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

Deadline for manuscript submissions: 15 July 2026 | Viewed by 3008

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Special Issue Editor

Prof. Dr. Maciej Zdanowski

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Guest Editor

Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76, 45-758 Opole, Poland
Interests: high voltage engineering; electrical insulation and materials; condition monitoring and diagnostics of power equipment

Special Issue Information

Dear Colleagues,

Power transformers play a critical role in ensuring reliable and efficient operation of electrical power systems. While traditionally perceived as mature technologies, they are now undergoing significant innovation in response to evolving grid architectures, the growing integration of renewable energy sources, increasing demands for digitalization, and the global push for sustainability. This Special Issue aims to highlight and disseminate cutting-edge research on the design, operation, diagnostics, monitoring, optimization, and future concepts of power transformers.

We invite original research articles, case studies, and high-quality review papers that explore recent developments in power transformer engineering. Both conventional (oil-immersed, dry-type) and advanced technologies (solid-state, hybrid, high-temperature, and digital transformers) are welcome.

Topics of interest include, but are not limited to, the following:

Smart condition monitoring and predictive diagnostics;
Artificial intelligence and machine learning in asset health management;
Electromagnetic, thermal, and mechanical modeling;
Partial discharge, DGA, FRA, and other advanced diagnostic tools;
Life-cycle analysis and insulation aging mechanisms;
Integration with renewable energy and microgrids;
Solid-state transformers and power electronics-based solutions;
Eco-friendly materials, sustainable insulation systems, and nanofluids;
Performance evaluation under dynamic loading conditions;
Optimization techniques for transformer design and performance.

This Special Issue aims to serve as a platform for collaboration and knowledge exchange among researchers, manufacturers, and grid operators. The collected contributions will help define the next generation of transformer technology that meets the expectations of digital grids and low-carbon energy infrastructure.

Prof. Dr. Maciej Zdanowski
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 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

power transformers
transformer insulation
thermal management
insulating materials
insulation oil
high voltage technology
transformer diagnostics
fault detection
advanced monitoring systems
transformer lifetime extension

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Published Papers (5 papers)

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Research

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29 pages, 3640 KB

Open AccessArticle

Linear and Nonlinear Feature Extraction for Transformer Partial Discharge Severity Classification: A Comparative Study Using Artificial Neural Networks

by Lucas Thobejane and Bonginkosi A. Thango

Energies 2026, 19(11), 2642; https://doi.org/10.3390/en19112642 (registering DOI) - 29 May 2026

Abstract

Accurate classification of transformer partial discharge (PD) severity is essential for insulation diagnostics yet remains challenging due to nonlinear feature relationships and class imbalance. This study evaluates whether feature extraction improves PD severity classification and compares the effectiveness of linear and nonlinear extraction methods. A dataset of 294 samples was categorized into four IEC-aligned severity classes. Two raw measurements (discharge magnitude and applied voltage) were expanded into a 15-dimensional feature space. Principal Component Analysis (PCA) and a bottleneck Autoencoder (AE) were used for linear and nonlinear feature extraction, respectively. Extracted features were classified using an identical Multilayer Perceptron (MLP). Both feature extraction methods improved classification performance over raw and full-feature baselines (96.6%). PCA+ANN achieved 100.0% accuracy (k = 9), while AE+ANN achieved 98.3% (k = 8). The AE misclassified one minority “Normal” sample due to poor latent boundary representation. Reconstruction analysis showed the highest error for the Normal class, reflecting imbalance-driven optimization bias. Feature extraction enhances PD severity classification, with linear PCA outperforming nonlinear AE in this near-linearly separable dataset. PCA’s deterministic projection preserves minority class boundaries more effectively, whereas AE performance is limited by class imbalance. These findings suggest that nonlinear methods provide advantages only in more complex feature spaces. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

21 pages, 1453 KB

Open AccessArticle

Life-Cycle Cost–Optimal Right-Sizing and Replacement Assessment of Distribution Transformers Under Demand Uncertainty

by Jorge Muñoz-Pilco, Milton Ruiz, Cristian Cuji and Edwin García

Energies 2026, 19(8), 1983; https://doi.org/10.3390/en19081983 - 20 Apr 2026

Viewed by 626

Abstract

This paper presents a scenario-based optimization framework for evaluating the life-cycle cost of right-sizing and replacement timing for distribution transformers under demand–growth uncertainty. The proposed formulation jointly considers the discrete commercial transformer ratings, the discounted investment cost, and the monetized iron and copper losses over a 15-year planning horizon. Demand uncertainty is represented by nine scenarios defined by combinations of initial apparent power demand and annual growth rate, with

D_{1} \in {45, 50, 55}

kVA and

g \in {3 %, 4 %, 5 %}

. Under these assumptions, the demand envelope evolves from an initial range of 45–55 kVA to approximately 68.1–108.9 kVA in Year 15, while expected demand increases from 50 kVA to about 87 kVA. The optimization results show that the economically optimal policy is to install a 112.5 kVA transformer in Year 1 and maintain that rating throughout the horizon, without triggering any replacement events. The selected transformer maintains expected loading between approximately 0.44 p.u. and 0.77 p.u., while the upper-demand scenario remains below 1.0 p.u. over the entire horizon. These results indicate that, for the demand–growth conditions analyzed, the preferred outcome is a single initial sizing decision rather than a phased replacement strategy. Therefore, the proposed framework provides a consistent scenario-based alternative to deterministic margin-based planning for distribution transformer asset management. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

