Bad data identification and fault diagnosis of smart substation based on secondary system information redundancy
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Lingwen Meng
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Ruifeng Zhang
Abstract
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.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This work was supported by China Southern Power Grid Corporation Key Science and Technology Project: Research and Application of Key Technologies for Information Governance of the Smart Substations Secondary System (GZKJXM20191312).
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Conflict of interest statement: The authors declare no conflicts of interest.
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Data availability: The data has been presented in the paper.
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© 2022 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
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- A real-time hybrid battery state of charge and state of health estimation technique in renewable energy integrated microgrid applications
- Adaptive Single Carrier Modulation scheme based MLI supported TDVC for Voltage Quality enhancement
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- A new reduced switch double boost five-level inverter with Self-Balancing of Capacitor Voltage
- Voltage control of standalone photovoltaic – electrolyzer- fuel cell-battery energy system
- Bad data identification and fault diagnosis of smart substation based on secondary system information redundancy
- Fault detection method of digital three-dimensional substation based on singular value decomposition
- Blockchain data privacy protection modeling based on CP-ABE algorithm
Articles in the same Issue
- Frontmatter
- Research Articles
- Accounting for current limitation and input saturation in adaptive nonlinear control of fuel cell power system
- Day-ahead and real-time congestion scheduling method for distribution network with multiple access to electric vehicle charging piles
- A real-time hybrid battery state of charge and state of health estimation technique in renewable energy integrated microgrid applications
- Adaptive Single Carrier Modulation scheme based MLI supported TDVC for Voltage Quality enhancement
- Efficiency analysis of dual motor powertrain with planetary gear set
- Information model of low-voltage distribution IoT monitoring terminal based on IEC 61850
- Most Valuable Player based selective harmonic elimination in a cascaded H-bridge inverter for wide operating range
- A new reduced switch double boost five-level inverter with Self-Balancing of Capacitor Voltage
- Voltage control of standalone photovoltaic – electrolyzer- fuel cell-battery energy system
- Bad data identification and fault diagnosis of smart substation based on secondary system information redundancy
- Fault detection method of digital three-dimensional substation based on singular value decomposition
- Blockchain data privacy protection modeling based on CP-ABE algorithm
