Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.2
Journals
Energies
Special Issues
Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced...
energies-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 25 August 2026 | Viewed by 4888

Special Issue Editors

Prof. Dr. Jacek Starzynski

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Warsaw University of Technology, Koszykowa 75, 00-662 Warszawa, Poland
Interests: numerical simulation of electrical devices (electromagnetic field, circuits and systems); construction of HV pulse generators; automated diagnostics of electrical and power electronics equipment (machine learning, deep neural networks)
Special Issues, Collections and Topics in MDPI journals
Dr. Bogdan Dziadak

E-Mail Website
Guest Editor
Electrical Engineering Department, Warsaw University of Technology, Plac Politechniki 1, 00-661 Warsaw, Poland
Interests: electrical engineering; design engineering; sensors; energy harvesting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern electrical engineering is at a groundbreaking stage of development, with intelligent systems, modern algorithms, and advanced technologies and materials shaping the future of energy, industry, and medicine. With the dynamic advancement of artificial intelligence and machine learning, new opportunities have emerged for process optimization, improved system efficiency, and enhanced infrastructure reliability.

This Special Issue focuses on research that integrates cutting-edge technologies with the challenges of electrical engineering, covering topics such as intelligent control systems, AI-assisted algorithms, and innovative approaches to signal analysis and processing. Particular emphasis is placed on groundbreaking solutions in renewable energy and energy harvesting, which play a key role in sustainable development and increasing energy efficiency. Additionally, we consider the safety and reliability of modern electrical systems, including methods for fault detection and failure prevention.

We invite researchers and engineers to submit articles presenting new concepts, methods, and applications in the field of intelligent systems and algorithms, as well as modern technologies supporting the advancement of energy and automation. The goal of this Special Issue is to create a platform for knowledge exchange and to inspire the further development of innovative solutions that could significantly impact the future of electrical engineering.

Prof. Dr. Jacek Starzynski
Dr. Bogdan Dziadak
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 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 250 words) can be sent to the Editorial Office for assessment.

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. Energies 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 2600 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

  • smart sensors
  • machine learning for automated control and diagnostics
  • energy harvesting
  • renewable sources
  • energy quality
  • WSN and IoT networks
  • signal processing
  • embedded systems technologies

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

15 pages, 5728 KB  
Article
Investigation of Subsurface Current Flow Using an Active Front-End Converter for Through-the-Soil Long-Range Wireless Power Transfer
by Olivia E. Nnadi, Christopher S. Johnson, Erlind Boraj, Charles W. van Neste and Ghadir Radman
Energies 2026, 19(4), 1080; https://doi.org/10.3390/en19041080 - 20 Feb 2026
Viewed by 389
Abstract
There is a strong demand for buried sensor networks in industries including mining, agriculture, geothermal energy, and oil/gas. However, the integration of these sensors is bottle-necked by the need for electric power which cannot be delivered by conventional means, i.e., cables, photocells, and [...] Read more.
There is a strong demand for buried sensor networks in industries including mining, agriculture, geothermal energy, and oil/gas. However, the integration of these sensors is bottle-necked by the need for electric power which cannot be delivered by conventional means, i.e., cables, photocells, and batteries. To mitigate this bottle-neck, a recent technique was developed that utilizes conduction currents through the soil and subsurface (TTS) to transfer power wirelessly over large distances. The work presented here further investigates changes in conducted power signals as they flow over a 50m radius around a buried TTS Transmitter. An Active Front-End (AFE) converter in tandem with an integrated inverter output is used for creating signals with large spectral densities in order to study attenuation effects throughout the subsurface. The changes in the signals’ spectral content over distance are analyzed and discussed. The abilities to separate attenuation from current spread (divergence) from attenuation due to resistive loss are given, allowing the identification of frequencies best suited for long range power transfer. Full article
(This article belongs to the Special Issue Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies)
►▼ Show Figures

Figure 1

12 pages, 832 KB  
Article
Fault Detection of High-Speed Train Traction System Based on Probability-Related Slow Feature Analysis
by Ruiting Zhang, Soon-Hyung Lee, Kyung-Min Lee and Yong-Sung Choi
Energies 2025, 18(22), 6073; https://doi.org/10.3390/en18226073 - 20 Nov 2025
Viewed by 643
Abstract
As the core subsystem of high-speed trains, the reliable operation of the traction system is critical to ensuring train safety. To enhance fault detection performance, this study proposes a probability-related slow feature analysis (PRSFA) method that leverages the intrinsic characteristics of the traction [...] Read more.
As the core subsystem of high-speed trains, the reliable operation of the traction system is critical to ensuring train safety. To enhance fault detection performance, this study proposes a probability-related slow feature analysis (PRSFA) method that leverages the intrinsic characteristics of the traction system. Specifically, Kullback–Leibler divergence is incorporated into the conventional slow feature analysis framework. Based on the slow features extracted from traction system data, the probability distribution distance between offline and online features is further computed to construct detection statistics. The feasibility of the proposed approach is validated using the high-speed train traction system simulation platform developed by Central South University. Compared with the existing SFA, DSFA and DWSFA methods, the results show that the PRSFA method can effectively improve the accuracy and robustness of fault detection. Full article
(This article belongs to the Special Issue Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies)
►▼ Show Figures

