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Operation Optimization and Security Analysis of Energy Cyber Physical Systems—2nd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: 30 August 2026 | Viewed by 2252

Special Issue Editors

Dr. Tianlei Zang

E-Mail Website
Guest Editor
College of Electrical Engineering, Sichuan University, Wangjiang Campus, Chengdu 610065, China
Interests: energy cyber physical systems; operation optimization and security analysis of integrated energy systems
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaoguang Wei

E-Mail Website
Guest Editor
School of Electrical Engineering, Southwest Jiaotong University, Xipu Campus, Chengdu 611756, China
Interests: energy cyber physical systems; power market and energy system security
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Buxiang Zhou

E-Mail Website
Guest Editor
College of Electrical Engineering, Sichuan University, Wangjiang Campus, Chengdu 610065, China
Interests: dispatch, operation, control of power systems; energy cyber physical systems and information processing technology of Integrated energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to their rapid integration with advanced sensing, monitoring, communication and control technologies, energy systems have now emerged as typical cyber-physical systems (CPSs). Intricate spatial–temporal interactions between multiple energy resources and domains have brought an unprecedented flexibility to energy systems, while also making them more vulnerable to cyber-related threats. Currently, traditional analysis, optimization or control methods mainly focus on physical energy systems and neglect the complex interdependencies between cyber and physical domains. Therefore, novel operational optimization and security analysis approaches regarding energy cyber-physical systems (ECPSs) are highly desired in order to conduct the thorough investigation of complex interactions found between cyber and physical domains, the reduction in newly introduced risks, and improvement in the efficiency of ECPSs. This Special Issue is devoted to reflecting on the latest progress and key technologies concerning ECPSs, focusing on their modeling, analysis, optimization, control, and demonstration.

Topics of interest for publication in this Special Issue include, but are not limited to, the following:

  • Digital twin-driven modeling and real-time simulation for ECPSs;
  • Federated learning for privacy-preserving data analytics in ECPSs;
  • Integration and cybersecurity of distributed energy resources and inverter-based resources;
  • Socio-technical-economic impact assessment of cyber-attacks on energy infrastructure;
  • Dynamic state estimation and anomaly detection for ECPSs;
  • Propagation mechanism and mitigation of cyber-physical cross-domain cascading failures in ECPSs;
  • Intelligent attack detection and dynamic risk assessment for ECPSs;
  • Active defense and moving target defense mechanisms for ECPSs;
  • Resilience assessment and enhancement strategies for ECPSs;
  • Robustness and survivability of ECPSs against extreme events;
  • Cyber-physical coordinated restoration and self-healing for ECPSs;
  • Distributed and decentralized control strategies for ECPSs;
  • Integration and security of 5G/6G communication technologies in ECPSs;
  • Edge intelligence and computing for decentralized ECPS management;
  • Explainable artificial intelligence and quantum computing for ECPSs;
  • Secure cross-domain cooperative market mechanism for ECPSs;
  • Cooperative control of human-in-the-loop ECPSs;
  • Human factor security and human error mitigation in ECPSs.

Dr. Tianlei Zang
Dr. Xiaoguang Wei
Prof. Dr. Buxiang Zhou
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. 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

  • electrical power systems
  • integrated energy systems
  • cyber-physical systems
  • operation optimization
  • coordination control
  • security analysis

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Related Special Issue

Published Papers (3 papers)

