136 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001.Power system applications are computationally intense, and therefore there is a need to develop new methods for performing these calculations. This study proposes the use of numerical methods based on the Krylov subspace methodology on four areas of power systems: the power flow problem, the dynamic simulation, the trajectory sensitivity analysis and the model reduction. Krylov subspace techniques are tested and compared with traditional approaches. Additionally, a physical interpretation of this methodology is investigated, and links with well-established concepts in power systems are attempted.U of I OnlyRestricted to the U of I community idenfinitely during batch inge...
Summary. Krylov subspace methods are well-known for their nice properties, but they have to be imple...
An overview of projection methods based on Krylov subspaces are given with emphasis on their applica...
In this paper, the proper orthogonal decomposition and the Arnoldi-based Krylov subspace methods are...
This paper describes the use of Krylov subspace methods in the model reduction of power systems. Add...
A power system is a system that provides for the generation, transmission, and distribution of elect...
Continuation Power Flow (CPF) analysis is developed to overcome singularity problem of Jacobian matr...
The solution of large sparse linear systems forms the core of power system computations whether it i...
Nowadays considering more accuracy and speed to compute Available Transfer Capabilities (ATC) are im...
In this paper, we present a novel stochastic simulation approach based on extended Krylov subspace m...
In this paper the Krylov subspace method is investigated regarding its use for the vibration analysi...
Current and future developments in the power system industry demand fast power flow solvers for larg...
One of the Dynamic Security Assessment (DSA) tools that electric utilities use is transient stabilit...
A large variety of physical phenomena can be described by large-scale systems of linear ordinary dif...
The performance of parareal-in-time algorithms is determined on the number of sequential, coarse ste...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
Summary. Krylov subspace methods are well-known for their nice properties, but they have to be imple...
An overview of projection methods based on Krylov subspaces are given with emphasis on their applica...
In this paper, the proper orthogonal decomposition and the Arnoldi-based Krylov subspace methods are...
This paper describes the use of Krylov subspace methods in the model reduction of power systems. Add...
A power system is a system that provides for the generation, transmission, and distribution of elect...
Continuation Power Flow (CPF) analysis is developed to overcome singularity problem of Jacobian matr...
The solution of large sparse linear systems forms the core of power system computations whether it i...
Nowadays considering more accuracy and speed to compute Available Transfer Capabilities (ATC) are im...
In this paper, we present a novel stochastic simulation approach based on extended Krylov subspace m...
In this paper the Krylov subspace method is investigated regarding its use for the vibration analysi...
Current and future developments in the power system industry demand fast power flow solvers for larg...
One of the Dynamic Security Assessment (DSA) tools that electric utilities use is transient stabilit...
A large variety of physical phenomena can be described by large-scale systems of linear ordinary dif...
The performance of parareal-in-time algorithms is determined on the number of sequential, coarse ste...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
Summary. Krylov subspace methods are well-known for their nice properties, but they have to be imple...
An overview of projection methods based on Krylov subspaces are given with emphasis on their applica...
In this paper, the proper orthogonal decomposition and the Arnoldi-based Krylov subspace methods are...