Recent Advances in Materials and Technologies for 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 (31 December 2022) | Viewed by 11324

Special Issue Editors

University of Salerno, Salerno, Italy
Interests: Models and methods for design of DC/DC and DC/AC switching converters; tolerance analysis and robust design; modeling and characterization of photovoltaic sources and storage systems. Nonlinear control techniques and maximum power point tracking (MPPT); numerical methods for parameters identification of electrical systems. Energy harvesting
Delft University of Technology, Delft, The Netherlands
Interests: development of innovative photovoltaic module topologies and PV-based intelligent energy agents; analysis, design and control of switching converters for renewable energy source; on-line diagnostics of the whole energy conversion system by means of linear and non-linear identification techniques; photovoltatronics

Special Issue Information

Dear Colleagues,

The large-scale integration of renewable energy in electrical grids and the distributed generation of electricity are crucial to speed up the global green-energy transition and decarbonize the energy sector. Photovoltaic (PV) systems are leading this transition, especially in urban areas, thanks to their scalability in terms of power and ease of integration in the urban fabric, in particular on building rooftops and facades. Recent studies on second- and third-generation PV cells, including among others organic solar cells and perovskite solar cells, demonstrate that these technologies can reach high efficiency and longer lifetime, not only at the laboratory level, and have the potential to rapidly be competitive with the well-established crystalline silicon solar cells technology. Similarly, power devices based on wide-bandgap semiconductors are playing an important role in improving the PV system conversion efficiency and controllability owing to their ability to operate at higher switching frequencies. On the other hand, due to the intermittent nature of solar energy and its high penetration in smart grids, the modelling, design, monitoring, control, and diagnosis of PV systems are becoming increasingly complex. To deal with these challenges, novel techniques employing massive computational intelligence and IoT technologies are being developed for both the design (off-line) and the control, monitoring, and diagnosis (on-line) of PV systems, as well as for energy forecasting. Furthermore, the integration of storage in PV systems is becoming very popular as a means to ensure supply–demand balancing and grid stability.

The Special Issue aims to collect research works and reviews discussing recent advances in materials and technologies for photovoltaic systems. Topics of interest include, but are not limited to:

  • Materials and technologies
    • Second- and third-generation photovoltaic cells;
    • Power electronics and wide-bandgap semiconductors for PV applications;
    • Manufacturing processes for enhancing PV lifetime;
    • Materials for PV encapsulation and protection;
  • Modelling, simulations and design tools
    • Advanced modeling of emerging PV technologies;
    • Modeling and simulation tools for the design and optimization of PV systems;
    • PV energy forecast for decision processes and grid operators;
    • Data-driven design for PV cells and modules manufacturing;
  • Control, monitoring, and diagnosis
    • New techniques for maximum power extraction and maximum energy yield;
    • PV degradation phenomena, fault diagnosis, mismatching detection;
    • Distributed sensing and IoT for the monitoring and maintenance of PV systems;
    • Identification techniques and their application to the control, monitoring, and diagnosis of PV systems.

Prof. Dr. Giovanni Petrone
Dr. Patrizio Manganiello
Guest Editors

Manuscript Submission Information

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Published Papers (5 papers)

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Research

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21 pages, 4956 KiB  
Article
Asymmetrical Multilevel Inverter-Based PV System with Voltage Feedback Control: An Experimental Validation
by Muhammad Najwan Hamidi, Arjuna Marzuki, Dahaman Ishak, Mohamed Salem, Mohd Hezri Marzaki and Ikechi Augustine Ukaegbu
Appl. Sci. 2022, 12(7), 3581; https://0-doi-org.brum.beds.ac.uk/10.3390/app12073581 - 31 Mar 2022
Cited by 2 | Viewed by 1616
Abstract
This paper presents an experimental evaluation and validation of a standalone photovoltaic (PV) renewable energy system using a perturb and observe MPPT-based voltage controller (POVC) for application on the reduced component multilevel inverter (MLI). The objective is to verify the effectiveness of POVC [...] Read more.
This paper presents an experimental evaluation and validation of a standalone photovoltaic (PV) renewable energy system using a perturb and observe MPPT-based voltage controller (POVC) for application on the reduced component multilevel inverter (MLI). The objective is to verify the effectiveness of POVC and asymmetrical MLI for real PV interconnection applications, which has never been reported before. An asymmetrical 17-level MLI topology is selected in this research. It requires four isolated DC sources to operate. A boost converter is deployed as one of the inputs while isolated DC power supplies power to the others. POVC is implemented at the boost converter to control the DC voltage from the PV panel. From the experimental results, the capability of the POVC to produce constant voltage levels under varying conditions is proven. It is also capable of delivering maximum power under maximum load. The full system is tested using different load types, including nonlinear loads. The MLI produces expected outputs under all operating conditions with efficiencies above 97%. The viability of the proposed PV system is firstly analysed through MATLAB/Simulink simulations. The results are then evaluated experimentally. Full article
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22 pages, 2095 KiB  
Article
Parameter Estimation of the Bishop Photovoltaic Model Using a Genetic Algorithm
by Bonie Johana Restrepo-Cuestas, Jhon Montano, Carlos Andrés Ramos-Paja, Luz Adriana Trejos-Grisales and Martha Lucia Orozco-Gutierrez
Appl. Sci. 2022, 12(6), 2927; https://0-doi-org.brum.beds.ac.uk/10.3390/app12062927 - 13 Mar 2022
Cited by 7 | Viewed by 2313
Abstract
Photovoltaic panels can be affected by partial shading, which causes some shaded cells to consume the energy generated by other cells of the panel. That is, shaded cells stop operating in the first quadrant and start operating in the second quadrant, with negative [...] Read more.
Photovoltaic panels can be affected by partial shading, which causes some shaded cells to consume the energy generated by other cells of the panel. That is, shaded cells stop operating in the first quadrant and start operating in the second quadrant, with negative voltage at their terminals, causing power losses and other negative effects in the cells. The Bishop model is an accurate representation of the cells behavior at the second quadrant, but estimating its parameters is not a trivial task. Therefore, this paper presents a procedure to estimate the parameters of the Bishop model by using the Chu–Beasley optimization technique. The effectiveness of this procedure was evaluated using different accuracy measures such as RMSE and MAPE, obtaining values lower than 0.5%. In addition, the results of this study demonstrate that it is essential to estimate all the parameters of the Bishop model, illustrate the variation in the parameters according to the cell technology and show the strong influence of the shunt resistance into the behavior at the second quadrant. Full article
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23 pages, 955 KiB  
Article
Sliding-Mode Control of a Photovoltaic System Based on a Flyback Converter for Microinverter Applications
by Carlos Andres Ramos-Paja, Juan David Bastidas-Rodriguez and Andres Julian Saavedra-Montes
Appl. Sci. 2022, 12(3), 1399; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031399 - 28 Jan 2022
Cited by 10 | Viewed by 1658
Abstract
A method to design a sliding-mode control of a photovoltaic system based on a flyback converter is proposed. First, the photovoltaic system is modeled to design the sliding-mode controller and to select the parameters of a maximum power point tracking algorithm. Then, the [...] Read more.
A method to design a sliding-mode control of a photovoltaic system based on a flyback converter is proposed. First, the photovoltaic system is modeled to design the sliding-mode controller and to select the parameters of a maximum power point tracking algorithm. Then, the detailed design of the sliding-mode controller is presented, which includes the establishment of the sliding surface. The transversality, reachability, and equivalent control tests are also developed. Because the power extraction of the PV system is carried out through a P&O MPPT algorithm, the selection of the perturbation magnitude, the perturbation period, and the maximum switching frequency is integrated into the control design. Additionally, since the derivative of the MPPT output could prevent the achievement of the reachability test, a filter to limit that derivative is also integrated into the design process. The whole method is illustrated in an application example where the data of a BP585 PV module and a real flyback converter are used. Once the parameters were obtained, circuital simulations performed in PSIM validated the intended operation of a PV system composed of a PV module and a flyback converter, which is connected to a source that produces the perturbations of an AC grid. Full article
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27 pages, 1159 KiB  
Article
Early Detection of Photovoltaic Panel Degradation through Artificial Neural Network
by Rudy Alexis Guejia Burbano, Giovanni Petrone and Patrizio Manganiello
Appl. Sci. 2021, 11(19), 8943; https://0-doi-org.brum.beds.ac.uk/10.3390/app11198943 - 25 Sep 2021
Cited by 3 | Viewed by 1698
Abstract
In this paper, an artificial neural network (ANN) is used for isolating faults and degradation phenomena occurring in photovoltaic (PV) panels. In the literature, it is well known that the values of the single diode model (SDM) associated to the PV source are [...] Read more.
In this paper, an artificial neural network (ANN) is used for isolating faults and degradation phenomena occurring in photovoltaic (PV) panels. In the literature, it is well known that the values of the single diode model (SDM) associated to the PV source are strictly related to degradation phenomena and their variation is an indicator of panel degradation. On the other hand, the values of parameters that allow to identify the degraded conditions are not known a priori because they can be different from panel to panel and are strongly dependent on environmental conditions, PV technology and the manufacturing process. For these reasons, to correctly detect the presence of degradation, the effect of environmental conditions and fabrication processes must be properly filtered out. The approach proposed in this paper exploits the intrinsic capability of ANN to map in its architecture two effects: (1) the non-linear relations existing among the SDM parameters and the environmental conditions, and (2) the effect of the degradation phenomena on the I-V curves and, consequently, on the SDM parameters. The ANN architecture is composed of two stages that are trained separately: one for predicting the SDM parameters under the hypothesis of healthy operation and the other one for degraded condition. The variation of each parameter, calculated as the difference of the output of the two ANN stages, will give a direct identification of the type of degradation that is occurring on the PV panel. The method was initially tested by using the experimental I-V curves provided by the NREL database, where the degradation was introduced artificially, later tested by using some degraded experimental I-V curves. Full article
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Review

