Real-Time Monitoring and Intelligent Control for a Microgrid

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

Deadline for manuscript submissions: 15 June 2025 | Viewed by 493

Special Issue Editors


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Guest Editor
Division of Electric Power and Energy Systems, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Interests: control and stability analysis of power electronic converters; microgrid control and DER integration; HVDC and FACTS; motor design and drives

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Guest Editor
School of Electrical Engineering, Chongqing University, Chongqing 40044, China
Interests: machine learning and big data applications in power systems; power system protection; smart cities; microgrid; EV integration; real-time simulation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Automation, Nanjing University of Science and Technology, Nanjing 210000, China
Interests: learning for optimization; power system economics; power system operation and control

Special Issue Information

Dear Colleagues,

The global transition toward sustainable energy systems and a deregulated electricity market has accelerated the adoption of microgrids as essential components of smart power infrastructure. These localized, autonomous energy networks integrate distributed energy resources (DERs), storage systems, and intelligent controls to enhance grid resilience and reliability, reduce carbon emissions, and optimize energy distribution. Their ability to operate independently or through grid connection and aggregate and manage the multitudes of DERs makes them crucial for modern power systems.

According to IEEE Std 2030.7, the microgrid controller, with dispatch and transition as its two core functions, is the heart and soul of the microgrid system by serving as the central intelligence unit that orchestrates all operations, making critical decisions to maintain stability, efficiency, and reliability. Microgrid dispatch or energy management functions orchestrate power flow between distributed energy resources, optimizing generation, storage, and load balance in both grid-connected and islanded modes. The transition function enables seamless switching between operational states while maintaining power quality and system stability through intelligent real-time control algorithms. With smart metering, real-time monitoring and advanced control techniques, intelligent microgrid controllers can adaptively adjust the operating modes according to the objectives defined, the constraints of DERs, and the specific application of the microgrid.

This Special Issue invites original contributions and review papers on emerging trends and innovations in real-time monitoring and control of microgrids. Topics of interest may include, but are not limited to, the following:

  • Device-level voltage and frequency control.
  • System-level optimal and rule-based dispatch.
  • Seamless transition between grid-connected and islanded modes.
  • Operation, planning, and design of microgrid system.
  • Distributed energy resource management systems (DERMSs) and virtual power plants (VPPs).
  • Artificial intelligence and machine learning for microgrid applications.
  • Smart metering, communication, and cybersecurity for microgrids.
  • Real-time simulation and hardware-in-the-loop testing for microgrids.
  • Case studies and real-world implementations of microgrid controllers.

We look forward to receiving your contributions.

Dr. Chu Sun
Dr. Qiushi Cui
Dr. Yuchong Huo
Guest Editors

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Keywords

  • smart grid
  • microgrid controller
  • energy management
  • seamless transition
  • DER management
  • intelligent control

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Published Papers (2 papers)

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Research

18 pages, 549 KiB  
Article
Adaptive Real-Time Convergence Estimation for Enhancing Reliability of Time Synchronization in Distributed Energy Monitoring System
by Fanrong Shi, Jiacheng Yang, Lili Ran and Wei Wang
Electronics 2025, 14(9), 1836; https://doi.org/10.3390/electronics14091836 - 30 Apr 2025
Abstract
In distributed energy monitoring systems, precise time synchronization is paramount for efficient data acquisition and energy management. With the high penetration of new energy sources, the distributed energy monitoring system will evolve into a complex heterogeneous network utilizing various short-range wireless communication technologies. [...] Read more.
In distributed energy monitoring systems, precise time synchronization is paramount for efficient data acquisition and energy management. With the high penetration of new energy sources, the distributed energy monitoring system will evolve into a complex heterogeneous network utilizing various short-range wireless communication technologies. Therefore, wireless communication-based time synchronization technologies will be widely applied, and it is important for the distributed energy monitoring system to be aware of the current time synchronization errors as this is crucial for accurate data processing. Our findings propose the first real-time convergence estimation method using an adaptive real-time convergence estimation (ARCE) algorithm, which can accurately estimate the current network time synchronization error and convergence status in real time. This ARCE algorithm is based on synchronization error and distribution of both synchronous and asynchronous time synchronization algorithm. The actual distributions of synchronization error are analyzed and evaluated using a significant amount of experimental results. According to the experimental results and simulations, ARCE can effectively detect the convergence state for all the comparisons. Therefore, ARCE can be used to evaluate the reliability of timestamps in data acquisition. Moreover, it can be utilized to enhance the adaptive capability of time synchronization algorithms, which could be robust and scalable for a large-scale and randomly deployed wireless networks. Full article
(This article belongs to the Special Issue Real-Time Monitoring and Intelligent Control for a Microgrid)
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20 pages, 5457 KiB  
Article
A Mathematical Method of Current-Carrying Capacity for Shore Power Cables in Port Microgrids
by Fei You, Mohd Abdul Talib Mat Yusoh, Nik Hakimi Nik Ali and Hao Yang
Electronics 2025, 14(9), 1749; https://doi.org/10.3390/electronics14091749 - 25 Apr 2025
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Abstract
It is difficult to consider factors such as wind speed, water flow velocity, and solar radiation when using the IEC 60287 standard to calculate the current-carrying capacity of shore power cables in port microgrids. Therefore, based on the equivalent thermal circuit model and [...] Read more.
It is difficult to consider factors such as wind speed, water flow velocity, and solar radiation when using the IEC 60287 standard to calculate the current-carrying capacity of shore power cables in port microgrids. Therefore, based on the equivalent thermal circuit model and heat balance equation, this research takes solar radiation as the heat source of the cable used in port microgrids and proposes a mathematical calculation method for the current-carrying capacity of shore power cables based on the Newton–Raphson method. The influence of wind and water speed, environmental temperature, and solar radiation on current-carrying capacity is compared and analyzed using this mathematical calculation method and simulation calculation method. Shore power cables exhibit higher ampacity in water than air due to water’s superior thermal conductivity. Maximum ampacity difference occurs at 0.17 m/s flow (26.8 A analytically) and 0.066 m/s flow (64.4 A simulation). Air-laid cables show amplified ambient temperature effects from solar radiation, while water-laid cables demonstrate near-linear ampacity variations (Δ40 °C: 0–40 °C temperature range). This research can provide a reference for the revision of the standard for calculating the current-carrying capacity of shore power cables and optimizing renewable-energy-integrated port power systems. Full article
(This article belongs to the Special Issue Real-Time Monitoring and Intelligent Control for a Microgrid)
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