More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods.The traditional modeldriven...More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods.The traditional modeldriven methods have clear physical mechanisms and reliable evaluation results but the calculation process is time-consuming,while the data-driven methods have the strong fitting ability and fast calculation speed but the evaluation results lack interpretation.Therefore,it is a future development trend of transient stability assessment methods to combine these two kinds of methods.In this paper,the rate of change of the kinetic energy method is used to calculate the transient stability in the model-driven stage,and the support vector machine and extreme learning machine with different internal principles are respectively used to predict the transient stability in the data-driven stage.In order to quantify the credibility level of the data-driven methods,the credibility index of the output results is proposed.Then the switching function controlling whether the rate of change of the kinetic energy method is activated or not is established based on this index.Thus,a newparallel integratedmodel-driven and datadriven online transient stability assessment method is proposed.The accuracy,efficiency,and adaptability of the proposed method are verified by numerical examples.展开更多
The frequency of based on the load pattern the power system varies of the consumers. With continuous increase in the load, the frequency of the system keeps decreasing and may reach its minimum allowable limits. Furth...The frequency of based on the load pattern the power system varies of the consumers. With continuous increase in the load, the frequency of the system keeps decreasing and may reach its minimum allowable limits. Further increase in the load will result in more frequency drop leading to the need of load shedding, if excess generation is not available to cater the need. This paper proposed a methodology in a hybrid thermal-hydro system for finding the required amount of load to be shed for setting the frequency of the system within its minimum allowable limits. The load shedding steps were obtained based on the rate of change of frequency with the increase in the load in both areas. The impact of superconducting magnetic energy storage （SMES） was obtained on load shedding scheme. The comparison of the results was presented on the two-area system.展开更多
基金funded by the Science and Technology Project of State Grid Shanxi Electric Power Co.,Ltd.(Project No.520530200013).
文摘More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods.The traditional modeldriven methods have clear physical mechanisms and reliable evaluation results but the calculation process is time-consuming,while the data-driven methods have the strong fitting ability and fast calculation speed but the evaluation results lack interpretation.Therefore,it is a future development trend of transient stability assessment methods to combine these two kinds of methods.In this paper,the rate of change of the kinetic energy method is used to calculate the transient stability in the model-driven stage,and the support vector machine and extreme learning machine with different internal principles are respectively used to predict the transient stability in the data-driven stage.In order to quantify the credibility level of the data-driven methods,the credibility index of the output results is proposed.Then the switching function controlling whether the rate of change of the kinetic energy method is activated or not is established based on this index.Thus,a newparallel integratedmodel-driven and datadriven online transient stability assessment method is proposed.The accuracy,efficiency,and adaptability of the proposed method are verified by numerical examples.
文摘The frequency of based on the load pattern the power system varies of the consumers. With continuous increase in the load, the frequency of the system keeps decreasing and may reach its minimum allowable limits. Further increase in the load will result in more frequency drop leading to the need of load shedding, if excess generation is not available to cater the need. This paper proposed a methodology in a hybrid thermal-hydro system for finding the required amount of load to be shed for setting the frequency of the system within its minimum allowable limits. The load shedding steps were obtained based on the rate of change of frequency with the increase in the load in both areas. The impact of superconducting magnetic energy storage （SMES） was obtained on load shedding scheme. The comparison of the results was presented on the two-area system.
