scholarly journals Computationally Efficient Optimal Control for Unstable Power System Models

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Mahtab Uddin ◽  
M. Monir Uddin ◽  
Md. Abdul Hakim Khan
Keyword(s):  
Optimal Control ◽  
Power System ◽  
Large Scale ◽  
Krylov Subspace ◽  
Feedback Stabilization ◽  
Descriptor Systems ◽  
Low Rank ◽  
Computationally Efficient ◽  
System Models ◽  
Alternating Direction

In this article, the focus is mainly on gaining the optimal control for the unstable power system models and stabilizing them through the Riccati-based feedback stabilization process with sparsity-preserving techniques. We are to find the solution of the Continuous-time Algebraic Riccati Equations (CAREs) governed from the unstable power system models derived from the Brazilian Inter-Connected Power System (BIPS) models, which are large-scale sparse index-1 descriptor systems. We propose the projection-based Rational Krylov Subspace Method (RKSM) for the iterative computation of the solution of the CAREs. The novelties of RKSM are sparsity-preserving computations and the implementation of time-convenient adaptive shift parameters. We modify the Low-Rank Cholesky-Factor integrated Alternating Direction Implicit (LRCF-ADI) technique-based nested iterative Kleinman–Newton (KN) method to a sparse form and adjust this to solve the desired CAREs. We compare the results achieved by the Kleinman–Newton method with that of using the RKSM. The applicability and adaptability of the proposed techniques are justified numerically with MATLAB simulations. Transient behaviors of the target models are investigated for comparative analysis through the tabular and graphical approaches.

scholarly journals Efficient Techniques for Solving the Periodic Projected Lyapunov Equations and Model Reduction of Periodic Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad-Sahadet Hossain ◽  
M. Monir Uddin
Keyword(s):  
Model Reduction ◽  
Discrete Time ◽  
Large Scale ◽  
Computational Cost ◽  
Descriptor Systems ◽  
Low Rank ◽  
Lyapunov Equations ◽  
Adi Method ◽  
Smith Method ◽  
Alternating Direction

We have presented the efficient techniques for the solutions of large-scale sparse projected periodic discrete-time Lyapunov equations in lifted form. These types of problems arise in model reduction and state feedback problems of periodic descriptor systems. Two most popular techniques to solve such Lyapunov equations iteratively are the low-rank alternating direction implicit (LR-ADI) method and the low-rank Smith method. The main contribution of this paper is to update the LR-ADI method by exploiting the ideas of the adaptive shift parameters computation and the efficient handling of complex shift parameters. These approaches efficiently reduce the computational cost with respect to time and memory. We also apply these iterative Lyapunov solvers in balanced truncation model reduction of periodic discrete-time descriptor systems. We illustrate numerical results to show the performance and accuracy of the proposed methods.

scholarly journals SVD-Krylov based Sparsity-preserving Techniques for Riccati-based Feedback Stabilization of Unstable Power System Models

2021 ◽  
Author(s):  
Mahtab Uddin ◽  
M. Monir Uddin ◽  
M. A. Hakim Khan ◽  
M. Tanzim Hossain
Keyword(s):  
Power System ◽  
Riccati Equations ◽  
Descriptor Systems ◽  
Low Rank ◽  
Reduced Order Models ◽  
Reduced Order ◽  
System Models ◽  
Reduced Order Modelling ◽  
Feedback Matrix ◽  
Finite Solution

We propose an efficient sparsity-preserving reduced-order modelling approach for index-1 descriptor systems extracted from large-scale power system models through two-sided projection techniques. The projectors are configured by utilizing Gramian based singular value decomposition (SVD) and Krylov subspace-based reduced-order modelling. The left projector is attained from the observability Gramian of the system by the low-rank alternating direction implicit (LR-ADI) technique and the right projector is attained by the iterative rational Krylov algorithm (IRKA). The classical LR-ADI technique is not suitable for solving Riccati equations and it demands high computation time for convergence. Besides, in most of the cases, reduced-order models achieved by the basic IRKA are not stable and the Riccati equations connected to them have no finite solution. Moreover, the conventional LR-ADI and IRKA approach not preserves the sparse form of the index-1 descriptor systems, which is an essential requirement for feasible simulations. To overcome those drawbacks, the fitting of LR-ADI and IRKA based projectors from left and right sides, respectively, desired reduced-order systems attained. So that, finite solution of low-rank Riccati equations, and corresponding feedback matrix can be executed. Using the mechanism of inverse projection, the Riccati-based optimal feedback matrix can be computed to stabilize the unstable power system models. The proposed approach will maintain minimized ℌ2 -norm of the error system for reduced-order models of the target models.

The extended nonsymmetric block Lanczos methods for solving large-scale differential Lyapunov equations

2021 ◽  
Vol 8 (3) ◽  
pp. 526-536
Author(s):  
L. Sadek ◽  
◽  
H. Talibi Alaoui ◽  
Keyword(s):  
Matrix Equation ◽  
Large Scale ◽  
Krylov Subspace ◽  
Low Rank ◽  
Lyapunov Equations ◽  
Lanczos Algorithm ◽  
Lyapunov Matrix ◽  
Block Lanczos ◽  
Low Dimensional ◽  
Differential Lyapunov Equations

In this paper, we present a new approach for solving large-scale differential Lyapunov equations. The proposed approach is based on projection of the initial problem onto an extended block Krylov subspace by using extended nonsymmetric block Lanczos algorithm then, we get a low-dimensional differential Lyapunov matrix equation. The latter differential matrix equation is solved by the Backward Differentiation Formula method (BDF) or Rosenbrock method (ROS), the obtained solution allows to build a low-rank approximate solution of the original problem. Moreover, we also give some theoretical results. The numerical results demonstrate the performance of our approach.

Identifying Power Flow Control Infeasibilities in Large-Scale Power System Models

2009 ◽  
Vol 24 (1) ◽  
pp. 86-95 ◽  
Author(s):  
JoÃo A. Passos Filho ◽  
Nelson Martins ◽  
Djalma M. Falcao
Keyword(s):  
Power System ◽  
Flow Control ◽  
Power Flow ◽  
Large Scale ◽  
Power Flow Control ◽  
System Models

scholarly journals An Alternating Direction Implicit Method for Solving Projected Generalized Continuous-Time Sylvester Equations

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Yujian Zhou ◽  
Liang Bao ◽  
Yiqin Lin
Keyword(s):  
Continuous Time ◽  
Computational Cost ◽  
Implicit Method ◽  
Descriptor Systems ◽  
Low Rank ◽  
Balanced Truncation ◽  
Alternating Direction Implicit Method ◽  
Alternating Direction Implicit ◽  
Smith Method ◽  
Alternating Direction

We present the generalized low-rank alternating direction implicit method and the low-rank cyclic Smith method to solve projected generalized continuous-time Sylvester equations with low-rank right-hand sides. Such equations arise in control theory including the computation of inner products andℍ2norms and the model reduction based on balanced truncation for descriptor systems. The requirements of these methods are moderate with respect to both computational cost and memory. Numerical experiments presented in this paper show the effectiveness of the proposed methods.

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