This paper aims at putting forward viewpoints regarding the use of stability technology to prevent and control cascading outages by examining recent blackout events.Based on the inquiry reports of the 2011 SouthwestAm...This paper aims at putting forward viewpoints regarding the use of stability technology to prevent and control cascading outages by examining recent blackout events.Based on the inquiry reports of the 2011 SouthwestAmerica blackout and the 2012 India power blackouts,event evolution features are first summarized from a stability perspective.Then a comparative analysis is conducted so as to propose suggestions of effective measures,either preventive or emergency,which could have avoided the blackouts.It is shown that applications of several mature technologies can create opportunities of preventing or interrupting the cascading development.These include offline dynamic simulation,online stability analysis and preventive control,real-time situational awareness and automatic emergency control.Further R&D directions are given to address the challenges of modern power systems as well.They cover system fault identification criterion of protection and control devices,verification of adaptability of control effect to system operating conditions,real-time operational management of emergency control measures and improvement of simulation accuracy.展开更多
Addressed to the N-k_(1)-k_(2) cascading outages,it is computationally burdensome for the reliable calculation of active and reactive power flows.This paper builds a comprehensive framework with three algorithms,inclu...Addressed to the N-k_(1)-k_(2) cascading outages,it is computationally burdensome for the reliable calculation of active and reactive power flows.This paper builds a comprehensive framework with three algorithms,including the distribution factor(DF),the Newton-Raphson(NR),and the first iteration of NR algorithm(termed as 1J).Classifiers are designed to determine whether the NR algorithm should be employed for accuracy.Classifier features are extracted upon the analytical error of 1J.As reactive power is partially considered in the 1J but neglected in the DF algorithm,the deviation between the solutions is taken as one crucial feature.The support vector machine(SVM)is then utilized for classifier training.As the deep integration of the causal inference and the statistical paradigm,this framework calculates active and reactive power flows rapidly,reliably,and robustly.The effectiveness and robustness are fully validated in three typical IEEE systems.展开更多
基金This work is supported by State Grid Corporation of China(No.SGCC-MPLG003-2012).
文摘This paper aims at putting forward viewpoints regarding the use of stability technology to prevent and control cascading outages by examining recent blackout events.Based on the inquiry reports of the 2011 SouthwestAmerica blackout and the 2012 India power blackouts,event evolution features are first summarized from a stability perspective.Then a comparative analysis is conducted so as to propose suggestions of effective measures,either preventive or emergency,which could have avoided the blackouts.It is shown that applications of several mature technologies can create opportunities of preventing or interrupting the cascading development.These include offline dynamic simulation,online stability analysis and preventive control,real-time situational awareness and automatic emergency control.Further R&D directions are given to address the challenges of modern power systems as well.They cover system fault identification criterion of protection and control devices,verification of adaptability of control effect to system operating conditions,real-time operational management of emergency control measures and improvement of simulation accuracy.
基金This work was supported by the China State Grid Corporation Project of the Key Technologies of Power Grid Proactive Support for Energy Transition(No.5100-202040325A-0-0-00).
文摘Addressed to the N-k_(1)-k_(2) cascading outages,it is computationally burdensome for the reliable calculation of active and reactive power flows.This paper builds a comprehensive framework with three algorithms,including the distribution factor(DF),the Newton-Raphson(NR),and the first iteration of NR algorithm(termed as 1J).Classifiers are designed to determine whether the NR algorithm should be employed for accuracy.Classifier features are extracted upon the analytical error of 1J.As reactive power is partially considered in the 1J but neglected in the DF algorithm,the deviation between the solutions is taken as one crucial feature.The support vector machine(SVM)is then utilized for classifier training.As the deep integration of the causal inference and the statistical paradigm,this framework calculates active and reactive power flows rapidly,reliably,and robustly.The effectiveness and robustness are fully validated in three typical IEEE systems.
