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Cybersecurity in Critical Infrastructures, especially Digital Substations, has garnered significant attention from both the industrial and academic sectors. A commonly adopted approach to support research in this area involves the use of datasets, which consist of network traffic samples gathered during the operation of an infrastructure. However, creating such datasets from real-world electrical systems presents some challenges: (i) These datasets are often generated under controlled or idealized conditions, potentially overlooking the complexities of real-world operations within a digital substation; (ii) the captured data frequently contain sensitive information, making it difficult to share openly within the research community. This paper presents the creation of a new dataset aimed at advancing cybersecurity research, specifically focused on GOOSE spoofing attacks, given the crucial role of the GOOSE protocol in managing operational and control tasks within Digital Substations. The dataset highlights the real-world impacts of these attacks, demonstrating the execution of unintended operations under different operational scenarios, including both stable conditions and situations involving system failures. The data were collected from a laboratory testbed that replicates the actual functioning of a real digital substation with two bays. The experiments provided insights into key characteristics of GOOSE protocol traffic and the vulnerability of DS infrastructure to Spoofing Attacks. [ABSTRACT FROM AUTHOR]

A substation is integral to the functioning of a power grid, enabling the efficient and safe transmission and distribution of electrical energy to meet the demands of consumers. The digital transformation of critical infrastructures, particularly in the electric power sector, such as the emergence of intelligent substations, is a double-edged sword. While it brings about efficiency improvements and consumer-centric advancements, it raises concerns about the heightened vulnerability to cyberattacks. This article proposes a new static-dynamic strategy for host security detection by implementing a system prototype and evaluating its detection accuracy. To reduce the subjectivity in manually selecting features, we combine classified protection for cybersecurity-related standards and construct the requirement generation algorithm to construct a network security detection standard library for the substation host. Based on this, we develop strategy generation algorithm to match the list of host detection projects to obtain the security detection strategy of the target host. Moreover, we output and analyze the detection logs to obtain a security detection report. The prototype is efficient and effective through practical use, and it serves as a practical tool in substation host security detection. The experiments suggest that the mechanism proposed in our study can operate at a high speed and demonstrates satisfactory performance in terms of detection. [ABSTRACT FROM AUTHOR]

This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea's Yeonggwang substation, which is connected to renewable energy sources (RESs), is introduced. Time-synchronized μPMU data are collected through the phasor data concentrator (PDC). A pre-processing program is implemented and utilized to integrate the raw data of each μPMU into a single comma-separated values (CSV) snapshot file based on the Timetag. After presenting the technique for identification and correction of event, duplicate, and spike bad data of μPMU, causal relationships are confirmed through the voltage and current fluctuations for a total of five states, such as T/L fault, tap-up, tap-down, generation, and generation shutdown. Additionally, the difference in active power between the T/L and the secondary side of the M.Tr is compared, and the fault ride through (FRT) regulations, when the fault in wind power generation (WP), etc., occurred, is analyzed. Finally, a statistical analysis, such as boxplot and kernel density, based on the instantaneous voltage fluctuation rate (IVFR) is conducted. As a result of the simulation evaluation, the proposed correction technique and precise analysis can accurately identify various phenomena in substations and reliably estimate causal relationships. [ABSTRACT FROM AUTHOR]

The idea of a decentralized electric grid has shifted from being a concept to a reality. The growing integration of distributed energy resources (DERs) has transformed the traditional centralized electric grid into a decentralized one. However, while most efforts to manage and optimize this decentralization focus on the electrical infrastructure layer, the operational and control layer, as well as the data management layer, have received less attention. Current electric grids rely on centralized control centers (CCCs) that serve as the electric grid's brain, where operators monitor, control, and manage the entire grid infrastructure. Hence, any disruption caused by a cyberattack or a natural event, disconnecting the CCC, could have numerous negative effects on grid operations, including socioeconomic impacts, equipment damage, market repercussions, and blackouts. This article introduces the idea of a fully decentralized electric grid that leverages autonomous smart substations and blockchain integration for decentralized data management and control. The aim is to propose a blockchain-enabled decentralized electric grid model and its potential impact on energy markets, sustainability, and resilience. The model presented underlines the transformative potential of decentralized autonomous grids in revolutionizing energy systems for better operability, management, and flexibility. [ABSTRACT FROM AUTHOR]

