing of a single-layer long-short-term-memory (LSTM) artificial neural network for intra-hour power forecasting of a single PV system in Cyprus. Four years of PV data were used for training and testing the model (80% for training and 20% for testing). With a normalized root mean squared error (nRMSE) of 10.7%, the single-layer network performed similarly to a more complex 5-layer LSTM network trained and tested using the same data. Overall, these results suggest that simple LSTM networks can be just as effective as more complicated ones. Full article
(This article belongs to the Special Issue Performance Analysis of Photovoltaic Systems)
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