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19 pages, 1563 KB

Open AccessArticle

A Partial Power Processing SEPIC Converter for Photovoltaic Applications

by Josué Francisco Rebullosa-Castillo, Pedro Martín García-Vite, Carolina Contreras-Alvarez, Jose de Jesus Chavez-Muro and Hector R. Robles-Campos

Energies 2026, 19(6), 1484; https://doi.org/10.3390/en19061484 - 16 Mar 2026

Viewed by 498

Abstract

This paper presents the analysis, design, and experimental validation of a Partial Power Processing (PPP) Single-Ended Primary Inductor Converter (SEPIC) for photovoltaic (PV) applications. The proposed topology limits the fraction of processed power through the active switching stage, thereby reducing MOSFET RMS current and associated conduction losses and improving overall conversion efficiency. A complete analytical framework is developed, including steady-state modeling, state-space formulation, and small-signal analysis. The theoretical results are validated through MATLAB/Simulink simulations and laboratory-scale experimental tests under multiple loading conditions. Comparative analysis against a conventional Full Power Processing (FPP) SEPIC converter demonstrates that the proposed PPP configuration achieves efficiencies up to 95% in simulation and up to 93% experimentally, compared to 87% for the FPP counterpart under identical nominal conditions (

V_{in} = 18

f_{s} = 70

kHz). Additionally, the PPP approach reduces the MOSFET RMS current by more than 50%, which directly translates into lower conduction losses and reduced device power dissipation. The results confirm that the proposed PPP-SEPIC converter constitutes a technically viable and energy-efficient solution for photovoltaic DC–DC power conversion systems. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

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28 pages, 3705 KB

Open AccessEditor’s ChoiceArticle

Transformer Iron Core Temperature Field Calculation Based on Finite Element Analysis

by Ziyang Chen, Zhenggang He and Shuhong Wang

Energies 2025, 18(24), 6537; https://doi.org/10.3390/en18246537 - 13 Dec 2025

Cited by 1 | Viewed by 828

Abstract

Temperature anomaly is a common fault in power transformers; therefore, achieving a fast and accurate calculation of the transformer temperature field is of great significance. This paper primarily introduces the methodology and self-programmed calculation for realizing the temperature field analysis of a single-phase, two-limb transformer iron core. First, the finite element equation for the three-dimensional steady-state temperature field is derived to provide the basis for the self-programmed Finite Element Method (FEM) calculation. Subsequently, the Finite Element Method (FEM) calculation of the single-phase, two-limb transformer iron core temperature field was implemented using the self-programmed code, and the results were compared with the COMSOL calculation results. The comparison showed that the error at each node was within 0.5 K. Compared to COMSOL, the computation time was reduced by 46.89%, and the memory usage was reduced by 82.37%. Finally, a temperature rise test was designed for the single-phase, two-limb transformer. Compared with the experimental data, the maximum error is within 3 K, which further confirms the accuracy of the program. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

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Review

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39 pages, 3155 KB

Open AccessReview

Electrifying the Future: Second- and Third-Generation Derived Oils for Transformers

by Arputhasamy Joseph Amalanathan, Susaimanickam Anto and Maciej Zdanowski

Energies 2026, 19(6), 1547; https://doi.org/10.3390/en19061547 - 20 Mar 2026

Viewed by 528

Abstract

The reliability of power transmission and distribution depends on the proper functioning of power transformers, which use conventional mineral oil as an insulating fluid. The lower fire class and biodegradability of mineral oil have led to a shift towards second-generation oils from vegetable and plant crops. Ester fluids provide a better performance in combination with solid pressboard/paper insulation, increasing the lifetime of power transformers compared to those using mineral oil. Considering the need for sustainability in the near future, second-generation oils are no longer feasible, and hence, third-generation oils derived from microalgae species are suitable alternative fuels for the energy sector. The fatty acid methyl ester (FAME) content of algae is similar to that of biodiesel, making it a suitable fluid for power transformers. A detailed overview of third-generation feedstock (algae) for power transformer applications is provided, focusing on the extraction of algal oil, in conjunction with safety precautions and its fatty acid content, and a comparison with conventional vegetable and plant-based oils is presented. Various properties of algal oil (fatty acid composition, kinematic viscosity, oxidation stability, breakdown voltage, etc.) are analyzed to assess its suitability as a transformer fluid. This review article comprehensively analyzes the current research landscape surrounding the use of algal oil as an insulating fluid in transformers. It critically evaluates both the potential advantages and the unique challenges associated with this alternative to conventional mineral oil and second-generation vegetable and plant-based oils. Full article

(This article belongs to the Special Issue Advancements in Power Transformers)

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