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27 pages, 5248 KiB  
Review
Common-Ground Photovoltaic Inverters for Leakage Current Mitigation: Comparative Review
by Mahmoud A. Gaafar, Mohamed Orabi, Ahmed Ibrahim, Ralph Kennel and Mohamed Abdelrahem
Appl. Sci. 2021, 11(23), 11266; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311266 - 28 Nov 2021
Cited by 12 | Viewed by 2972
Abstract
In photovoltaic systems, parasitic capacitance is often formed between PV panels and the ground. Because of the switching nature of PV converters, a high-frequency voltage is usually generated over these parasitic capacitances; this, in turn, can result in a common-mode current known as [...] Read more.
In photovoltaic systems, parasitic capacitance is often formed between PV panels and the ground. Because of the switching nature of PV converters, a high-frequency voltage is usually generated over these parasitic capacitances; this, in turn, can result in a common-mode current known as leakage current. This current can badly reach a high value if a resonance circuit is excited through the PV’s parasitic capacitance and the converter’s inductive components. Transformers are usually used for leakage current mitigation. However, this decreases the efficiency and increases the cost, size, and weight of the PV systems. Number of strategies have been introduced to mitigate the leakage current in transformer-less converters. Among these strategies, using common-ground converters is considered the most effective solution as it offers a solid connection between the negative terminal of PV modules and the neutral of the grid side; thus, complete mitigation of the leakage current is achieved. Number of common-ground inverters have been recently presented. These inverters are different in their size, cost, boosting capability, the possibility of producing DC currents, and their capability to offer multilevel shaping of output voltage. This work introduces a comprehensive review and classification for various common-ground PV inverters. Therefore, a clear picture of the advantages and disadvantages of these inverters is clarified. This provides a useful indication for a trade-off between gaining some of the advantages and losing others in PV systems. In addition, the potentials for optimization based on different performance indicators are identified. Full article
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