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Energies
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Advances and Optimization of Electric Energy Systems—3rd Edition
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Advances and Optimization of Electric Energy Systems—3rd Edition

A Special Issue of Energies (ISSN 1996-1073) belonging to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 25 January 2027 | Viewed by 1730

Editors

Dr. Yuqing Bao

E-Mail Website
Guest Editor
NARI School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Interests: energy management of the electric power system; demand side management of the electric power system
Special Issues, Collections and Topics in MDPI journals
Dr. Zhenya Ji

E-Mail Website
Guest Editor
NARI School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Interests: vehicle-to-grid (V2G); coordinated operations of integrated energy systems; electricity market
Special Issues, Collections and Topics in MDPI journals
Dr. Zhenyu Lv

E-Mail Website
Guest Editor
NARI School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Interests: microgrid control; DC distribution network; application of energy storage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rise in renewable energy, electric energy systems are evolving. Distributed power sources, electric vehicles, distributed energy storage, and flexible loads are gaining importance, increasingly affecting electric energy systems via source–load interactions, and making them more complex. The optimization of a power system not only requires consideration of the operating characteristics of energy resources; we also need to take into account the uncertainty of distributed power sources, the travel rules of electric vehicles, the comfort level of electric energy users, etc. Therefore, it is necessary to fully investigate the advances in electric energy systems and design more feasible, efficient, and robust optimization strategies.

Thus, topics relevant to this Special Issue of Energies, entitled ‘Advances and Optimization of Electric Energy Systems—3rd Edition’, include (but are not limited to) the following:

  • modeling and optimization of electric energy systems;
  • modeling and management of flexible loads;
  • scheduling of high renewable penetrated electric power systems;
  • load forecasting of electric energy systems;
  • electricity market design for source–load interactions;
  • coordinated operations of integrated energy systems;
  • vehicle-to-grid (V2G) optimization and control technologies;
  • optimization and control of energy storage systems;
  • review of advances in electric energy systems.

Dr. Yuqing Bao
Dr. Zhenya Ji
Dr. Zhenyu Lv
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-anonymized 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

  • energy management
  • demand response
  • vehicle-to-grid (V2G)
  • integrated energy systems

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Related Special Issue

Published Papers (2 papers)

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Research

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20 pages, 10706 KB  
Article
A Dynamic Harmonic Coupling Matrix Modeling Approach for Power Quality Analysis in Electric Vehicle Charging Stations with Bidirectional Capability
by Xueliang Huang, Fei Zeng, Linlin Tan, Huiyu Miao, Jijian Wu and Hanyi Yao
Energies 2026, 19(11), 2670; https://doi.org/10.3390/en19112670 - 1 Jun 2026
Viewed by 462
Abstract
The proliferation of large-scale electric vehicle charging stations has made power quality issues increasingly prominent. While conventional unidirectional charging stations already present complex harmonic interactions, the development of vehicle-to-grid technology has introduced more complex harmonic coupling in bidirectional charging stations. To improve the [...] Read more.
The proliferation of large-scale electric vehicle charging stations has made power quality issues increasingly prominent. While conventional unidirectional charging stations already present complex harmonic interactions, the development of vehicle-to-grid technology has introduced more complex harmonic coupling in bidirectional charging stations. To improve the accuracy of harmonic power flow analysis, this paper proposes a hybrid mechanism–data-driven dynamic harmonic coupling matrix model (DHCMM) for power quality assessment in bidirectional charging stations. A DHCMM-based harmonic power flow calculation process is further developed to evaluate the harmonic impact on power distribution networks following station integration. The proposed method is validated using field measurement data from an actual bidirectional charging station with tests covering typical charging, discharging, and dynamic transition scenarios. Results show that the DHCMM provides accurate harmonic modeling with both the total harmonic current distortion estimation error and the voltage fluctuation estimation error within 5%. The validated model is applied to an IEEE 33-bus distribution system. A comparison of the results reveals that the power quality impact of such stations extends beyond the point of connection to neighboring nodes, while the proposed DHCMM outperforms mechanism-based models including the static harmonic coupling matrix model and the Norton harmonic equivalent model as well as data-driven models such as the backpropagation neural network and least squares support vector machines. Full article
(This article belongs to the Special Issue Advances and Optimization of Electric Energy Systems—3rd Edition)
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Review

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21 pages, 3950 KB  
Review
A Review of Open-Access Image Datasets for Power Line Inspection
by Xue-Hua Wu, Enze Zhao, Kangyao Yuan and Yu-Qing Bao
Energies 2026, 19(11), 2649; https://doi.org/10.3390/en19112649 - 30 May 2026
Viewed by 843
Abstract
Automated power line inspection plays a crucial role in maintaining grid reliability within smart cities by identifying potential defects in towers, conductors, insulators, and fittings. While modern anomaly detection relies heavily on deep neural networks (DNNs), training these models requires massive amounts of [...] Read more.
Automated power line inspection plays a crucial role in maintaining grid reliability within smart cities by identifying potential defects in towers, conductors, insulators, and fittings. While modern anomaly detection relies heavily on deep neural networks (DNNs), training these models requires massive amounts of high-quality image data. However, a significant scarcity of publicly available datasets persists because data acquisition not only demands highly specialized professional skills but also faces strict data protection regulations enforced by grid companies. To bridge this gap, this paper presents a comprehensive review of open-access image datasets dedicated to power line inspection. Based on strict inclusion criteria—specifically, unrestricted public availability and a direct focus on core power line components—19 datasets are systematically selected and analyzed. We provide a detailed taxonomy and comparative analysis of these datasets in terms of inspection targets, acquisition platforms, annotation toolkits, and labeling schemes. Furthermore, our investigation highlights current research trends and identifies critical gaps, such as the disproportionate focus on insulators and the notable scarcity of multimodal data. To address the limitations of small-scale datasets, we also discuss existing data augmentation strategies and synthetic data generation techniques. Ultimately, this review serves as a unified navigational guide, aiming to foster the development of more robust visual inspection algorithms and to inspire future high-quality dataset construction in the power domain. Full article
(This article belongs to the Special Issue Advances and Optimization of Electric Energy Systems—3rd Edition)
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