High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guara...High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guarantee the stability of the slopes and the safety of residents. This article pre-sents a comprehensive method for integrating particle swarm optimization （PSO） and support vector machines （SVMs）, combined with numerical analysis, to handle the determination of appropriate rein-forcement parameters, which guarantee both slope stability and lower construction costs. The relation-ship between reinforcement parameters and slope factor of safety （FOS） and construction costs is in-vestigated by numerical analysis and SVMs, PSO is adopted to determine the best SVM performance resulting in the lowest construction costs for a given FOS. This methodology is demonstrated by a prac-tical reservoir high cut slope stabilised with anti-sliding piles, which is located at the Xingshan （兴山） County of Hubei （湖北） Province, China. The determination process of reinforcement parameters is discussed profoundly, and the pile spacing, length, and section dimension are obtained. The results pro-vide a satisfactory reinforcement design, making it possible a signficant reduction in construction costs.展开更多
This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repul...This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repulsion(ASSMR),of doubly-fed induction generator based wind farms(DFIG-WFs)penetrated power systems.As some important parameters of DFIG-WF are difficult to obtain,reinforcement learning and least squares method are applied to identify those important parameters.By predicting the location of closed-loop subsynchronous oscillation(SSO)modes based on the calculation of partial differentials of characteristic equation,both ASSMA and ASSMR can be found.The proposed method in this paper can select SSO modes which move to the right half complex planes as control parameters change.Besides,the proposed open-loop analysis method is adaptive to parameter uncertainty.Simulation studies are carried out on the 4-machine 11-bus power system to verify properties of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 40902091, 51178187)the Special Funds for Major State Basic Research Project (No. 2010CB732006)
文摘High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guarantee the stability of the slopes and the safety of residents. This article pre-sents a comprehensive method for integrating particle swarm optimization （PSO） and support vector machines （SVMs）, combined with numerical analysis, to handle the determination of appropriate rein-forcement parameters, which guarantee both slope stability and lower construction costs. The relation-ship between reinforcement parameters and slope factor of safety （FOS） and construction costs is in-vestigated by numerical analysis and SVMs, PSO is adopted to determine the best SVM performance resulting in the lowest construction costs for a given FOS. This methodology is demonstrated by a prac-tical reservoir high cut slope stabilised with anti-sliding piles, which is located at the Xingshan （兴山） County of Hubei （湖北） Province, China. The determination process of reinforcement parameters is discussed profoundly, and the pile spacing, length, and section dimension are obtained. The results pro-vide a satisfactory reinforcement design, making it possible a signficant reduction in construction costs.
基金supported in part by the State Key Program of National Natural Science Foundation of China under Grant No.U1866210the National Natural Science Foundation of China under Grant No.51807067.
文摘This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repulsion(ASSMR),of doubly-fed induction generator based wind farms(DFIG-WFs)penetrated power systems.As some important parameters of DFIG-WF are difficult to obtain,reinforcement learning and least squares method are applied to identify those important parameters.By predicting the location of closed-loop subsynchronous oscillation(SSO)modes based on the calculation of partial differentials of characteristic equation,both ASSMA and ASSMR can be found.The proposed method in this paper can select SSO modes which move to the right half complex planes as control parameters change.Besides,the proposed open-loop analysis method is adaptive to parameter uncertainty.Simulation studies are carried out on the 4-machine 11-bus power system to verify properties of the proposed method.
