Special Issue "Emerging Technologies for Photovoltaic Solar Energy"

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

Deadline for manuscript submissions: closed (30 October 2021).

Special Issue Editors

Prof. Dr. Luis M. Fernández-Ramírez
E-Mail Website
Guest Editor
Research Group in Electrical Technologies for Sustainable and Renewable Energy (PAIDI-TEP023), Department of Electrical Engineering, Higher Polytechnic School of Algeciras, University of Cadiz, Algeciras (Cádiz), Spain
Interests: smart grids; microgrids; renewable energy; wind energy; photovoltaic solar energy; energy storage systems; hydrogen and fuel cells; hybrid electric systems; electric vehicles; electric power systems; power converters and energy management/control systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Pablo García Triviño
E-Mail Website
Guest Editor
Research Group in Electrical Technologies for Sustainable and Renewable Energy (PAIDI-TEP023), Department of Electrical Engineering, Higher Polytechnic School of Algeciras, University of Cadiz, Algeciras (Cádiz), Spain
Interests: hydrogen and fuel cells; wind energy; photovoltaic solar energy; renewable energy; energy storage systems; hybrid electric systems; microgrids; smart grids; electric vehicles; power converters and energy management/control systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Photovoltaic (PV) solar energy has become one of the main renewable energy sources in the world as a result of the improvements and rapidly falling costs of the PV technology. This has led to PV systems that can be used in many applications, such as portable appliances, stand-alone or grid-connected electric power supplies for domestic, commercial, and industrial sectors, smart grids with renewable energy sources, and large-scale power plants. PV systems can be combined with other renewable energy sources and energy storage systems in hybrid power systems or smart grids in order to improve their generation capacity and efficiency. Power electronic converters play a key role in PV systems, since they allow to maximize the energy generated from irradiance (maximum power point tracking, MPPT), adapt the output of the PV system to the connection load/grid, and control the energy flow through them. The topologies of these converters, as well as functional control techniques, are also fundamental to make PV systems operate efficiently. Although the use of PV solar energy has significantly increased in recent years, new solutions must be developed to improve the efficiency and reduce the cost of the technology, which will allow to further increase the use of PV systems in the future.

This Special Issue aims to present recent advances and emerging technologies in PV solar energy and is focused and includes, but not limited to the following topics:

  • Solar potential estimation and PV systems sizing.
  • New developments in PV solar cells, modules, and arrays.
  • PV systems for portable, stand-alone, and grid-connected applications.
  • Large-scale PV power plants.
  • Smart grids with PV systems.
  • Hybrid power systems with PV solar energy.
  • Energy storage systems with PV solar energy.
  • Power converters for PV systems.
  • MPPT algorithms for PV systems.
  • Intelligent control methods of power converters for PV systems.
  • Monitoring, control, and management of PV systems.
  • PV solar energy forecasting methods.
  • Economics of PV systems.
  • State-of-the-art reviews on PV systems and applications.

Prof. Dr. Luis M. Fernández-Ramírez
Prof. Dr. Sonia Leva
Prof. Dr. Pablo García Triviño
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 papers will be 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 1800 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

  • PV solar energy forecasting
  • PV system design
  • PV cells
  • PV solar energy applications
  • Large-scale PV power plants
  • Energy storage systems
  • Hybrid power systems
  • Smart grids
  • Power converters and control 
  • Monitoring, control and management 
  • Economics of PV systems

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
An Innovative Tunable Rule-Based Strategy for the Predictive Management of Hybrid Microgrids
Electronics 2021, 10(10), 1162; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10101162 - 13 May 2021
Cited by 2 | Viewed by 528
Abstract
This work proposes a methodology for the optimal training of rule-based management strategies, to be directly implemented in the industrial controller of hybrid off-grid microgrids. The parameters defining the control rules are optimally tuned resorting to different evolutionary algorithms, based on the expected [...] Read more.
This work proposes a methodology for the optimal training of rule-based management strategies, to be directly implemented in the industrial controller of hybrid off-grid microgrids. The parameters defining the control rules are optimally tuned resorting to different evolutionary algorithms, based on the expected operating conditions. The performance of the resulting management heuristics is compared with conventional approaches to optimal scheduling, including Mixed Integer Linear Programming (MILP) optimization, direct evolutionary scheduling optimization, and traditional non-trained heuristics. Results show how the trained heuristics achieve a performance very close to the global optimum found by the MILP solution, outperforming the other methods, and providing a single-layer commitment and dispatch algorithm which is easily deployable in the microgrid controller. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Article
Method for Estimating Solar Energy Potential Based on Photogrammetry from Unmanned Aerial Vehicles
Electronics 2020, 9(12), 2144; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9122144 - 14 Dec 2020
Cited by 5 | Viewed by 981
Abstract
This study presents a method to estimate the solar energy potential based on 3D data taken from unmanned aerial devices. The solar energy potential on the roof of a building was estimated before the placement of solar panels using photogrammetric data analyzed in [...] Read more.
This study presents a method to estimate the solar energy potential based on 3D data taken from unmanned aerial devices. The solar energy potential on the roof of a building was estimated before the placement of solar panels using photogrammetric data analyzed in a geographic information system, and the predictions were compared with the data recorded after installation. The areas of the roofs were chosen using digital surface models and the hemispherical viewshed algorithm, considering how the solar radiation on the roof surface would be affected by the orientation of the surface with respect to the sun, the shade of trees, surrounding objects, topography, and the atmospheric conditions. The results show that the efficiency percentages of the panels and the data modeled by the proposed method from surface models are very similar to the theoretical efficiency of the panels. Radiation potential can be estimated from photogrammetric data and a 3D model in great detail and at low cost. This method allows the estimation of solar potential as well as the optimization of the location and orientation of solar panels. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Article
Hybrid Power System Optimization in Mission-Critical Communication
Electronics 2020, 9(11), 1971; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9111971 - 22 Nov 2020
Viewed by 532
Abstract
One of the common problems faced by Telecommunication (TLC) companies is the lack of power supply, usually for those appliances with scarce chances of grid connection often placed in remote zones. This issue is more and more critical if the radio network has [...] Read more.
One of the common problems faced by Telecommunication (TLC) companies is the lack of power supply, usually for those appliances with scarce chances of grid connection often placed in remote zones. This issue is more and more critical if the radio network has the specific task of guaranteeing the so-called “mission-critical communications”. This manuscript aims to propose and assess a viable solution to optimize the power supply and maintenance operations required to assure the proper functionality in such critical and remote sites. In particular, the main goals are defining a method to select the critical sites in an extensive and composite radio system and designing the hybrid power system in a way to improve the service availability and technical-economic benefits of the whole mission-critical TLC system. Finally, the proposed method and related procedures are tested and validated in a real scenario. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Article
Very-Short-Term Power Prediction for PV Power Plants Using a Simple and Effective RCC-LSTM Model Based on Short Term Multivariate Historical Datasets
Electronics 2020, 9(2), 289; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9020289 - 08 Feb 2020
Cited by 19 | Viewed by 1266
Abstract
Improving the accuracy of very-short-term (VST) photovoltaic (PV) power generation prediction can effectively enhance the quality of operational scheduling of PV power plants, and provide a reference for PV maintenance and emergency response. In this paper, the effects of different meteorological factors on [...] Read more.
Improving the accuracy of very-short-term (VST) photovoltaic (PV) power generation prediction can effectively enhance the quality of operational scheduling of PV power plants, and provide a reference for PV maintenance and emergency response. In this paper, the effects of different meteorological factors on PV power generation as well as the degree of impact at different time periods are analyzed. Secondly, according to the characteristics of radiation coordinate, a simple radiation classification coordinate (RCC) method is proposed to classify and select similar time periods. Based on the characteristics of PV power time-series, the selected similar time period dataset (include power output and multivariate meteorological factors data) is reconstructed as the training dataset. Then, the long short-term memory (LSTM) recurrent neural network is applied as the learning network of the proposed model. The proposed model is tested on two independent PV systems from the Desert Knowledge Australia Solar Centre (DKASC) PV data. The proposed model achieving mean absolute percentage error of 2.74–7.25%, and according to four error metrics, the results show that the robustness and accuracy of the RCC-LSTM model are better than the other four comparison models. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Article
Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study
Electronics 2019, 8(12), 1434; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics8121434 - 01 Dec 2019
Cited by 13 | Viewed by 1130
Abstract
Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical [...] Read more.
Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG L a b 2 ) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Article
LLC Resonant Voltage Multiplier-Based Differential Power Processing Converter Using Voltage Divider with Reduced Voltage Stress for Series-Connected Photovoltaic Panels under Partial Shading
Electronics 2019, 8(10), 1193; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics8101193 - 20 Oct 2019
Cited by 3 | Viewed by 1442
Abstract
Partial shading on photovoltaic (PV) strings consisting of multiple panels connected in series is known to trigger severe issues, such as reduced energy yield and the occurrence of multiple power point maxima. Various kinds of differential power processing (DPP) converters have been proposed [...] Read more.
Partial shading on photovoltaic (PV) strings consisting of multiple panels connected in series is known to trigger severe issues, such as reduced energy yield and the occurrence of multiple power point maxima. Various kinds of differential power processing (DPP) converters have been proposed and developed to prevent partial shading issues. Voltage stresses of switches and capacitors in conventional DPP converters, however, are prone to soar with the number of panels connected in series, likely resulting in impaired converter performance and increased circuit volume. This paper proposes a DPP converter using an LLC resonant voltage multiplier (VM) with a voltage divider (VD) to reduce voltage stresses of switches and capacitors. The VD can be arbitrarily extended by adding switches and capacitors, and the voltage stresses can be further reduced by extending the VD. Experimental verification tests for four PV panels connected in series were performed emulating partial shading conditions in a laboratory and outdoor. The results demonstrated the proposed DPP converter successfully precluded the negative impacts of partial shading with mitigating the voltage stress issues. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
Show Figures

Figure 1

Back to TopTop