scholarly journals Efficient computation of matrix–vector products with full observation weighting matrices in data assimilation

2021 ◽  
Author(s):  
Guannan Hu ◽  
Sarah L. Dance
Keyword(s):  
Data Assimilation ◽  
Efficient Computation ◽  
Matrix Vector

scholarly journals Optimal solution error covariance in highly nonlinear problems of variational data assimilation

2012 ◽  
Vol 19 (2) ◽  
pp. 177-184 ◽  
Author(s):  
V. Shutyaev ◽  
I. Gejadze ◽  
G. J. M. Copeland ◽  
F.-X. Le Dimet
Keyword(s):  
Nonlinear Dynamics ◽  
Data Assimilation ◽  
Optimal Solution ◽  
Nonlinear Problems ◽  
Variational Data Assimilation ◽  
Model Parameters ◽  
Efficient Computation ◽  
Viscous Term ◽  
Highly Nonlinear ◽  
The Cost

Abstract. The problem of variational data assimilation (DA) for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition, boundary conditions and/or model parameters. The input data contain observation and background errors, hence there is an error in the optimal solution. For mildly nonlinear dynamics, the covariance matrix of the optimal solution error can be approximated by the inverse Hessian of the cost function. For problems with strongly nonlinear dynamics, a new statistical method based on the computation of a sample of inverse Hessians is suggested. This method relies on the efficient computation of the inverse Hessian by means of iterative methods (Lanczos and quasi-Newton BFGS) with preconditioning. Numerical examples are presented for the model governed by the Burgers equation with a nonlinear viscous term.

scholarly journals Log(v) 3LPF: A Linear Power Flow Formulation for Unbalanced Three-Phase Distribution Systems

2021 ◽  
Author(s):  
Ignacio Losada Carreño ◽  
Shammya Saha ◽  
Anna Scaglione ◽  
Daniel Arnold ◽  
Ngo Sy-Toan ◽  
...  
Keyword(s):  
Power Flow ◽  
Distribution Systems ◽  
Phase Distribution ◽  
Decomposition Methods ◽  
Efficient Computation ◽  
Flow Solver ◽  
Flow Equations ◽  
Ac Power ◽  
Three Phase ◽  
Matrix Vector

In this work, we introduce Log(v) 3LPF, a linear power flow solver for unbalanced three-phase distribution systems. Log(v) 3LPF uses a logarithmic transform of the voltage phasor to linearize the AC power flow equations around the balanced case. We incorporate the modeling of ZIP loads, transformers, capacitor banks, switches and their corresponding controls and express the network equations in matrix-vector form. With scalability in mind, special attention is given to the computation of the inverse of the system admittance matrix, Ybus. We use the Sherman-Morrison-Woodbury identity for an efficient computation of the inverse of a rank-k corrected matrix and compare the performance of this method with traditional LU decomposition methods in terms of FLOPS. We showcase the solver for a variety of network sizes, ranging from tens to thousands of nodes, and compare the Log(v) 3LPF with commercial-grade software, such as OpenDSS. <br>

scholarly journals Log(v) 3LPF: A Linear Power Flow Formulation for Unbalanced Three-Phase Distribution Systems

2021 ◽  
Author(s):  
Ignacio Losada Carreño ◽  
Shammya Saha ◽  
Anna Scaglione ◽  
Daniel Arnold ◽  
Ngo Sy-Toan ◽  
...  
Keyword(s):  
Power Flow ◽  
Distribution Systems ◽  
Phase Distribution ◽  
Decomposition Methods ◽  
Efficient Computation ◽  
Flow Solver ◽  
Flow Equations ◽  
Ac Power ◽  
Three Phase ◽  
Matrix Vector

In this work, we introduce Log(v) 3LPF, a linear power flow solver for unbalanced three-phase distribution systems. Log(v) 3LPF uses a logarithmic transform of the voltage phasor to linearize the AC power flow equations around the balanced case. We incorporate the modeling of ZIP loads, transformers, capacitor banks, switches and their corresponding controls and express the network equations in matrix-vector form. With scalability in mind, special attention is given to the computation of the inverse of the system admittance matrix, Ybus. We use the Sherman-Morrison-Woodbury identity for an efficient computation of the inverse of a rank-k corrected matrix and compare the performance of this method with traditional LU decomposition methods in terms of FLOPS. We showcase the solver for a variety of network sizes, ranging from tens to thousands of nodes, and compare the Log(v) 3LPF with commercial-grade software, such as OpenDSS. <br>

Integral Control Data Assimilation in Wave Predictions

1997 ◽  
Author(s):  
L.H. Holthuijsen ◽  
N. Booij ◽  
M. van Endt ◽  
S. Caires ◽  
C. Guedes Soares
Keyword(s):  
Data Assimilation ◽  
Control Data ◽  
Integral Control
Sign in / Sign up

Export Citation Format

Share Document