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Operation Optimization and Security Analysis of Energy Cyber Physical Systems

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

Deadline for manuscript submissions: 15 July 2025 | Viewed by 8988

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
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
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 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 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 for the thorough investigation of the 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 modelling, analysis, optimization, control and demonstration.

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

  • Interaction mechanisms and models of ECPSs;
  • Operation optimization of ECPSs;
  • Coordination control of ECPSs;
  • Situational awareness for ECPSs;
  • Reliability, risk, vulnerability and resilience assessments for ECPSs;
  • Cyber security analysis of ECPSs;
  • Attack detection and defence of ECPSs;
  • Early warning, fault diagnosis and service restoration of ECPSs;
  • Market transaction and supervision of ECPSs;
  • Application of artificial intelligence and big data in ECPSs;
  • Application of cloud computing and secure multiparty computation in ECPSs;
  • Verification and demonstration of 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 100 words) can be sent to the Editorial Office for announcement on this website.

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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Published Papers (5 papers)

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Research

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41 pages, 9332 KiB  
Article
An Innovative Real-Time Recursive Framework for Techno-Economical Self-Healing in Large Power Microgrids Against Cyber–Physical Attacks Using Large Change Sensitivity Analysis
by Mehdi Zareian Jahromi, Elnaz Yaghoubi, Elaheh Yaghoubi, Mohammad Reza Maghami and Harold R. Chamorro
Energies 2025, 18(1), 190; https://doi.org/10.3390/en18010190 - 4 Jan 2025
Cited by 1 | Viewed by 1322
Abstract
In the past, providing an online and real-time response to cyber–physical attacks in large-scale power microgrids was considered a fundamental challenge by operators and managers of power distribution networks. To address this issue, an innovative framework is proposed in this paper, enabling real-time [...] Read more.
In the past, providing an online and real-time response to cyber–physical attacks in large-scale power microgrids was considered a fundamental challenge by operators and managers of power distribution networks. To address this issue, an innovative framework is proposed in this paper, enabling real-time responsiveness to cyberattacks while focusing on the techno-economic energy management of large-scale power microgrids. This framework leverages the large change sensitivity (LCS) method to receive immediate updates to the system’s optimal state under disturbances, eliminating the need for the full recalculation of power flow equations. This significantly reduces computational complexity and enhances real-time adaptability compared to traditional approaches. Additionally, this framework optimizes operational points, including resource generation and network reconfiguration, by simultaneously considering technical, economic, and reliability parameters—a comprehensive integration often overlooked in recent studies. Performance evaluation on large-scale systems, such as IEEE 33-bus, 69-bus, and 118-bus networks, demonstrates that the proposed method achieves optimization in less than 2 s, ensuring superior computational efficiency, scalability, and resilience. The results highlight significant improvements over state-of-the-art methods, establishing the proposed framework as a robust solution for real-time, cost-effective, and resilient energy management in large-scale power microgrids under cyber–physical disturbances. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems)
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19 pages, 6588 KiB  
Article
Virtual Power Plant Reactive Power Voltage Support Strategy Based on Deep Reinforcement Learning
by Qihe Lou, Yanbin Li, Xi Chen, Dengzheng Wang, Yuntao Ju and Liu Han
Energies 2024, 17(24), 6268; https://doi.org/10.3390/en17246268 - 12 Dec 2024
Viewed by 694
Abstract
After the large-scale access of distributed power sources to the distribution network, significant high/low voltage problems have emerged. Using a virtual power plant to provide reactive power voltage regulation as an ancillary service effectively addresses voltage issues. However, since a third party manages [...] Read more.
After the large-scale access of distributed power sources to the distribution network, significant high/low voltage problems have emerged. Using a virtual power plant to provide reactive power voltage regulation as an ancillary service effectively addresses voltage issues. However, since a third party manages the virtual power plant and contains both discrete and continuous regulation devices internally, there is a need to consider privacy protection. To address this, a training method that requires minimal boundary information and reward–penalty information for interaction between discrete and continuous action agents is proposed. This method uses distributed two-layer multi-agent deep reinforcement learning for the virtual power plant’s reactive power voltage support strategy. By utilizing actual engineering data and comparing it with the “centralized training” framework algorithm, this study proves the effectiveness of the deep reinforcement learning training method and reactive power voltage control strategy. It demonstrates advantages such as protecting the privacy of the virtual power plant and low training difficulty. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems)
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13 pages, 3477 KiB  
Article
Temperature Regulation Strategy of Heterogeneous Air Conditioning Loads for Renewable Energy Consumption
by Shu Zhang, Liping Zhou, Dejin Fan and Jie Tang
Energies 2023, 16(12), 4705; https://doi.org/10.3390/en16124705 - 14 Jun 2023
Cited by 3 | Viewed by 1467
Abstract
In a power system with a high proportion of renewable energy, sudden increases in wind power or photovoltaic output can lead to huge challenges, such as difficulties in accommodating excess renewable energy and imbalances between supply and demand on the grid. As an [...] Read more.
In a power system with a high proportion of renewable energy, sudden increases in wind power or photovoltaic output can lead to huge challenges, such as difficulties in accommodating excess renewable energy and imbalances between supply and demand on the grid. As an important adjustable resource on the demand side, air conditioning load is a flexible load for realizing output consumption. In this paper, a heterogeneous air conditioning load regulation strategy for renewable energy consumption is proposed. Each air conditioning load regulation quantity is obtained based on the day-ahead dispatching mode. Then, the temperature setting value, rated power, and duty cycle are selected as the indexes. The load regulation sequence is obtained by the entropy weight method. Finally, the load regulation time of each air conditioning load is obtained based on the constraint of the quantity of loads during the possible adjustment time. The simulation analysis shows that the temperature regulation strategy presented in this paper can effectively reduce the power fluctuations of air conditioning loads, while ensuring that users with lower temperature settings are selected in the adjustment process. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems)
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14 pages, 5609 KiB  
Article
An Improved Q-Axis Current Control to Mitigate the Low-Frequency Oscillation in a Single-Phase Grid-Connected Converter System
by Kai Wei, Changjun Zhao and Yi Zhou
Energies 2023, 16(9), 3816; https://doi.org/10.3390/en16093816 - 28 Apr 2023
Cited by 2 | Viewed by 1489
Abstract
An electric railway system is a typical single-phase grid-connected converter system, and the low-frequency oscillation (LFO) phenomenon in electric railway systems has been widely reported around the world. Previous research has indicated that the LFO is a small-signal instability issue caused by impedance [...] Read more.
An electric railway system is a typical single-phase grid-connected converter system, and the low-frequency oscillation (LFO) phenomenon in electric railway systems has been widely reported around the world. Previous research has indicated that the LFO is a small-signal instability issue caused by impedance mismatching between the traction network system and electric trains. Therefore, this paper proposes an improved q-axis current control method to reshape the train’s impedance. The proposed method can be implemented easily by relating a reverse q-axis reactive current directly to the reference of the q-axis current under the dq current decoupled control. Moreover, considering the additional q-axis reactive current control, a small-signal impedance model of a train–network system is built. The impedance-based analysis results indicate that the proposed q-axis reactive current feedback control can increase the magnitude of the train’s impedance, which is beneficial to enhancing the system’s stability. Finally, this paper employs experimental results to verify the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems)
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Review

