Thank you Dr. Abhyankar for the guidance. I appreciate your time and effort.
Shruti On Sun, Oct 18, 2015 at 10:02 PM, Abhyankar, Shrirang G. <abhy...@anl.gov> wrote: > Shruti, > MATPOWER does use “\” operator for the linear solves. However note that, > internally, MATLAB does perform some sort of matrix reordering to reduce > the fill-ins in the factored matrix. For instance, UMFPACK uses an > approximate minimum degree reordering scheme by default. > > Shri > > From: Shruti Rao <sra...@asu.edu> > Reply-To: MATPOWER discussion forum <matpowe...@list.cornell.edu> > Date: Sunday, October 18, 2015 at 8:31 PM > To: MATPOWER discussion forum <matpowe...@list.cornell.edu> > Subject: Re: Question about sparsity-based implementation in MATPower > > Thank you Dr. Abhyakar, > > My main aim was to confirm that MATPower uses the inbuilt "\" to solve the > matrix equations and not Tinney or some other form of reordering and then > LU factorization followed by forward,backward substitutions. From your > response I assume that it is true that MATpower uses "\" right? > > Thank you for your response. > > > > On Sun, Oct 18, 2015 at 6:27 PM, Abhyankar, Shrirang G. <abhy...@anl.gov> > wrote: > >> Hi Shruti, >> The direct linear solver used by MATLAB depends on the symmetry of the >> Jacobian matrix. For MATPOWER test cases that have symmetric Jacobians (due >> to inactive taps), a Cholesky factorization is used (LL^T = A). For cases >> that lead to non-symmetric Jacobian, MATLAB uses UMFPACK for performing the >> linear solve. >> >> Shri >> >> From: Shruti Rao <sra...@asu.edu> >> Reply-To: MATPOWER discussion forum <matpowe...@list.cornell.edu> >> Date: Sunday, October 18, 2015 at 5:37 PM >> To: MATPOWER discussion forum <matpowe...@list.cornell.edu> >> Subject: Question about sparsity-based implementation in MATPower >> >> Greetings MATPower community, >> >> I had a question about the way sparsity-based techniques are used in the >> Newton-Raphson solver of the power flow algorithm in MATPower. >> >> I ran the code step-by-step and from my understanding, the way the >> sparsity of the Jacobian matrix is exploited is that it is created as a >> MATLAB "sparse" matrix wherein only the non-zeros are stored with the >> respective matrix positions and then the MATLAB operator "\" is invoked >> while calculating dx = -(J \ F); where J is the Jacobian and F is the >> vector of mismatches. >> >> MATLAB "\" by default exploits the sparsity of the matrix by using a LU >> solver. The kind of solver "\" uses actually depends on the matrix >> structure if it is diagonal/tridiagonal/banded and so on (Flowchart >> obtained from Mathworks website attached in the email). I assume based on >> the typical structure of the Jacobian that an LU solver is most likely to >> be chosen. >> >> Is my understanding correct or am I missing something out? Thank you for >> your time and effort. >> >> >> -- >> Best Regards, >> Shruti Dwarkanath Rao >> >> Graduate Research Assistant >> School of Electrical, Computer and Energy Engineering >> Arizona State University >> Tempe, AZ, 85281 >> 650 996 0116 >> >> > > > -- > Best Regards, > Shruti Dwarkanath Rao > > Graduate Research Assistant > School of Electrical, Computer and Energy Engineering > Arizona State University > Tempe, AZ, 85281 > 650 996 0116 > > -- Best Regards, Shruti Dwarkanath Rao Graduate Research Assistant School of Electrical, Computer and Energy Engineering Arizona State University Tempe, AZ, 85281 650 996 0116