In order to improve the effect and timeliness of ground fault monitoring and improve the effect of fault early warning, a DC ground fault monitoring method for electrical equipment in 110 kV smart substations based on improved rough sets is proposed. The characteristics of the DC ground fault current are analyzed, and the equivalent model of the DC system is constructed according to the analysis results. The low-frequency signal is enhanced according to the fuzzy rough set, and the low-frequency sampled transient zero-sequence current signal is enhanced preprocessing and wavelet packet decomposition according to the signal enhancement proportional coefficient, and the fault line is selected according to the principle of maximum energy. The wavelet packet transform method is used to decompose and analyze the waveform of the leakage current generated when a single-point grounding fault occurs in a branch of the DC system, and the grounding fault location of the DC system of the substation is realized by relative entropy operation. With the help of the cloud platform, a DC ground fault monitoring platform is built, and the ground fault monitoring is completed by using this platform. The experimental results show that the method can obtain the characteristic harmonics of the ground fault, accurately monitor whether the mutation occurs, and can realize the early warning of the ground fault of the electrical equipment in a faster time, indicating that it can realize the accurate and timely monitoring of the ground fault. [ABSTRACT FROM AUTHOR]

A substation is integral to the functioning of a power grid, enabling the efficient and safe transmission and distribution of electrical energy to meet the demands of consumers. The digital transformation of critical infrastructures, particularly in the electric power sector, such as the emergence of intelligent substations, is a double-edged sword. While it brings about efficiency improvements and consumer-centric advancements, it raises concerns about the heightened vulnerability to cyberattacks. This article proposes a new static-dynamic strategy for host security detection by implementing a system prototype and evaluating its detection accuracy. To reduce the subjectivity in manually selecting features, we combine classified protection for cybersecurity-related standards and construct the requirement generation algorithm to construct a network security detection standard library for the substation host. Based on this, we develop strategy generation algorithm to match the list of host detection projects to obtain the security detection strategy of the target host. Moreover, we output and analyze the detection logs to obtain a security detection report. The prototype is efficient and effective through practical use, and it serves as a practical tool in substation host security detection. The experiments suggest that the mechanism proposed in our study can operate at a high speed and demonstrates satisfactory performance in terms of detection.

In order to meet the requirements of automatic mapping of the smart substation models, based on the application requirements of the smart substation model construction and automatic model association configuration, the automatic generation technology of smart station diagram models is studied, and the automatic correlation modeling method and wiring diagram generation technology of primary and secondary equipment models based on the automatic matching of predefined correlation models are proposed. Support the realization of the goal of effective configuration and efficient application of the secondary system model of the smart substation.

Overload service in the communication network of smart substation will cause congestion, resulting in low overload service throughput, high congestion rate and long congestion control time in the average smart substation. A congestion control method for overloaded services in smart substations with high concurrent users is proposed. According to the characteristics of overload service request of smart substation, the mathematical model of the algorithm is defined by describing the overload service request of smart substation on the basis of network topology model. Combined with the wavelength rotation strategy, the congestion rate of overloaded services in smart substations is reduced, and the throughput rate of overloaded services in smart substations is improved. Considering the factors of high concurrent users, by judging and feeding back the congestion of the overloaded services of smart substations, the congestion control of overloaded services of smart substations under high concurrent users is realized. The experimental results show that the proposed method has better effect and scalability in the congestion control of the overloaded service of the smart substation, and can effectively shorten the congestion control time of the overloaded service of the smart substation. [ABSTRACT FROM AUTHOR]

