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Electronics
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Photovoltaic Systems for Sustainable Energy
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Photovoltaic Systems for Sustainable Energy

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

Deadline for manuscript submissions: closed (15 September 2020) | Viewed by 36519

Special Issue Editor

Dr. Taha Selim Ustun

E-Mail Website
Guest Editor
Power System Automation and Cybersecurity Lab, Fukushima Renewable Energy Institute, Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, Japan
Interests: power system protection; renewable energy; microgrid design; electric vehicle–grid integration; smart grid communications; substation automation; IEC 61850; IEC 62351; cybersecurity for power systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Photovoltaic (PV) generation holds a special place among renewable energy technologies. PV systems can be implemented from micro-to-macro scale. It can be the only power generation source of a poor house or a multi-megawatt power plant in the desert. Recent developments in material science have, dramatically, increased the efficiency of PV systems. At the same time, costs have plummeted continuously. All these developments made PV systems very popular due to several technical, economical, and environmental benefits.

The successful implementation of PV systems, be it stand-alone or grid-connected, relies on several factors. Potential estimation, correct sizing, power electronics, energy conversion, grid stability, dynamic interactions, power quality, power system stability, public policy, investment, and incentives are all different parts of the puzzle for a smooth PV systems operation. This exciting research field includes fields such as data analysis, public policy, power electronics, power systems modeling, and analysis. In addition, recent advances in communication and control extended to PV systems to enable standardized communication and different optimization control techniques such as fuzzy logic or neural networks.

In short, PV systems hold a key position in renewable energy field. There are research questions that belong to a wide variety of engineering branches. This Special Issue solicits papers that relate to the successful planning, investment, application, and operation of PV systems. This Special Issue focuses on the following topics (including but not limited to the following):

  • PV materials, including new and further developed solutions, modeling, and simulations;
  • PV cells and modules;
  • Power electronics devices (inverters, controllers, etc.);
  • PV solutions for off-grid and grid-connected operation;
  • Novel optimization and control techniques (fuzzy logic, neural networks, partical swarm optimization, ant colonies, and the like);
  • Studies for solar potential estimation and PV sizing;
  • Modeling, simulation, and stability analysis of PV systems;
  • Schemes for increased PV penetration (e.g., coordination with EVs, or storage);
  • New controller designs, e.g., virtual synchronous generator, grid-forming inverters, smart inverters;
  • Performance analysis of PV panels;
  • Economic analysis for PV systems;
  • Renewable energy policy and incentive studies for increased PV penetration.

Contributions reporting original theoretical works as well as experiences in practical implementations are of interest. Especially for practical works, negative results are also encouraged. Also, critical review papers on technologies, policies, and financial aspects of PV systems are considered for publication. I would like to cordially invite to contribute to this Special Issue.

Dr. Taha Selim Ustun
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. Electronics 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.

Keywords

  • Power system optimization
  • Artificial intelligence for power systems
  • Renewable energy
  • Impacts of PV on power systems
  • Dynamical modeling and simulation of PV systems
  • Control of grid-connected PV systems
  • Economic analysis
  • Policy studies for increased PV penetration
  • Power quality enhancement of PV systems
  • Solar resource assessment and PV sizing.

Published Papers (8 papers)

