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Advanced Control Techniques for Power Electronics: Addressing Challenges in Renewable Energy System Applications

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

Deadline for manuscript submissions: closed (15 September 2025) | Viewed by 5265

Special Issue Editors

Dr. Tushar Kanti Roy

E-Mail Website
Guest Editor
School of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: dynamical modeling, stability, and control of power systems; robust adaptive control of modern power systems (with photovoltaic and wind generators); robust control of microgrids (AC, DC, and hybrid AC/DC)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Aman Maung Than Oo

E-Mail Website
Guest Editor
School of Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: polymer based ReRAM; microgrid & energy storage system; smart grid communication; power system stability; energy management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of renewable energy systems, electric vehicles, and smart grids has brought power electronics to the forefront of modern electrical engineering. Power electronics serve as a critical interface between energy sources and loads, ensuring efficient energy conversion and control. However, the increasing complexity of power systems, such as distributed energy resources, microgrids, and electric mobility, requires robust and advanced control methods to optimize performance, enhance stability, and ensure reliability under diverse operating conditions.

This Special Issue on advanced control methods for power electronics aims to explore cutting-edge solutions in control theory and their application to power electronic systems. The focus is on addressing the critical challenges that arise from the integration of renewable energy, hybrid AC/DC systems, energy storage, and more complex converter architectures.

This Special Issue will provide a platform for disseminating knowledge on state-of-the-art control methods, such as model predictive control, sliding mode control, adaptive control, robust and intelligent control methods, their applications in power electronic systems, and real-time simulation and experimental validation of advanced control systems. However, research areas may include (but are not limited to) the following:

  • Nonlinear Control in Power Electronics: New methods for addressing nonlinear dynamics in power converters and systems with constant power loads.
  • Model Predictive Control for Power Converters: Innovations in predictive control that enhance performance in high-power, high-speed converters.
  • Sliding Mode Control: Applications of sliding mode control in handling disturbances and ensuring robustness in energy conversion systems.
  • Artificial Intelligence and Machine Learning-based Control: Use of AI and ML techniques for adaptive, real-time control of power electronic systems.
  • Robust and Adaptive Control Techniques: Approaches to manage uncertainties and system variations in renewable energy systems, electric vehicles, and industrial applications.
  • Hybrid Control Strategies for Grid-Connected Systems: Advanced hybrid control strategies for integrating renewable energy sources and storage with AC/DC microgrids.
  • Stability and Dynamic Response in Complex Power Electronic Systems: Control strategies to improve dynamic response, voltage stability, and power quality in microgrids and smart grids.

We look forward to receiving your contributions.

Dr. Tushar Kanti Roy
Prof. Dr. Aman Maung Than Oo
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. 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

  • model predictive control
  • sliding mode control
  • AI in power electronics
  • ML-based control
  • robust and adaptive control
  • hybrid control for microgrids
  • Lyapunov system stability in power electronics
  • dynamic response in microgrids

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Published Papers (4 papers)