The inability to locate device faults quickly and accurately has become prominent due to the large number of communication devices and the complex structure of secondary circuit networks in smart substations. Traditional methods are less efficient when diagnosing secondary equipment faults in smart substations, and deep learning methods have poor portability, high learning sample costs, and often require retraining a model. Therefore, a secondary equipment fault diagnosis method based on a graph attention network is proposed in this paper. All fault events are automatically represented as graph-structured data based on the K-nearest neighbors (KNNs) algorithm in terms of the feature information exhibited by the corresponding detection nodes when equipment faults occur. Then, a fault diagnosis model is established based on the graph attention network. Finally, partial intervals of a 220 kV intelligent substation are taken as an example to compare the fault localization effect of different methods. The results show that the method proposed in this paper has the advantages of higher localization accuracy, lower learning cost, and better robustness than the traditional machine learning and deep learning methods. [ABSTRACT FROM AUTHOR]

Secondary system is an important link that affects the reliable operation of power system. However, the current improvement measures for accurate data acquisition and reliable operation in secondary systems are mainly concentrated at the equipment level. The solution at the equipment level not only increases the complexity of the system, but also can only optimize a single link or problem, which is difficult to improve the overall system level. In order to enhance the information accuracy, operation and maintenance precision and operation reliability of smart substation secondary system, this paper proposes bad data identification and fault diagnosis methods based on secondary system information redundancy. Firstly, according to the analysis of secondary information redundancy, this paper constructs the data information redundancy model of the smart substation secondary system. Then the data information state estimation method based on the least square method and the bad data identification method based on the information redundancy are proposed. Finally, case analysis is carried out to verify that the proposed method can effectively increase the information accuracy of smart substation, which also provides new research route and foundations for secondary system fault diagnosis. [ABSTRACT FROM AUTHOR]

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At present, the original drawing information of the substation is stored in a single way, and the degree of digital analysis is not high. In order to reduce the huge workload of manually analyzing the original drawing of the substation, a method is proposed to intelligently extract the information of the equipment and connection relationship of the substation based on the portable document format (PDF) drawing for building a physical circuit model, thus implementing the method according to the smart substation physical configuration description (SPCD) file. Firstly, the primitive information is extracted and processed from drawings. Then electrical symbol recognition is realized through string similarity matching running Karp-Rabin greedy string tiling (RKR-GST) algorithm, and substation images are classified by gradient boosting decision tree-logistic regression (GBDT-LR) hybrid algorithm based on features. Finally, the digital description from the original drawing to the physical circuit model is completed according to the SPCD file. Experiments show that the correct rate of electrical symbol matching is 93%, and the correct rate of physical circuit identification is more than 90% when there are errors in primitives.

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the intelligent substation, the failure of communication network will affect the safe and stable operation of the substation. Therefore, an intelligent substation communication network status monitoring platform based on embedded Ethernet is designed. The platform is composed of monitoring network module, message capture and analysis module, monitoring equipment module and status monitoring software module. The monitoring network module is designed based on embedded Ethernet, which is composed of soft timer, network card hardware driver, etc. In the message capture and analysis module, Libpcap is selected as the data packet capture library to implement the analysis of three kinds of messages. In the monitoring equipment module, the monitoring equipment used includes communication analyzer and communication analysis monitoring device. The support vector data description algorithm is used to monitor the status of the communication network, and the design of the status monitoring software module is completed. The test results of the test design platform show that the platform can achieve packet detection of three kinds of messages, real-time monitoring of communication network status, and monitoring of packet loss rate and link utilization rate, with good results. [ABSTRACT FROM AUTHOR]

The current information exchange interface and human-computer interaction interface of secondary equipment operation and maintenance in substation are not unified,which seriously restricts the efficient operation and maintenance of substation. In view of this situation,the research on the efficient operation and maintenance technology of secondary equipment in substation based on power system general service protocol (GSP) is carried out. Firstly,the architecture of integrated operation and maintenance of secondary equipment in substation is designed,and the information modeling method of integrated operation and maintenance of secondary equipment in substation based on substation operation and maintenance configuration language (SOMCL) is proposed. Then,the service interface and information interaction mechanism of integrated operation and maintenance of secondary equipment in substation are designed based on object-oriented technology (OOT),which achieves the goal of plug and play information interaction between operation and maintenance tools and the object to be transported. Finally,the integrated operation and maintenance tool of secondary equipment in substation is developed to realize the standardization and visualization of operation and maintenance of intelligent secondary equipment in substation,and achieves the goal of integrated and efficient operation and maintenance of secondary equipment in substation. The proposed method has been piloted in several new smart substations,which verifies the feasibility of the integrated operation and maintenance technology of secondary equipment in substation.