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Research

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22 pages, 3552 KiB  
Article
Neuro-Fuzzy-Based Model Predictive Energy Management for Grid Connected Microgrids
by Ahsen Ulutas, Ismail Hakki Altas, Ahmet Onen and Taha Selim Ustun
Electronics 2020, 9(6), 900; https://doi.org/10.3390/electronics9060900 - 28 May 2020
Cited by 23 | Viewed by 3535
Abstract
With constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may [...] Read more.
With constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may prove to be economical in the long run. However, the intermittent character of renewable energy sources is a major disadvantage. It is important to integrate them with the rest of the grid so that their benefits can be reaped while their negative impacts can be mitigated. In this article, an energy management algorithm is recommended for a grid-connected microgrid consisting of loads, a photovoltaic (PV) system and a battery for efficient use of energy. A model predictive control-inspired approach for energy management is developed using the PV power and consumption estimation obtained from daylight solar irradiation and temperature estimation of the same area. An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system. The proposed system is compared with a rule-based control strategy. Results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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18 pages, 5781 KiB  
Article
A Fast GMPPT Algorithm Based on PV Characteristic for Partial Shading Conditions
by Mustafa Engin Başoğlu
Electronics 2019, 8(10), 1142; https://doi.org/10.3390/electronics8101142 - 09 Oct 2019
Cited by 8 | Viewed by 3227
Abstract
Photovoltaic (PV) modules experience some partial shading conditions (PSC) due to some various factors. In that kind of a condition, a few maximum power points (MPPs) possibly appear on the power-voltage (P-V) curve, which increases the tracking difficulties. It is known that maximum [...] Read more.
Photovoltaic (PV) modules experience some partial shading conditions (PSC) due to some various factors. In that kind of a condition, a few maximum power points (MPPs) possibly appear on the power-voltage (P-V) curve, which increases the tracking difficulties. It is known that maximum power point tracking (MPPT) may not be realized by hill climbing (HC) based conventional MPPT algorithms under PSCs. In this context, this paper presents a novel micro converter based algorithm that was developed by using P-V characteristics of PV modules. Unlike voltage or duty ratio scanning techniques, this paper introduces a new deciding method to determine the correct global MPP (GMPP) region. For this, the proposed method uses some duty ratios that were calculated corresponding to each MPP region. Thus, the initialization of duty ratio is done properly, which results in high tracking speed and accurate tracking of the GMPP. The other advantages of the proposed algorithm are structural simplicity, less computational burden, and ease of implementation with a basic microcontroller. The simulation results show that this algorithm has fast tracking capability and it manages to track GMPP for PSCs correctly, since it includes an artificial scanning procedure. Single ended primary inductance converter (SEPIC) is built in order to validate the proposed global maximum power point tracking (GMPPT) algorithm. The performance of the proposed GMPPT technique is verified by experimental studies. The results show that the proposed GMPPT technique is fast by up to five times than an adaptive full scanning strategy and improved IC algorithm. Furthermore, the proposed algorithm can be commercially used in micro converters, since it is compatible with small number of bypass diodes in a module. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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16 pages, 4853 KiB  
Article
Design and Performance Analysis of a Stand-alone PV System with Hybrid Energy Storage for Rural India
by Kashif Javed, Haroon Ashfaq, Rajveer Singh, S.M. Suhail Hussain and Taha Selim Ustun
Electronics 2019, 8(9), 952; https://doi.org/10.3390/electronics8090952 - 28 Aug 2019
Cited by 58 | Viewed by 6696
Abstract
The operations of domestic stand-alone Photovoltaic (PV) systems are mostly dependent on storage systems due to changing weather conditions. For electrical energy storage, batteries are widely used in stand-alone PV systems. The performance and life span of batteries depend on charging/discharging cycles. Fluctuation [...] Read more.
The operations of domestic stand-alone Photovoltaic (PV) systems are mostly dependent on storage systems due to changing weather conditions. For electrical energy storage, batteries are widely used in stand-alone PV systems. The performance and life span of batteries depend on charging/discharging cycles. Fluctuation in weather conditions causes batteries to charge/discharge quite often, which decreases the operational life and increases the maintenance cost. This paper proposes a domestic stand-alone PV system with Hybrid Energy Storage System (HESS) that is a combination of battery and supercapacitor. A new Fuzzy Logic Control Strategy (FHCS) is implemented to control the power flow of the battery and supercapacitor. Simulation studies are performed with real data collected in Sultanpur, India to investigate the proposed system’s performance (Latitude [N] 26.29 and Longitude [E] 82.08). The results show that FHCS successfully controls the power flow of HESS components to increase the system efficiency. The developed system is validated to provide an effective alternative that would enhance the battery life span and reduce the system maintenance cost. While considering the prohibitive upfront costs for rural systems, such an improvement helps to electrify more underserved communities. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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20 pages, 7684 KiB  
Article
Design of an Efficient Maximum Power Point Tracker Based on ANFIS Using an Experimental Photovoltaic System Data
by Sadeq D. Al-Majidi, Maysam F. Abbod and Hamed S. Al-Raweshidy
Electronics 2019, 8(8), 858; https://doi.org/10.3390/electronics8080858 - 02 Aug 2019
Cited by 42 | Viewed by 6044
Abstract
Maximum power point tracking (MPPT) techniques are a fundamental part in photovoltaic system design for increasing the generated output power of a photovoltaic array. Whilst varying techniques have been proposed, the adaptive neural-fuzzy inference system (ANFIS) is the most powerful method for an [...] Read more.
