This paper presents a transient energy based screening approach for quickly identifying potential critical attacks that might have significant impacts on power system transient stability.Specifically,the proposed appr...This paper presents a transient energy based screening approach for quickly identifying potential critical attacks that might have significant impacts on power system transient stability.Specifically,the proposed approach focuses on the total transient energy injected into power systems as the result of assumptive cyber attacks.The computational improvements of the proposed method are significant as the time-domain simulations can be avoided.The efficacy of the proposed approach is demonstrated using a practical power system with various cyber attack scenarios.The identification results of the proposed method can be used to guide more detailed impact analysis and to develop more effective countermeasures against cyber attacks.展开更多
Practical power curve estimation is necessary for evaluating the actual power output of a wind farm;since a power curve provided by the wind turbine manufacture will be different with the actual power curve following ...Practical power curve estimation is necessary for evaluating the actual power output of a wind farm;since a power curve provided by the wind turbine manufacture will be different with the actual power curve following several years of operation.It can be estimated using the collected power output data including wind power generation and wind speed.This data is commonly ill-distributed due to a noticeable number of outliers,which impose a serious bias to the estimation models obtained from this data.It introduces an interesting challenge in estimation of a power curve.In this paper,an intelligent algorithm is proposed for estimating a power curve using the measured data while modeling and bias errors,imposed to the estimation model by the outliners,are minimized.More specifically,this algorithm is designed based on the Statistical Analysis Software(SAS)programming software package in order to facilitate analyzing and managing big datasets of wind speed and wind power generation.The effectiveness and practical application of the proposed algorithm is demonstrated using a real-world dataset.展开更多
基金supported in part by the National Science Foundation under Grant ECCS-0955265.
文摘This paper presents a transient energy based screening approach for quickly identifying potential critical attacks that might have significant impacts on power system transient stability.Specifically,the proposed approach focuses on the total transient energy injected into power systems as the result of assumptive cyber attacks.The computational improvements of the proposed method are significant as the time-domain simulations can be avoided.The efficacy of the proposed approach is demonstrated using a practical power system with various cyber attack scenarios.The identification results of the proposed method can be used to guide more detailed impact analysis and to develop more effective countermeasures against cyber attacks.
文摘Practical power curve estimation is necessary for evaluating the actual power output of a wind farm;since a power curve provided by the wind turbine manufacture will be different with the actual power curve following several years of operation.It can be estimated using the collected power output data including wind power generation and wind speed.This data is commonly ill-distributed due to a noticeable number of outliers,which impose a serious bias to the estimation models obtained from this data.It introduces an interesting challenge in estimation of a power curve.In this paper,an intelligent algorithm is proposed for estimating a power curve using the measured data while modeling and bias errors,imposed to the estimation model by the outliners,are minimized.More specifically,this algorithm is designed based on the Statistical Analysis Software(SAS)programming software package in order to facilitate analyzing and managing big datasets of wind speed and wind power generation.The effectiveness and practical application of the proposed algorithm is demonstrated using a real-world dataset.