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Research

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20 pages, 13714 KB  
Article
Dynamic Anomaly Detection: A Multimodal Spatiotemporal Cross-Fusion Transformer Approach
by Zefu Deng and Dongliang Xu
Energies 2026, 19(11), 2605; https://doi.org/10.3390/en19112605 - 28 May 2026
Viewed by 158
Abstract
Accurate fault diagnosis is critical for the reliable and secure operation of modern industrial equipment; however, traditional unimodal data representations often fail to fully capture the complex, multi-dimensional characteristics of mechanical faults. To address this limitation, this paper proposes CFNET, a novel multimodal [...] Read more.
Accurate fault diagnosis is critical for the reliable and secure operation of modern industrial equipment; however, traditional unimodal data representations often fail to fully capture the complex, multi-dimensional characteristics of mechanical faults. To address this limitation, this paper proposes CFNET, a novel multimodal cross-fusion recognition framework designed for the robust fault diagnosis of rotating machinery, including vane pumps and bearings. The proposed framework employs an innovative three-modal input strategy that systematically extracts deep spatial and temporal features using parallel ResNet50 and stacked GRU networks. To break through the limitations of conventional decision-level fusion, CFNET introduces a dynamic mid-layer cross-fusion mechanism driven by adaptive attention weights, effectively enhancing feature interaction depth while preventing redundancy during back-propagation. Furthermore, handcrafted prior features are integrated via skip connections to supplement the deep learning representations. The aggregated multi-dimensional features are ultimately processed by a Transformer architecture for feature sparsification and high-precision classification. Extensive experiments rigorously validate the superiority of the proposed method. On a custom-built industrial vane pump test rig, CFNET achieved a maximum accuracy improvement of 25% over traditional unimodal methods. Furthermore, it demonstrated state-of-the-art performance on two authoritative benchmark datasets, achieving impressive recognition accuracies of 98.12% and 99.92% on the Paderborn University and Case Western Reserve University bearing datasets, respectively. These results underscore the exceptional robustness, efficiency, and industrial applicability of the CFNET framework. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems—2nd Edition)
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17 pages, 1728 KB  
Article
Multi-Criteria-Based Key Transmission Section Identification and Prevention–Emergency Coordinated Optimal Control Strategy
by Xinyu Peng, Chuan He, Honghao Zhang, Lu Nan, Tianqi Liu, Jian Gao, Biao Wang, Xi Ye and Xinwei Sun
Energies 2025, 18(22), 5871; https://doi.org/10.3390/en18225871 - 7 Nov 2025
Viewed by 631
Abstract
Large-scale blackouts in power systems are often triggered by weak links susceptible to cascading failures. As the concentrated reflection of the system’s weak links, identifying key transmission sections and further implementing safety control measures are of great significance for ensuring the stable operation [...] Read more.
Large-scale blackouts in power systems are often triggered by weak links susceptible to cascading failures. As the concentrated reflection of the system’s weak links, identifying key transmission sections and further implementing safety control measures are of great significance for ensuring the stable operation of the system. This paper proposes a multi-criteria-based method for identifying key transmission sections and an optimal strategy for the prevention–emergency coordinated control of key transmission sections. Firstly, a line criticality index based on three characteristics—topology, power flow, and voltage—has been established to identify critical lines. Furthermore, search for all initial transmission sections that include the critical line, and form the initial transmission section set for each critical line, then, based on the analysis of the Theil index of power flow impact rate distribution after the failure of critical lines, a key transmission section identification method integrating multiple criteria is proposed. Then, based on the anticipated faults of key transmission sections, an optimization model for the prevention–emergency coordinated control of key transmission sections is established. A constraint relaxation factor is introduced to divide the above model into two independent sub-problems, then the golden section method is applied to update the value of constraint relaxation factors, so as to iteratively search for the optimal solution of the model. Finally, the feasibility and correctness of the proposed method are verified through the simulation and analysis of the IEEE 39-bus system. The results demonstrate that the proposed method can effectively identify the key transmission sections of the system and improve the operational safety of the system through the prevention–emergency coordinated optimal control strategy. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems—2nd Edition)
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Review

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66 pages, 7571 KB  
Review
Key Technologies and Research Prospects for Defense Strategies Against Cyberattacks in Electricity Markets
by Tianlei Zang, Lan Yu, Rundong Liao, Kewei He, Libo Ran and Siting Li
Energies 2025, 18(24), 6589; https://doi.org/10.3390/en18246589 - 17 Dec 2025
Viewed by 833
Abstract
The deep integration of digital technologies has significantly improved the operational efficiency of electricity markets, but it has also introduced increasingly severe and sophisticated cybersecurity challenges. As a highly coupled cyber–physical system (CPS), the electricity market is increasingly vulnerable to attacks that exploit [...] Read more.
The deep integration of digital technologies has significantly improved the operational efficiency of electricity markets, but it has also introduced increasingly severe and sophisticated cybersecurity challenges. As a highly coupled cyber–physical system (CPS), the electricity market is increasingly vulnerable to attacks that exploit weaknesses in both market mechanisms and information infrastructure. Unlike existing reviews, this study makes three key contributions: First, it provides a hierarchical analysis of cyberattacks targeting electricity market operations, detailing how such attacks manipulate outcomes for profit or disruption. Second, it proposes a novel full-lifecycle dynamic defense framework tailored to the cyber–physical–market nature of the electricity market, coordinating defenses across the entire attack lifecycle to ensure market stability and financial integrity. Third, it analyzes key enabling technologies for attack–defense games and identifies fundamental challenges to market resilience. Looking ahead, the manuscript outlines a strategic research agenda, emphasizing breakthroughs in intelligent and collaborative technologies. These advancements are expected to drive the evolution of the electricity market’s defense from a passive–reactive model to a state of active immunity, which can anticipate, withstand, and autonomously recover from complex cyber threats. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems—2nd Edition)
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