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Electronics
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Power Electronics and Renewable Energy System
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Power Electronics and Renewable Energy System

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

Deadline for manuscript submissions: 31 October 2024 | Viewed by 4694

Special Issue Editor

Dr. Francisco Javier Ruiz-Rodríguez

E-Mail Website
Guest Editor
Department of Electrical and Thermal Engineering, Higher Technical School of Engineering, University of Huelva, Avda. Fuerzas Armadas, s/n, 21007 Huelva, Spain
Interests: power system analysis; renewable energy; distributed generation; power quality; power electronics; electric vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

At present, we must construct a sustainable global energy system to stop climate change. In this sense, the electricity and transport sectors play an important role. The transition towards an renewable energies and the progressive implementation of electric vehicles are necessary.

Power electronics refers to the application of electronic devices to control and transform electrical energy. This technology is essential for the operation of renewable energy systems, as well as the charging of electric vehicles.

They are being increasingly used to reduce dependence on fossil fuels and achieve a cleaner, more sustainable future.

The topics to be addressed in the Special Issue include (but are not limited to):

  • Power electronics in renewable energy sources.
  • Power flow control and optimization.
  • Electrical energy efficiency in industry, buildings, transmission and distribution, etc.
  • Modeling, simulation and control of power electronic converters.
  • Analysis of the uncertainty generated by renewable sources and electric vehicles.
  • High/Medium-voltage DC systems.
  • Grid planning with large-scale renewable energy resources.
  • Renewable energy conversion systems: design, modelling, control and integration to modern power systems.
  • Power and energy quality in electric systems with renewable energy resources.
  • Power electronics and control in microgrids.

Dr. Francisco Javier Ruiz-Rodríguez
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

  • voltage control
  • microgrid and smart grid
  • renewable energy sources
  • electric vehicles
  • photovoltaics
  • wind power
  • optimization
  • power electronics
  • power quality
  • electric systems
  • uncertainty
  • MVDC system
  • energy efficiency

Published Papers (5 papers)