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38 pages, 5448 KiB  
Review
Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory
by Tianlei Zang, Zian Wang, Xiaoguang Wei, Yi Zhou, Jiale Wu and Buxiang Zhou
Energies 2023, 16(18), 6509; https://doi.org/10.3390/en16186509 - 9 Sep 2023
Cited by 6 | Viewed by 2602
Abstract
The increasing factors of uncertainty faced by the system are due to the deep coupling of the electric power cyber network and the physical network. Consequently, ensuring the efficient, secure, and stable operation of the cyber–physical power system (CPPS) has become a key [...] Read more.
The increasing factors of uncertainty faced by the system are due to the deep coupling of the electric power cyber network and the physical network. Consequently, ensuring the efficient, secure, and stable operation of the cyber–physical power system (CPPS) has become a key concern. To achieve this, vulnerability assessment plays a crucial role, as it identifies and protects the vulnerable points of the system. The application of complex network theory to assess the vulnerability of CPPSs has garnered significant attention from scholars. This paper delves into the research connotation of vulnerability assessment for CPPSs, starting with the origin, definition, and classification of vulnerability. Subsequently, the assessment framework of vulnerability based on complex network theory is presented, and the status of current domestic and international research in this field is summarized. Furthermore, the interrelationship between system vulnerability and cascading failures is analyzed from the perspective of complex network theory. In conclusion, the ideas of CPPS coupling modeling in vulnerability assessment are summarized, the concept of situation awareness is introduced, and a prospective approach for dynamic vulnerability assessment is proposed. This approach is based on situation awareness combined with complex network theory. Security protection and optimal operation of CPPSs based on vulnerability assessment are also discussed, along with the assessment of vulnerability within integrated energy cyber–physical systems (IECPSs). Full article
(This article belongs to the Special Issue Operation Optimization and Security Analysis of Energy Cyber Physical Systems)
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