Maximum power point tracking (MPPT) techniques are a fundamental part in photovoltaic system design for increasing the generated output power of a photovoltaic array. Whilst varying techniques have been proposed, the adaptive neural-fuzzy inference system (ANFIS) is the most powerful method for an MPPT because of its fast response and less oscillation. However, accurate training data are a big challenge for designing an efficient ANFIS-MPPT. In this paper, an ANFIS-MPPT method based on a large experimental training data is designed to avoid the system from experiencing a high training error. Those data are collected throughout the whole of 2018 from experimental tests of a photovoltaic array installed at Brunel University, London, United Kingdom. Normally, data from experimental tests include errors and therefore are analyzed using a curve fitting technique to optimize the tuning of ANFIS model. To evaluate the performance, the proposed ANFIS-MPPT method is simulated using a MATLAB/Simulink model for a photovoltaic system. A real measurement test of a semi-cloudy day is used to calculate the average efficiency of the proposed method under varying climatic conditions. The results reveal that the proposed method accurately tracks the optimized maximum power point whilst achieving efficiencies of more than 99.3%. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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17 pages, 3523 KiB  
Article
A Novel Nature-Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA-GWO Algorithm for Partially Shaded Photovoltaic Systems
by Yihao Wan, Mingxuan Mao, Lin Zhou, Qianjin Zhang, Xinze Xi and Chen Zheng
Electronics 2019, 8(6), 680; https://doi.org/10.3390/electronics8060680 - 15 Jun 2019
Cited by 44 | Viewed by 4120
Abstract
To overcome the real-time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature-inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The proposed MPPT controller is achieved by combining salp swarm [...] Read more.
To overcome the real-time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature-inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The proposed MPPT controller is achieved by combining salp swarm algorithm (SSA) with grey wolf optimizer (GWO) (namely, SSA-GWO). The leader structure of the GWO algorithm is introduced into the basic SSA algorithm to enhance the global search capability. Numerical simulation on 13 benchmark functions was done to evaluate the proposed SSA-GWO algorithm. Finally, the MPPT performance on PV system with the proposed SSA-GWO algorithm under static and dynamic partial shading conditions was investigated and compared with conventional MPPT algorithms. The quantitative and simulation results validated the effectiveness and superiority of the proposed method. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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19 pages, 2335 KiB  
Article
Automated Network Topology Extraction Based on Graph Theory for Distributed Microgrid Protection in Dynamic Power Systems
by Taha Selim Ustun and Saqib Ayyubi
Electronics 2019, 8(6), 655; https://doi.org/10.3390/electronics8060655 - 10 Jun 2019
Cited by 14 | Viewed by 3376
Abstract
Unlike conventional grids, microgrids may utilize different connections and the overall topology can be variable. Considering this, it is required to develop a new protection concept/scheme for safe operation. Maintaining proper selective operation of the relays in these dynamic microgrid structures is a [...] Read more.
Unlike conventional grids, microgrids may utilize different connections and the overall topology can be variable. Considering this, it is required to develop a new protection concept/scheme for safe operation. Maintaining proper selective operation of the relays in these dynamic microgrid structures is a challenge itself. This requires monitoring the connections and updating time delays of the relays which will ensure the desired hierarchy in the system. In this paper, a novel approach has been taken where electrical networks are modeled according to graph theory. Smart algorithms, such as network graph discovery, local manager selection, and protection coordination strategy, are run to automatically detect topology changes and ensure proper protection operation. Furthermore, distributed nature of this method mitigates the risks associated with central controller-based schemes. The developed method is applicable to all power system operations, and it poses a unique implementation in postdisaster recovery. After a disaster or terror attack, this self-diagnosis, self-healing system can identify healthy sections and run them as a standalone system until the relief arrives. The ability of the protection system to be run as a distributed control makes sure that any healthy part of the system can be restructured and utilized, without the dependency, on any central controller or connection. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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15 pages, 4142 KiB  
Article
Photovoltaic Module Array Global Maximum Power Tracking Combined with Artificial Bee Colony and Particle Swarm Optimization Algorithm
by Kuei-Hsiang Chao and Cheng-Chieh Hsieh
Electronics 2019, 8(6), 603; https://doi.org/10.3390/electronics8060603 - 29 May 2019
Cited by 7 | Viewed by 2519
Abstract
In this study, the output characteristics of partial modules in a photovoltaic module array when subject to shading were first explored. Then, an improved particle swarm optimization (PSO) algorithm was applied to track the global maximum power point (MPP), with a multi-peak characteristic [...] Read more.
In this study, the output characteristics of partial modules in a photovoltaic module array when subject to shading were first explored. Then, an improved particle swarm optimization (PSO) algorithm was applied to track the global maximum power point (MPP), with a multi-peak characteristic curve. The improved particle swarm optimization algorithm proposed, combined with the artificial bee colony (ABC) algorithm, was used to adjust the weighting, cognition learning factor, and social learning factor, and change the number of iterations to enhance the tracking performance of the MPP tracker. Finally, MATLAB software was used to carry out a simulation and prove the improved that the PSO algorithm successfully tracked the MPP in the photovoltaic array output curve with multiple peaks. Its tracking performance is far superior to the existing PSO algorithm. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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Review