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Research

23 pages, 4110 KB  
Article
RBF Neural Network-Enhanced Adaptive Sliding Mode Control for VSG Systems with Multi-Parameter Optimization
by Jian Sun, Chuangxin Chen and Huakun Wei
Electronics 2025, 14(21), 4309; https://doi.org/10.3390/electronics14214309 - 31 Oct 2025
Cited by 1 | Viewed by 851
Abstract
Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed [...] Read more.
Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed power sources. This study addresses the degradation of transient performance in traditional sliding mode control for VSG, caused by insufficient multi-parameter cooperative adaptation. It proposes an adaptive sliding mode control strategy based on radial basis function (RBF) neural networks. Through theoretical analysis of the influence mechanism of virtual inertia and damping coefficient perturbations on system stability, the RBF neural network achieves dynamic parameter decoupling and nonlinear mapping. Combined with an integral-type sliding surface to design a weight-adaptive convergence law, it effectively avoids local optima and ensures global stability. This strategy not only enables multi-parameter cooperative adaptive regulation of frequency fluctuations but also significantly enhances the system’s robustness under parameter perturbations. Simulation results demonstrate that compared to traditional control methods, the proposed strategy exhibits significant advantages in dynamic response speed and overshoot suppression. Full article
(This article belongs to the Special Issue Advanced Control Techniques for Power Electronics: Addressing Challenges in Renewable Energy System Applications)
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15 pages, 2438 KB  
Article
A Three-Terminal Modular-Multilevel-Converter-Based Power Electronic Transformer with Reduced Voltage Stress for Meshed DC Systems
by Haiqing Cai, Jiajie Zang, Haohan Gu, Guohui Zeng, Wencong Wu, Wei Chen and Chunyang Zhai
Electronics 2025, 14(21), 4192; https://doi.org/10.3390/electronics14214192 - 27 Oct 2025
Viewed by 667
Abstract
The traditional DC distribution grid is evolving into a meshed structure to create additional energy exchange paths and integrate the rapidly growing renewable energy sources. However, existing converter stations lack sufficient power flow controllability, necessitating the development of multiport power electronic transformers to [...] Read more.
The traditional DC distribution grid is evolving into a meshed structure to create additional energy exchange paths and integrate the rapidly growing renewable energy sources. However, existing converter stations lack sufficient power flow controllability, necessitating the development of multiport power electronic transformers to address potential power flow congestion and high loss issues. This paper proposes a compact multi-terminal modular-multilevel-converter-based power electronic transformer (M3C-PET). This device enables flexible power flow regulation of the connected feeders through adopting two small-capacity power flow control modules (PFCMs). The simple structure and reduced switching count make the proposed PET more competitive and prominent and more cost-effective. Furthermore, this paper elaborates on the operational principle of the proposed device and presents a multilayer power balancing control strategy along with a power flow control scheme. These control strategies are designed based on the internal and external energy distribution mechanism of the proposed PET. The feasibility and effectiveness of the proposed topology and control schemes are rigorously validated through both a MATLAB/Simulink simulation model and a scaled-down experimental prototype. Full article
(This article belongs to the Special Issue Advanced Control Techniques for Power Electronics: Addressing Challenges in Renewable Energy System Applications)
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18 pages, 5294 KB  
Article
Energy Scheduling of PV–ES Inverters Based on Particle Swarm Optimization Using a Non-Linear Penalty Function
by Lei Wang, Wenle Song and Kai Sun
Electronics 2025, 14(11), 2272; https://doi.org/10.3390/electronics14112272 - 1 Jun 2025
Viewed by 855
Abstract
The photovoltaic (PV) energy storage (ES) inverter is an effective way to solve the problems of energy shortage and environment pollution. However, when considering the constraints such as economic benefits and power supply reliability, the energy optimization and dispatching of this PV–ES system [...] Read more.
The photovoltaic (PV) energy storage (ES) inverter is an effective way to solve the problems of energy shortage and environment pollution. However, when considering the constraints such as economic benefits and power supply reliability, the energy optimization and dispatching of this PV–ES system poses great challenges. This paper proposes an optimization method based on the combination of the particle swarm algorithm and non-linear penalty function to dispatch the energy of household PV–ES inverter. Based on the established optimization model of the PV–ES inverter system, compared with the static penalty function, the penalty factor can be automatically adjusted according to the range beyond the constraint by using the proposed non-linear penalty function. Furthermore, the particle swarm algorithm is used as the optimization engine, and the energy scheduling scheme is obtained by the combination of the particle swarm algorithm and the proposed non-linear penalty function. Finally, the simulation and hardware-in-the-loop results verify the correctness of the proposed algorithm, compared with the static penalty function, the user electricity expenses can be effectively reduced, and economic requirements can be met. Full article
(This article belongs to the Special Issue Advanced Control Techniques for Power Electronics: Addressing Challenges in Renewable Energy System Applications)
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21 pages, 10373 KB  
Article
A 75 kW Medium-Frequency Transformer Design Based in Inductive Power Transfer (IPT) for Medium-Voltage Solid-State Transformer Applications
by Juan Blanco-Ortiz, Eduardo García-Martínez, Ignacio González-Prieto and Mario J. Duran
Electronics 2025, 14(6), 1059; https://doi.org/10.3390/electronics14061059 - 7 Mar 2025
Cited by 3 | Viewed by 2210
Abstract
Solid-State Transformers (SSTs) enable significant improvements in size and functionality compared to conventional power transformers. However, one of the key challenges in Solid-State Transformer design is achieving reliable insulation between the high-voltage and low-voltage sections. This proposal presents the design and optimization of [...] Read more.
Solid-State Transformers (SSTs) enable significant improvements in size and functionality compared to conventional power transformers. However, one of the key challenges in Solid-State Transformer design is achieving reliable insulation between the high-voltage and low-voltage sections. This proposal presents the design and optimization of a high-insulation Medium-Frequency Transformer (MFT) for 66 kV grids operating at 50 kHz and delivering up to 75 kW for SST applications using Inductive Power Transfer (IPT) technology. A fixed 50 mm gap between the primary and secondary windings is filled with dielectric oil to enhance insulation. The proposed IPT system employs a double-D coil design developed through iterative 2D and 3D finite element method simulations to optimize the magnetic circuit, thereby significantly reducing stray flux and losses. Notably, the double-D configuration reduces enclosure losses from 269.6 W, observed in a rectangular coil design, to 4.38 W, resulting in an overall system loss reduction of 42.4% while maintaining the electrical parameters required for zero-voltage switching operation. These advancements address the critical limitations in conventional Medium-Frequency Transformers by providing enhanced insulation and improved thermal management. The proposed IPT-based design offers a low-loss solution with easy thermal management for solid-state transformer applications in high-voltage grids. Full article
(This article belongs to the Special Issue Advanced Control Techniques for Power Electronics: Addressing Challenges in Renewable Energy System Applications)
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