Smart Grid Technologies and Energy Conversion Systems

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

Deadline for manuscript submissions: 15 August 2025 | Viewed by 481

Special Issue Editors

Key Laboratory of Photovoltaic Technology of Guangdong Province, School of Physics, Sun Yat-sen University, Guangzhou 510275, China
Interests: microgrid/power electronics and control technology; photovoltaic system application technology; electric vehicle charging technology; energy storage system

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Guest Editor
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Interests: renewable energy generation and its power quality control technology; power electronics; distributed power systems

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Guest Editor
School of Marine Engineering and Technology, Sun Yat-sen University, Zhuhai 519000, China
Interests: new energy power conversion; advanced power electronic systems; stability and control of power systems; wireless power transfer

Special Issue Information

Dear Colleagues,

With the rapid development of the global economy and the growing demand for energy, traditional fossil fuels are becoming progressively depleted. Moreover, the energy crisis is gradually emerging. At the same time, the extensive use of fossil fuels has led to serious environmental pollution and climate change issues, posing a threat to the human living environment. As the power grid structure becomes more and more complex, the development of high dynamic new energy is rapidly advancing, with energy storage systems also rapidly developing. In addition, users' requirements for power supply reliability and power quality are continuously rising. Traditional power grids are no longer able to meet these needs. The electric smart grid relies on the increasingly developed artificial intelligence and intelligent control technology, advanced sensing technology, communication technology, computing technology, and decision support systems to provide strong support for the establishment and development of new power systems. The conversion of electrical energy into various forms of energy, achieving efficient, stable, and intelligent changes, is an important part of realizing the efficient utilization of new energy and the efficient and stable operation of the power grid. Smart grids and energy transformations are not only important measures to address energy crisis and environmental pressure but are also effective ways to improve the efficiency and reliability of power grid operation; promote the development and utilization of clean energy; enhance energy utilization efficiency and energy conservation; reduce emissions; promote sustainable economic and social development; and enhance user electricity experience and satisfaction. Topics of interest include the following:

  • New energy utilization technology;
  • New energy conversion and control;
  • Power electronic converter and its control;
  • Intelligent control technology for power grid load;
  • Power quality;
  • Electricity safety;
  • Application of AI in power system;
  • Electric vehicle charging and interaction with the power grid;
  • Intelligent sensing technology.

Dr. Qing Fu
Dr. Ling Yang
Dr. Fan Feng
Guest Editors

Manuscript Submission Information

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Keywords

  • new energy utilization technology
  • new energy conversion and control
  • power electronic converter and its control
  • intelligent control technology for power grid load
  • power quality
  • electricity safety
  • application of AI in power system
  • electric vehicle charging and interaction with the power grid
  • intelligent sensing technology

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Published Papers (1 paper)

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Research

24 pages, 11440 KiB  
Article
Research on Estimation Optimization of State of Charge of Lithium-Ion Batteries Based on Kalman Filter Algorithm
by Tian Xia, Xiangyang Xia, Jiahui Yue, Yu Gong, Jianguo Tan and Lixing Wen
Electronics 2025, 14(7), 1462; https://doi.org/10.3390/electronics14071462 - 4 Apr 2025
Viewed by 254
Abstract
Accurate prediction of the State of Charge (SOC) of lithium-ion batteries is the foundation for the stable and efficient operation of battery management systems. This paper proposes a lithium-ion battery SOC estimation method based on the Dung Beetle Optimizer (DBO), optimizing the second-order [...] Read more.
Accurate prediction of the State of Charge (SOC) of lithium-ion batteries is the foundation for the stable and efficient operation of battery management systems. This paper proposes a lithium-ion battery SOC estimation method based on the Dung Beetle Optimizer (DBO), optimizing the second-order Kalman filter algorithm (DBO-DKF). Leveraging the DBO’s fast convergence speed and strong global search capability, this method optimizes the Kalman filter algorithm in the parameter identification stage and the extended Kalman filter algorithm in the SOC estimation stage to address the issue of insufficient estimation accuracy caused by noise covariance matrices of input current and voltage measurements. Through the discharge of current tests under complex conditions, as well as comparing and analyzing credibility indicators such as MAE, RMSE, and MSE as measures of estimation accuracy, it can be verified that the proposed method effectively enhances SOC estimation accuracy. Full article
(This article belongs to the Special Issue Smart Grid Technologies and Energy Conversion Systems)
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