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18 pages, 3005 KiB  
Review
The Emerging Energy Internet: Architecture, Benefits, Challenges, and Future Prospects
by S. M. Suhail Hussain, Furquan Nadeem, Mohd Asim Aftab, Ikbal Ali and Taha Selim Ustun
Electronics 2019, 8(9), 1037; https://doi.org/10.3390/electronics8091037 - 15 Sep 2019
Cited by 57 | Viewed by 6180
Abstract
Energy Internet is a concept proposed to harness, control, and manage energy resources effectively, with the help of information and communication technology. It improves a reliability of the system, and provides an increased utilization of energy resources by integrating the smart grid with [...] Read more.
Energy Internet is a concept proposed to harness, control, and manage energy resources effectively, with the help of information and communication technology. It improves a reliability of the system, and provides an increased utilization of energy resources by integrating the smart grid with the Internet. A scalable and reliable information and communication architecture is a crucial factor for both the operation and management of the energy Internet. The routing or managing of electrical energy is performed through an energy router (ER), synonymous with a communication router, which routes data packets instead of energy packets. In this paper, a holistic review of the energy Internet evolution in terms of the architecture, types of ERs, and the benefits and challenges of its implementation is presented. An exhaustive summary of the designs and architectures of the different types of ERs is also presented in this paper. The benefits of the energy Internet, along with the challenges of its implementation on a large-scale distributed architecture with the inclusion of renewable energy resources, is discussed. Finally, future prospects for the energy Internet for achieving guaranteed reliability and security is presented. Full article
(This article belongs to the Special Issue Photovoltaic Systems for Sustainable Energy)
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