Figure 1

27 pages, 910 KB  
Article
QES Model Aggregating Quality, Environmental Impact, and Social Responsibility: Designing Product Dedicated to Renewable Energy Source
by Dominika Siwiec and Andrzej Pacana
Energies 2025, 18(15), 4029; https://doi.org/10.3390/en18154029 - 29 Jul 2025
Cited by 2 | Viewed by 898
Abstract
The complexity of assessment is a significant problem in designing renewable energy source (RES) products, especially when one wants to take into account their various aspects, e.g., technical, environmental, or social. Hence, the aim of the research is to develop a model supporting [...] Read more.
The complexity of assessment is a significant problem in designing renewable energy source (RES) products, especially when one wants to take into account their various aspects, e.g., technical, environmental, or social. Hence, the aim of the research is to develop a model supporting the decision-making process of RES product development based on meeting the criteria of quality, environmental impact, and social responsibility (QES). The model was developed in four main stages, implementing multi-criteria decision support methods such as DEMATEL (decision-making trial and evaluation laboratory) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), as well as criteria for social responsibility and environmental impact from the ISO 26000 standard. The model was tested and illustrated using the example of photovoltaic panels (PVs): (i) five prototypes were developed, (ii) 30 PV criteria were identified from the qualitative, environmental, and social groups, (iii) the criteria were reduced to 13 key (strongly intercorrelated) criteria according to DEMATEL, (iv) the PV prototypes were assessed taking into account the importance and fulfilment of their key criteria according to TOPSIS, and (v) a PV ranking was created, where the fifth prototype turned out to be the most advantageous (QES = 0.79). The main advantage of the model is its simple form and transparency of application through a systematic analysis and evaluation of many different criteria, after which a ranking of design solutions is obtained. QES ensures precise decision-making in terms of sustainability of new or already available products on the market, also those belonging to RES. Therefore, QES will find application in various companies, especially those looking for low-cost decision-making support techniques at early stages of product development (design and conceptualization). Full article
(This article belongs to the Special Issue Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies)
►▼ Show Figures

Figure 1

17 pages, 6392 KB  
Article
Energy Harvesting from AC Magnetic Field Using PZT Piezoelectric Cantilever Beams
by Mariusz Kucharek, Bogdan Dziadak, Jacek Starzyński and Leszek Książek
Energies 2025, 18(11), 2830; https://doi.org/10.3390/en18112830 - 29 May 2025
Viewed by 1943
Abstract
This article investigates energy harvesting methods designed to capture energy from the alternating magnetic field surrounding a current-carrying conductor. The study focuses on the use of piezoelectric transducers in both monolithic and bimorph configurations. Experimental tests were conducted using vibrating beam structures composed [...] Read more.
This article investigates energy harvesting methods designed to capture energy from the alternating magnetic field surrounding a current-carrying conductor. The study focuses on the use of piezoelectric transducers in both monolithic and bimorph configurations. Experimental tests were conducted using vibrating beam structures composed of a single-layer piezoelectric material as well as bimorph piezoelectric composites, both utilizing lead zirconate titanate (PZT) as the active material. The results demonstrate a significant improvement in energy harvesting efficiency when using the bimorph configuration. Specifically, the bimorph-based system generated a peak voltage of 4.26 V and a current of 127.16 μA, resulting in an RMS power output of 272.48 μW. The operating principles, signal conditioning strategies, and structural differences in the evaluated designs are discussed in detail. The outcomes indicate the potential of such systems for powering autonomous sensors in low-power industrial monitoring applications. Full article
(This article belongs to the Special Issue Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies)
►▼ Show Figures

Figure 1

Review

Jump to: Research

37 pages, 2020 KB  
Review
Modeling Energy Consumption in Open-Source MATLAB-Based WSN Environments for the Simulation of Cluster Head Selection Protocols
by Agnieszka Chodorek, Robert Ryszard Chodorek and Pawel Sitek
Energies 2026, 19(8), 1824; https://doi.org/10.3390/en19081824 - 8 Apr 2026
Viewed by 373
Abstract
Wireless sensor networks using battery-powered, low-cost sensors, due to their non-rechargeability and strictly limited energy resources, are more sensitive to energy efficiency than other networks of this type. Clustered wireless sensor networks address this problem. In these networks, the most energy-intensive communication, i.e., [...] Read more.
Wireless sensor networks using battery-powered, low-cost sensors, due to their non-rechargeability and strictly limited energy resources, are more sensitive to energy efficiency than other networks of this type. Clustered wireless sensor networks address this problem. In these networks, the most energy-intensive communication, i.e., a long-range one, is carried out via designated nodes, called cluster head nodes, while other cluster nodes communicate with their cluster heads. Cluster head node selection is handled by appropriate routing protocols, and newly designed protocols are first tested in simulations. Among the simulators of cluster head selection protocols, those implemented in a MATLAB environment play an important role, and among these, those implementing a first-order radio model to estimate the energy cost of transmission, both at the transmitter and at the receiver, play a particularly important role. This paper presents and discusses the energy aspects of MATLAB-based open-source wireless sensor network environments that employ the first-order radio model for the simulation of cluster head selection protocols. Current MATLAB-based open-source simulators of cluster head selection protocols were inventoried and analyzed. The review results showed that the first-order radio model had been used in its classic form for years, with the same default parameters. Although the simulators were written using different programming paradigms, precluding simple copy-and-paste, the first-order radio model was generally similar. However, there were exceptions to this rule. A hard exception is the simulator for a body-area wireless sensor network, which only implements a version of the first-order radio model specific to that environment. Soft exceptions are two simulators of the popular cluster head selection protocol, which implemented only half the functionality of the classic first-order radio model. On the one hand, this demonstrates both the widespread use of a conservative approach to the model, which ensures relatively easy repeatability of simulation results, and, on the other hand, the flexibility of the model, which allows its extension to other environments. Finally, the limitations of the model are presented and directions for future research are indicated. Full article
(This article belongs to the Special Issue Advances in Electrical Engineering: Intelligent Systems, Modern Algorithms and Advanced Technologies)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop