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Electronics
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Photovoltaic Energy Systems and Storage
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Photovoltaic Energy Systems and Storage

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

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 8664

Special Issue Editor

Dr. Alan Morrison

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, School of Engineering, University College Cork, College Road, Cork T12 YN60, Ireland
Interests: optoelectronics; photovoltaics; PV systems; battery storage

Special Issue Information

Dear Colleagues,

Innovations in photovoltaic (PV) technology, including higher efficiency solar cells, newer materials technologies, improved energy storage, and better energy management have been key drivers for increased adoption of PV systems. PV energy systems, ranging in scale from milliwatts to gigawatts, serve a myriad of applications from energy harvesting to power the Internet of Things (IoT), integration into building infrastructure, to grid-connected utility-scale PV farms. As a stand-alone technology, PV energy systems are increasingly being used by industry in emerging economies to achieve grid autonomy.

This Special Issue of Electronics is focused on photovoltaic energy systems and storage, for both grid-connected and stand-alone system operation.

The main topics of interest for this issue include, but are not limited to:

  • Novel scalable PV technologies
  • PV system monitoring and optimization
  • PV energy management
  • Scalable system design incorporating energy storage
  • Energy storage opportunities, technologies and management
  • Battery storage systems
  • Grid defection strategies using PV systems
  • PV systems from micro-scale to utility scale
  • Concentrator PV systems
  • Building integrated photovoltaics and applications
  • Feasibility and comparison between existing and emerging PV technologies
  • Hybrid energy systems design
  • Modelling and simulation of PV energy systems
  • PV and energy systems reliability, degradation and failure prediction

Dr. Alan Morrison
Guest Editor

Manuscript Submission Information

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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

  • Photovoltaic systems
  • Energy storage
  • Battery storage
  • PV technology
  • PV system design
  • Module degradation
  • System reliability
  • Hybrid energy systems
  • Simulation and modelling of PV systems with energy storage

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Published Papers (3 papers)

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Research

17 pages, 3700 KiB  
Article
Forecasting of Photovoltaic Power by Means of Non-Linear Auto-Regressive Exogenous Artificial Neural Network and Time Series Analysis
by Mohamed Louzazni, Heba Mosalam and Daniel Tudor Cotfas
Electronics 2021, 10(16), 1953; https://doi.org/10.3390/electronics10161953 - 13 Aug 2021
Cited by 21 | Viewed by 2897
Abstract
In this research paper, a nonlinear autoregressive with exogenous input (NARX) model of the nonlinear system based on neural network and time series analysis is proposed to deal with the one-month forecast of the produced power from photovoltaic modules (PVM). The PVM is [...] Read more.
In this research paper, a nonlinear autoregressive with exogenous input (NARX) model of the nonlinear system based on neural network and time series analysis is proposed to deal with the one-month forecast of the produced power from photovoltaic modules (PVM). The PVM is a monocrystalline cell with a rated production of 175 watts that is placed at Heliopolis University, Bilbéis city, Egypt. The NARX model is considered powerful enough to emulate the nonlinear dynamic state-space model. It is extensively performed to resolve a variety of problems and is mainly important in complex process control. Moreover, the NARX method is selected because of its quick learning and completion times, as well as high appropriateness, and is distinguished by advantageous dynamics and interference resistance. The neural network (NN) is trained and optimized with three algorithms, the Levenberg–Marquardt Algorithm (NARX-LMA), the Bayesian Regularization Algorithm (NARX-BRA) and the Scaled Conjugate Gradient Algorithm (NARX-SCGA), to attain the best performance. The forecasted results using the NARX method based on the three algorithms are compared with experimentally measured data. The NARX-LMA, NARX-BRA and NARX-SCGA models are validated using statistical criteria. In general, weather conditions have a significant impact on the execution and quality of the results. Full article
(This article belongs to the Special Issue Photovoltaic Energy Systems and Storage)
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25 pages, 5807 KiB  
Article
Multi-Objective Energy Management Strategy for PV/FC Hybrid Power Systems
by Nicu Bizon and Phatiphat Thounthong
Electronics 2021, 10(14), 1721; https://doi.org/10.3390/electronics10141721 - 18 Jul 2021
Viewed by 2098
Abstract
In this paper, a new control of the DC–DC power converter that interfaces the fuel cell (FC) system with the DC bus of the photovoltaic (PV) power system is proposed to increase the battery lifespan by its operating in charge-sustained mode. Thus, the [...] Read more.
In this paper, a new control of the DC–DC power converter that interfaces the fuel cell (FC) system with the DC bus of the photovoltaic (PV) power system is proposed to increase the battery lifespan by its operating in charge-sustained mode. Thus, the variability of the PV power and the load demand is compensated by the FC power generated considering the power flows balance on the DC bus. During peak PV power, if the PV power exceeds the load demand, then the excess power on the DC bus will power an electrolyzer. The FC system operation as a backup energy source is optimized using a new fuel economy strategy proposed for fueling regulators. The fuel optimization function considers the fuel efficiency and electrical efficiency of the FC system to maximize fuel economy. The fuel economy obtained in the scenarios considered in this study is compared with reference strategies reported in the literature. For example, under scenarios considered in this paper, the fuel economy is between 4.82–20.71% and 1.64–3.34% compared to a commercial strategy based on static feed-forward (sFF) control and an advanced strategy recently proposed in the literature, respectively. Full article
(This article belongs to the Special Issue Photovoltaic Energy Systems and Storage)
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16 pages, 4868 KiB  
Article
Reconfigurable Distributed Power Electronics Technique for Solar PV Systems
by Kamran Ali Khan Niazi, Yongheng Yang, Tamas Kerekes and Dezso Sera
Electronics 2021, 10(9), 1121; https://doi.org/10.3390/electronics10091121 - 10 May 2021
Cited by 5 | Viewed by 2638
Abstract
A reconfiguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a [...] Read more.
A reconfiguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a voltage boosting capability to the PV system under no mismatch by connected the available PV cells/panels in series. The technique performs a reconfiguration by measuring the PV cell/panel voltages and their irradiances. The power balancing is achieved by charge redistribution through SC under mismatch conditions, e.g., partial shading. Moreover, PV cells/panels remain in series under no mismatch. Overall, this paper analyzes, simulates, and evaluates the effectiveness of the proposed DPP architecture through a simulation-based model prepared in PSIM. Additionally, the effectiveness is also demonstrated by comparing it with existing conventional DPP and traditional bypass diode architecture. Full article
(This article belongs to the Special Issue Photovoltaic Energy Systems and Storage)
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