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of power converters as solid state transformers is an attractive solution to modernize the power network, but this solution has not been fully addressed for MV and HV substations. This paper presents a customized and simple control for the Modular Multilevel Matrix Converter (M3C), specially conceived for its operation on synchronous ports, which is the case of AC substations. The control allows bidirectional power transfer, generation/absorption of reactive power and provisions of ancillary services. The converter is compared to the back-to-back Modular Multilevel Converter (B2B-MMC) where the key performance indicators to carry out the comparison are power efficiency, number of semiconductor devices, passive components required, footprint, voltage cell balance, fault blocking capability and stress of components. The simulation results show the features, performance and attractiveness of the M3C topology in a 33/11 kV, 16 MW substation under different operating conditions, including grid faults and dynamic operation. The M3C presents similar efficiency and performance than the B2B-MMC, but it uses fewer semiconductor devices, passive components and total cell capacitor energy than the B2B-MMC, reducing cost and footprint. The experimental results show the performance of the M3C under less ideal conditions including a substation transformer saturation and power step response. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A substation is the portion of a power grid that forms a link between the cyber system and the physical system. Reliability evaluation of smart substations based on a time-varying probabilistic hybrid attack graph (TVPHAG) is studied in this paper. First, the topology network of the smart substation is established, whose attributes are represented by probability. Then, in order to solve the problem of asynchrony in the cyber-physical system and the hybrid caused by heterogeneity, time-varying state equation in topology and cuts in algebra are introduced to TVPHAG. Based on TVPHAG, the evaluation of the reliability of cyber-physical systems with multiple equipment and multiple timescales is established. On this basis, the influences of physical conditions, cyberattacks, physical attacks, and cyber-physical attacks on substations are analyzed, respectively. Finally, the simulation shows that the method is effective in evaluating the reliability of smart substations, providing a new method for the evaluation of reliability. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The future development of power grid puts forward the requirement of unified network for all the communication services in smart substation.In order to meet the different quality of service (QoS) requirements of various communication services, as well as ensure the real-time and reliability of key services when the network congestion occurs, a priority scheme and its queue scheduling method for the smart substation was proposed.The priorities of the communication services in the smart substation were assigned considering the delay requirements, the importance to power grid operation control, and the traffic of the communication services.The queue scheduling algorithm of hierarchical deficit weighted round robin (HDWRR), combining the advantages of strict priority queue (SPQ) algorithm and deficit weight round robin (DWRR) algorithm, was designed for the proposed priority scheme.The simulation results show that the proposed method has isolation ability for malicious traffic, and can ensure the real-time and reliable transmission of key services in smart substation once the network is congested.

Copyright of Journal of Test & Measurement Technology is the property of Publishing Center of North University of China and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of intelligent operation and maintenance of substations, the daily inspection of substations needs to process massive video and image data. This puts forward higher requirements on the processing speed and accuracy of defect detection. Based on the end-to-end learning paradigm, this article proposes an intelligent detection method for substation insulator defects based on CenterMask. First, the backbone network VoVNet is improved according to the residual connection and eSE module, which effectively solves the problems of deep network saturation and gradient information loss. On this basis, an insulator mask generation method based on a spatial attention-directed mechanism is proposed. Insulators with complex image backgrounds are accurately segmented. Then, three strategies of pixel-wise regression prediction, multi-scale features, and centerness are introduced. The anchor-free single-stage target detector accurately locates the defect points of insulators. Finally, an example analysis is carried out with the substation inspection image of a power supply company in a certain area to verify the effectiveness and robustness of the proposed method.

