This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as ru...This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.展开更多
The integration of electricity technology and information technology,such as the Internet of Things(IoT),enables the construction of new power systems,along with the inno-vation of application scenarios and business s...The integration of electricity technology and information technology,such as the Internet of Things(IoT),enables the construction of new power systems,along with the inno-vation of application scenarios and business scope.The key technologies of power IoT and the data flow process are summarised first.The IoT technology and application scenario requirements of power generation,transmission,loading,and storage of new power systems are studied.Thus,the nature of the collaborative development of the digital power grid and the IoT is demonstrated from the perspective of data processing in power IoT and application requirements in power systems.The key problems and so-lutions faced by the power IoT under the digital transformation are described,and the cross-integration of key technologies and promotion of application scenario innovation are prospected.Finally,the key issues of future technological development were dis-cussed,providing reference ideas for fully leveraging the value of energy and electricity data production factors and promoting the construction of a digital electricity ecosystem.展开更多
Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(...Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.展开更多
By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and ...By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.展开更多
The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and ...The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.展开更多
文摘This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.
基金National Natural Science Foundation of China,Grant/Award Number:52177085DGRI‐CSG Innovative Project,Grant/Award Number:210000KK52220036。
文摘The integration of electricity technology and information technology,such as the Internet of Things(IoT),enables the construction of new power systems,along with the inno-vation of application scenarios and business scope.The key technologies of power IoT and the data flow process are summarised first.The IoT technology and application scenario requirements of power generation,transmission,loading,and storage of new power systems are studied.Thus,the nature of the collaborative development of the digital power grid and the IoT is demonstrated from the perspective of data processing in power IoT and application requirements in power systems.The key problems and so-lutions faced by the power IoT under the digital transformation are described,and the cross-integration of key technologies and promotion of application scenario innovation are prospected.Finally,the key issues of future technological development were dis-cussed,providing reference ideas for fully leveraging the value of energy and electricity data production factors and promoting the construction of a digital electricity ecosystem.
基金Supported by the National Key R&D Program of China (No.2023YFC3008100)the National Natural Science Foundation of China (No.U23A2033)
文摘Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.
基金supported by State Grid Information and Telecommunication Group Scientific and Technological Innovation Project“Research on Power Digital Space Technology System and Key Technologies”(Program No.SGIT0000XMJS2310456).
文摘By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.
文摘The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.
