Smart Converters/Inverters for Microgrid Applications

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

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 1403

Special Issue Editors


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Guest Editor
Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, 999077 Hong Kong, China
Interests: modeling and control of power electronic converters; HVDC; energy router; photovoltaic and battery energy storage systems; electrolytic hydrogen production
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Electrical Engineering, Sichuan University, Chengdu 610000, China
Interests: grid supporting inverter for microgrid; coordinative control for parallel inverters; high power rectifier for electrolytic hydrogen production
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China
Interests: advanced control; stability analysis; energy management techniques for renewable energy systems

Special Issue Information

Dear Colleagues,

A microgrid is a small-scale, autonomous power system composed of distributed energy resources, energy storage devices, loads, and an intelligent control and management system. Compared to the traditional centralized power grid, microgrids offer greater flexibility and adaptability, and can highly integrate renewable energy sources to enhance energy utilization efficiency and system reliability. Smart power converters are crucial components within a microgrid. They enable bidirectional power regulation and energy conversion, serving as key interfaces that connect distributed energy sources, loads, and energy storage systems.

As the core device of the microgrid, the technological development of smart power converters faces several significant challenges. Firstly, there is a need to improve power conversion efficiency and power density. This requires the adoption of new semiconductor devices, innovative topologies, and advanced cooling technologies. Secondly, it is essential to develop more intelligent and robust control algorithms. These algorithms must not only precisely regulate electrical parameters but also adapt to complex loads and distributed energy sources to enhance system stability and reliability. Furthermore, smart power converters should incorporate functions such as optimized energy management and coordinated control to fully leverage their coordinating role within the microgrid. Overcoming these technical challenges will drive continuous improvements in smart power converter performance and provide crucial support for realizing clean energy-powered, reliable, and high-performance microgrid operations.

This Special Issue is dedicated to collecting and sharing the latest research and the newest ideas on smart converters/ inverters for microgrid applications. Research areas include (but are not limited to) the following:

  • Novel smart converter topologies;
  • AI-enabled smart converters;
  • Wide bandgap power device-based smart converters;
  • Smart converters for Power-to-X systems;
  • Multi-port smart converters/inverters;
  • Digital twin technology for smart converters;
  • Grid-forming control strategies;
  • Small signal and transient stability analysis of a microgrid.

We look forward to receiving your contributions.

Dr. Xingxing Chen
Dr. Xin Meng
Dr. Qingchao Song
Guest Editors

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Keywords

  • microgrid
  • smart converters
  • topologies
  • artificial intelligence
  • wide bandgap power devices
  • digital twin
  • stability
  • grid forming

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Published Papers (2 papers)

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Research

17 pages, 4090 KiB  
Article
Grid Current Distortion Suppression Based on Harmonic Voltage Feedforward for Grid-Forming Inverters
by Baojin Liu, Bing Yu and Feng Zheng
Electronics 2025, 14(5), 839; https://doi.org/10.3390/electronics14050839 - 20 Feb 2025
Viewed by 479
Abstract
A grid-forming converter (GFM) controls power output by adjusting the phase angle and amplitude of its output voltage, providing voltage and frequency support to the power system and effectively enhancing system stability. However, it has limitations in current control, influencing the current only [...] Read more.
A grid-forming converter (GFM) controls power output by adjusting the phase angle and amplitude of its output voltage, providing voltage and frequency support to the power system and effectively enhancing system stability. However, it has limitations in current control, influencing the current only indirectly through voltage regulation, which results in weaker control over current waveform quality. In the context of a large number of renewable energy generation units being connected to the grid, harmonics in the grid voltage can lead to excessively high harmonic content in the grid current, exceeding standard limits and causing oscillations. To solve this problem, this paper proposes a control strategy of harmonic voltage feedforward compensation to suppress grid current distortion. The proposed control strategy extracts harmonic voltages from the output port of the GFM converter through a harmonic extraction module, processes them via a feedforward factor, and introduces the resulting signals into the converter’s control loop as feedforward compensation terms. This allows the converter’s output voltage to compensate for the harmonic components in the grid, achieving the improvement of grid current and reducing the total harmonic distortion (THD) value. The effectiveness of the proposed control strategy is verified by simulation results. Full article
(This article belongs to the Special Issue Smart Converters/Inverters for Microgrid Applications)
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20 pages, 4233 KiB  
Article
Smart Tuning of Control System Parameters for a Grid Connected Converter: A Robust Artificial Neural Network Approach
by Sharara Rehimi, Hassan Bevrani, Chiyori T. Urabe, Takeyoshi Kato and Toshiji Kato
Electronics 2025, 14(4), 699; https://doi.org/10.3390/electronics14040699 - 11 Feb 2025
Viewed by 608
Abstract
The reliable and effective operation of modern power grids is highly dependent on accurately adjusting the control system parameters of power converters. Traditional approaches to parameter tuning often depend on analytical models and offline optimization, which may not fully describe the intricate dynamics [...] Read more.
The reliable and effective operation of modern power grids is highly dependent on accurately adjusting the control system parameters of power converters. Traditional approaches to parameter tuning often depend on analytical models and offline optimization, which may not fully describe the intricate dynamics and nonlinearities seen in real-world modern power grids. This paper presents an innovative method for intelligently adjusting the control system settings of converters in a modern power grid. The proposed approach utilizes machine learning methods, particularly robust artificial neural networks, to tune the converter control parameters and improve the overall modern power grid performance. This intelligent tuning system can obtain ideal parameters for stable, economical, and resilient modern power grid operation under different operating circumstances and disturbances by training the neural network models robustly using detailed simulation data and real-time measurements. This study provides a comprehensive description of the intricate structure of the intelligent tuning framework, including the neural network models and the robust methods. The proposed approach’s usefulness in enhancing the modern power grid frequency control, active power regulation, and transient response is validated via comprehensive case studies in comparison to existing parameter tuning approaches. The performed simulation and laboratory real-time experiments indicate that the smart tuning system is adaptable and resilient, making it a potential alternative for improving the stability and performance of modern power grids. Full article
(This article belongs to the Special Issue Smart Converters/Inverters for Microgrid Applications)
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