In order to solve the problems of mining monitor and control systems during the construction process of digital mining combined with network and embedded technologies, the kernel access equipment of a mining monitor a...In order to solve the problems of mining monitor and control systems during the construction process of digital mining combined with network and embedded technologies, the kernel access equipment of a mining monitor and control system was proposed and designed. It is the architecture of a mining embedded network multifunctional substation. This paper presents the design of hardware and software of the substation in detail. Finally, the system’s ef- ficiency was validated through experimentation.展开更多
Mission-critical IEC 61850 system architectures are designed to tolerate hardware failures to achieve the highest reliability performance.Hence,multi-channel systems are used in such systems within industrial faciliti...Mission-critical IEC 61850 system architectures are designed to tolerate hardware failures to achieve the highest reliability performance.Hence,multi-channel systems are used in such systems within industrial facilities to isolate machinery when there are process abnormalities.Inevitably,multi-channel systems introduce Common Cause Failure(CCF)since the subsystems can rarely be independent.This paper integrates CCF into the Markov reliability model to enhance the model flexibility to investigate synchronous generator intra-bay SCN architecture reliability performance considering the quality of repairs and CCF.The Markov process enables integration of the impact of CCF factors on system performance.The case study results indicate that CCF,coupled with imperfect repairs,significantly reduce system reliability performance.High sensitivity is observed at low levels of CCF,whereas the highest level of impact occurs when the system diagnostic coverage is 99%based on ISO 13849-1,and reduces as the diagnostic coverage level reduces.Therefore,it is concluded that the severity of CCF depends more on system diagnostic coverage level than the repair efficiency,although both factors impact the system overall performance.Hence,CCF should be con-sidered in determining the reliability performance of mission-critical communication networks in power distribution centres.展开更多
With the advancement of new infrastructures,the digitalization of the substation communication network has rapidly increased,and its information security risks have become increasingly prominent.Accurate and reliable ...With the advancement of new infrastructures,the digitalization of the substation communication network has rapidly increased,and its information security risks have become increasingly prominent.Accurate and reliable substation communication network flow models and flow anomaly detection methods have become an important means to prevent network security problems and identify network anomalies.The existing substation network analyzers and flow anomaly detection algorithms are usually based on threshold determination,which cannot reflect the inherent characteristics of substation automation flow based on IEC 61850 and have low detection accuracy.To effectively detect abnormal traffic,this paper fully explores the substation network traffic rules,extracts the frequency domain features of the station level network,and designs an abnormal traffic identification model based on the ResNeSt convolutional neural network.Transfer learning is used to solve the problem of insufficient abnormal traffic labeled samples in the substation.Finally,a new method of abnormal traffic detection in smart substation station level communication networks based on deep transfer learning is proposed.The T1-1 substation communication network is constructed on OPNET for abnormal simulations,and the actual network traffic in a 110kV substation is fused with CIC DDoS2019 and KDD99 data sets for the algorithm performance test,respectively.The accuracy reached is 98.73%and 98.95%,indicating that the detection model proposed in this paper has higher detection accuracy than existing algorithms.展开更多
As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS...As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.展开更多
文摘In order to solve the problems of mining monitor and control systems during the construction process of digital mining combined with network and embedded technologies, the kernel access equipment of a mining monitor and control system was proposed and designed. It is the architecture of a mining embedded network multifunctional substation. This paper presents the design of hardware and software of the substation in detail. Finally, the system’s ef- ficiency was validated through experimentation.
文摘Mission-critical IEC 61850 system architectures are designed to tolerate hardware failures to achieve the highest reliability performance.Hence,multi-channel systems are used in such systems within industrial facilities to isolate machinery when there are process abnormalities.Inevitably,multi-channel systems introduce Common Cause Failure(CCF)since the subsystems can rarely be independent.This paper integrates CCF into the Markov reliability model to enhance the model flexibility to investigate synchronous generator intra-bay SCN architecture reliability performance considering the quality of repairs and CCF.The Markov process enables integration of the impact of CCF factors on system performance.The case study results indicate that CCF,coupled with imperfect repairs,significantly reduce system reliability performance.High sensitivity is observed at low levels of CCF,whereas the highest level of impact occurs when the system diagnostic coverage is 99%based on ISO 13849-1,and reduces as the diagnostic coverage level reduces.Therefore,it is concluded that the severity of CCF depends more on system diagnostic coverage level than the repair efficiency,although both factors impact the system overall performance.Hence,CCF should be con-sidered in determining the reliability performance of mission-critical communication networks in power distribution centres.
基金supported in part by the Science and Technology Project of State Grid Corporation of China(SGHADK00PJJS2000026).
文摘With the advancement of new infrastructures,the digitalization of the substation communication network has rapidly increased,and its information security risks have become increasingly prominent.Accurate and reliable substation communication network flow models and flow anomaly detection methods have become an important means to prevent network security problems and identify network anomalies.The existing substation network analyzers and flow anomaly detection algorithms are usually based on threshold determination,which cannot reflect the inherent characteristics of substation automation flow based on IEC 61850 and have low detection accuracy.To effectively detect abnormal traffic,this paper fully explores the substation network traffic rules,extracts the frequency domain features of the station level network,and designs an abnormal traffic identification model based on the ResNeSt convolutional neural network.Transfer learning is used to solve the problem of insufficient abnormal traffic labeled samples in the substation.Finally,a new method of abnormal traffic detection in smart substation station level communication networks based on deep transfer learning is proposed.The T1-1 substation communication network is constructed on OPNET for abnormal simulations,and the actual network traffic in a 110kV substation is fused with CIC DDoS2019 and KDD99 data sets for the algorithm performance test,respectively.The accuracy reached is 98.73%and 98.95%,indicating that the detection model proposed in this paper has higher detection accuracy than existing algorithms.
文摘As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.