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Research

17 pages, 7201 KiB  
Article
Control and Managing of Individual Solar Water Heating Systems in an Apartment Complex
by Michael Krinitsky and Moshe Averbukh
Electronics 2024, 13(12), 2305; https://doi.org/10.3390/electronics13122305 - 13 Jun 2024
Viewed by 686
Abstract
Managing solar energy utilization and water heating in multi-apartment buildings presents formidable challenges due to limited space for solar collector installation. Optimizing heat energy distribution among communal consumers is crucial, necessitating precise regulation of hot water flow from the main system line to [...] Read more.
Managing solar energy utilization and water heating in multi-apartment buildings presents formidable challenges due to limited space for solar collector installation. Optimizing heat energy distribution among communal consumers is crucial, necessitating precise regulation of hot water flow from the main system line to individual thermal storage tanks. The objective is to minimize heat and electricity losses while maximizing temperature levels in each tank. An electronic control system, centered around a microcontroller, has been developed with an efficient algorithm, data storage memory, and communication capabilities. The implemented solar heating system is tailored to each individual consumer, incorporating precise measurements for every apartment. This customization enhances efficiency not only for the individual consumer but also benefits the overall solar system within the building. This article explores the development and past outcomes of implementing such a control system, highlighting its significant advantages, particularly in multi-story buildings. Full article
(This article belongs to the Special Issue Power Electronics and Renewable Energy System)
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17 pages, 1124 KiB  
Article
A Multi-Step-Ahead Photovoltaic Power Forecasting Approach Using One-Dimensional Convolutional Neural Networks and Transformer
by Jihoon Moon
Electronics 2024, 13(11), 2007; https://doi.org/10.3390/electronics13112007 - 21 May 2024
Viewed by 555
Abstract
Due to environmental concerns about the use of fossil fuels, renewable energy, especially solar energy, is increasingly sought after for its ease of installation, cost-effectiveness, and versatile capacity. However, the variability in environmental factors poses a significant challenge to photovoltaic (PV) power generation [...] Read more.
Due to environmental concerns about the use of fossil fuels, renewable energy, especially solar energy, is increasingly sought after for its ease of installation, cost-effectiveness, and versatile capacity. However, the variability in environmental factors poses a significant challenge to photovoltaic (PV) power generation forecasting, which is crucial for maintaining power system stability and economic efficiency. In this paper, a novel muti-step-ahead PV power generation forecasting model by integrating single-step and multi-step forecasts from various time resolutions was developed. One-dimensional convolutional neural network (CNN) layers were used for single-step forecasting to capture specific temporal patterns, with the transformer model improving multi-step forecasting by leveraging the combined outputs of the CNN. This combination can provide accurate and immediate forecasts as well as the ability to identify longer-term generation trends. Using the DKASC-ASA-1A and 1B datasets for empirical validation, several preprocessing methods were applied and a series of experiments were conducted to compare the performance of the model with other widely used deep learning models. The framework proved to be capable of accurately predicting multi-step-ahead PV power generation at multiple time resolutions. Full article
(This article belongs to the Special Issue Power Electronics and Renewable Energy System)
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21 pages, 9425 KiB  
Article
Power Hardware-in-the-Loop Smart Inverter Testing with Distributed Energy Resource Management Systems
by Hao Chang and Luigi Vanfretti
Electronics 2024, 13(10), 1866; https://doi.org/10.3390/electronics13101866 - 10 May 2024
Viewed by 964
Abstract
The increasing integration of grid-connected photovoltaic (PV) inverters and inverter-based resource (IBR) systems into the power grid emphasizes the critical need for standardized procedures to ensure their reliability and effective grid support functions. This research is driven by the gap in standardized testing [...] Read more.
The increasing integration of grid-connected photovoltaic (PV) inverters and inverter-based resource (IBR) systems into the power grid emphasizes the critical need for standardized procedures to ensure their reliability and effective grid support functions. This research is driven by the gap in standardized testing methodologies for smart inverters, which are pivotal for the stability and quality of power in distributed energy systems. We used a Power Hardware-in-the-Loop (PHIL) laboratory setup to conduct a comprehensive analysis of smart inverters within a simulated real-world grid environment. Our approach integrates a Distributed Energy Resource Management System (DERMS) with PHIL testing to evaluate the smart inverter’s performance across various operational modes. The detailed test protocols mimic real-world grid conditions, enabling the examination of the inverter’s dynamic response to grid disturbances, control strategies, and communication protocols. The primary aim of this study is to rigorously test and validate the primary functions of smart inverters, focusing on their impact on overall grid stability and power quality management. This includes advanced features like Volt–VAR, Volt–Watt, dynamic power factor control, and the seamless integration of smart inverters into DERMSs and Advanced Distribution Management Systems (ADMSs). Furthermore, we aim to bridge the current gap in standardized testing procedures, contributing to the establishment of robust standards and operating protocols for smart inverter integration into the grid. Full article
(This article belongs to the Special Issue Power Electronics and Renewable Energy System)
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21 pages, 7100 KiB  
Article
Robust EMPC-Based Frequency-Adaptive Grid Voltage Sensorless Control for an LCL-Filtered Grid-Connected Inverter
by Yubin Kim, Thuy Vi Tran and Kyeong-Hwa Kim
Electronics 2024, 13(5), 998; https://doi.org/10.3390/electronics13050998 - 6 Mar 2024
Viewed by 659
Abstract
A robust explicit model predictive control (EMPC)-based frequency-adaptive grid voltage sensorless control is developed for a grid-connected inverter (GCI) via a linear matrix inequality (LMI) approach under the model parametric uncertainties as well as distorted and imbalanced grid voltages. In order to ensure [...] Read more.
A robust explicit model predictive control (EMPC)-based frequency-adaptive grid voltage sensorless control is developed for a grid-connected inverter (GCI) via a linear matrix inequality (LMI) approach under the model parametric uncertainties as well as distorted and imbalanced grid voltages. In order to ensure the quality of grid currents injected into the utility grid even when the system model parameters vary, the proposed control scheme is accomplished by an enhanced prediction model rather than the conventional prediction model obtained by fixed parameters. Furthermore, an LMI-based observer is integrated with the disturbance observer to improve the reference tracking performance and to reject disturbances. The proposed observer is employed for the grid frequency-adaptive control without the need for grid voltage sensors. The proposed current controller and observer employ the LMI scheme to maintain a stable and robust operation of the GCI. The discrete-time frequency response and pole-zero map analyses are utilized to examine the system performance including the stability and robustness against parametric uncertainties. Comprehensive simulation and experimental tests as well as theoretical analyses clearly validate the robustness of the proposed control scheme under various harsh test conditions with non-ideal and unexpected grid and system parametric uncertainties. Full article
(This article belongs to the Special Issue Power Electronics and Renewable Energy System)
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22 pages, 4278 KiB  
Article
Vulnerability Analysis of Power Transmission Grids Subject to Cascading Failures
by Francesco Cadini, Luca Lomazzi and Enrico Zio
Electronics 2024, 13(5), 943; https://doi.org/10.3390/electronics13050943 - 29 Feb 2024
Viewed by 728
Abstract
Cascading failures are a major threat to interconnected systems, such as electrical power transmission networks. Typically, approaches proposed for devising optimized control strategies are demonstrated with reference to a few test systems of reference (IEEE systems). However, this limits the robustness of the [...] Read more.
Cascading failures are a major threat to interconnected systems, such as electrical power transmission networks. Typically, approaches proposed for devising optimized control strategies are demonstrated with reference to a few test systems of reference (IEEE systems). However, this limits the robustness of the proposed strategies with respect to different power grid structures. Recently, this issue has been addressed by considering synthetic networks randomly generated for mimicking power transmission grids’ characteristics. These networks can be used for investigating the vulnerability of power networks to cascading failures. In this work, we propose to apply a recent algorithm for sampling random power grid topologies with realistic electrical parameters and further extend it to the random allocation of generation and load. Integration with a realistic cascade simulation tool, then, allows us to perform thorough statistical analyses of power grids with respect to their cascading failure behavior, thus offering a powerful tool for identifying the strengths and weaknesses of different grid classes. New metrics for ranking the control and mitigation effort requirements of individual cascade scenarios and/or of grid configurations are defined and computed. Finally, genetic algorithms are used to identify strategies to improve the robustness of existing power networks. Full article
(This article belongs to the Special Issue Power Electronics and Renewable Energy System)
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