Intelligent substation is an important fulcrum of the smart grid strategy, with the increasing of primary equipment in smart substation, the amount of equipment information and data increases exponentially, traditional data retrieval methods have been unable to adapt to requirement of the massive data processing, how accurate and efficient retrieval substation equipment information become the focus of the research problem. Therefore, a method for the primary information retrieval of smart substation equipment based on knowledge graphs was proposed. First, the primary equipment information of the smart substation was classified to obtain relevant equipment information corpus. then an unstructured equipment information extraction framework was defined to achieve efficient equipment information corpus Extraction. then, hidden Markov model was used to segment equipment information so as to construct a knowledge map of substation primary equipment information, realize the visual display of equipment information, and break through the limitations of two-dimensional semantic tables. Finally, the knowledge map technology was utilized to design the information management system of the smart substation primary equipment. Experiments show that the smart substation primary equipment information record retrieval system based on the knowledge graph can provide accurate equipment information and realize the efficient retrieval of smart substation equipment information. [ABSTRACT FROM AUTHOR]

The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish a smart substation network traffic prediction model based on the IGSA‐WNN. A comparative analysis of the experimental results shows that the performance of the IGSA‐WNN‐based prediction model further improves the convergence velocity and prediction accuracy, and that the proposed model solves the deficiency issues of the original WNN, such as slow convergence velocity and ease of falling into a locally optimal solution; thus, it is a better smart substation network traffic prediction model.

With the continuous improvement of substation automation, the number of communication equipment has risen sharply, the network topology is more complicated, and the problem of unable to locate the fault of process-level communication networks quickly and accurately has become more and more prominent. Under this background, to improve the maintenance efficiency of process-level communication networks in the smart substation, this article proposes a method for fault location of process-level communication networks based on deep neural networks. Based on the redundant monitoring of the fault state, the fault feature information of different monitoring nodes in the message transmission process is analyzed, and the characterization method of the fault feature information is proposed accordingly. Based on the emergence principle, it realizes the automatic generation of fault samples according to the physical connection, logical connection, and message subscription relationship of process-level communication networks. Combined with the training rules in deep learning theory, a fault location model of process-level communication networks based on deep neural networks is established, and the real-time location steps are given. Taking the process-level communication network of a typical 110kV smart substation as an example, simulations verify the effectiveness and accuracy of the proposed fault location method in single fault environments and multiple fault environments. Besides, accurate results can be obtained even when the fault feature information is wrong or missing, and the anti-interference ability is excellent.

Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.

Currently, there are few research on the influence of human reliability upon the reliability of integrated substation automation system (ISAS). This paper proposed a risk assessment method of ISAS considering human reliability. First, according to the operators work condition, estimate the human error probability based on analytic hierarchy process-smart substation automation system to correct the failure probability of physical devices. Then, adopt the function decomposition based method to assess the failure risk of functions. Finally, obtain the failure risk of ISAS by mixing the function risks to characterize the reliability of ISAS and offer guidance to dispatching department. The big impact of human reliability on the ISAS risk is demonstrated in case study, which means considering human reliability is more objective than the traditional method.

The future development of power grid puts forward the requirement of unified network for all the communication services in smart substation. In order to meet the different quality of service (QoS) requirements of various communication services, as well as ensure the real-time and reliability of key services when the network congestion occurs, a priority scheme and its queue scheduling method for the smart substation was proposed. The priorities of the communication services in the smart substation were assigned considering the delay requirements, the importance to power grid operation control, and the traffic of the communication services. The queue scheduling algorithm of hierarchical deficit weighted round robin (HDWRR), combining the advantages of strict priority queue (SPQ) algorithm and deficit weight round robin (DWRR) algorithm, was designed for the proposed priority scheme. The simulation results show that the proposed method has isolation ability for malicious traffic, and can ensure the real-time and reliable transmission of key services in smart substation once the network is congested. [ABSTRACT FROM AUTHOR]

This paper describes the technologies of virtual circuit and analyzes the SCL configuration files of smart substation. Based on the traditional virtual circuit test method, the visual technique of.NET is employed to develop the smart substation virtual circuit test tool accorded with the standard of IEC61850 9-2, the static test scheme and dynamic test scheme are presented respectively. The problem of SCL configuration of smart substation network could be detected quickly by the visual simulation of secondary virtual circuit for smart substation. Our work provides an effective virtual circuit test tool for smart substations. [ABSTRACT FROM AUTHOR]