Dear Professor Zimmerman, Id like to know about the numerically failed criterion used by MIPS algorithm. I attach the code used in the mips.m file.
alpha_min = 1e-8; %% OPT_AP_AD_MIN
if any(isnan(x)) || alphap < alpha_min || alphad < alpha_min || ...
gamma < eps || gamma > 1/eps
if opt.verbose
fprintf('\nNumerically Failed\n');
end
eflag = -1;
break;
end
The MIPS algorithm implemented in Matpower is considered to have failed when
the primal and dual variables (alphap and alphad) are lower than a critical
value.
For example, in the Garver test system I obtained the attached configuration
(garver_no_CV.m), where MIPS algorithm numerically failed; Virtual
generators are modeled in bus 2, 4 and 5. You could simulate the
configuration using the code mpopt=mpoption;
mpopt=mpoption('OPF_ALG',200,'VERBOSE',3); rundcopf(garver_no_CV,mpopt);.
You can see that the algorithm fails in 23 iterations, but if you analyze
the decision variables in the last iteration, you will note that the
solution point is very near the optimal solution. The algorithm fails
because the condition used by MIPS (alphap < alpha_min || alphad <
alpha_min), so I realize that the algorithm needs more iterations to solve
the DC-OPF problem. Considering a sensitivity analysis, I use another
alphan_min values (1e-9 and 1e-10), and I run the DC-OPF problem again. The
problem converges to the optimal solution.
Id like to know about failed criterion used by MIPS algorithm in order to
understand the criterion and give some opinions about it. I have the
following questions: 1) Is the condition necessary?; and 2) What was the
criterion to formulate this condition?
I accomplished a sensitivity analysis, and my recommendation will be
increase the critical value to 1e-10. I solved the static transmission
planning problem with this value using the SRA evolutionary algorithm, and I
cannot find any infeasible solution (numerically filed) conducting 100
simulations.
I think the DC-OPF problem modeled by linear objective function and linear
constraints must find the optimal solution using the MIPS algorithm.
Ill wait for your comments and opinions about the analysis accomplished.
Regards,
Vh
De: <mailto:[email protected]>
[email protected] [
<mailto:[email protected]>
mailto:[email protected]] En nombre de Victor Hugo
Hinojosa M.
Enviado el: lunes, 23 de septiembre de 2013 11:09
Para: 'MATPOWER discussion forum'
Asunto: RE: Reasons for non convergence of optimal power flows
Dear Professor Zimmerman,
Id like to study in more detail the problem of the initial point, so I want
to keep on working in this issue in order to obtain a better criterion. In
this moment, my single recommendation will be that user should consider a
different point.
I think that the PTDF factors can help to improve the convergence of the
MIPS algorithm, so I need more time to develop some criterions.
Regards,
Víctor
De: <mailto:[email protected]>
[email protected] [
<mailto:[email protected]>
mailto:[email protected]] En nombre de Ray
Zimmerman
Enviado el: lunes, 16 de septiembre de 2013 13:35
Para: MATPOWER discussion forum
Asunto: Re: Reasons for non convergence of optimal power flows
Importancia: Alta
Thanks Victor for your input. The initial point used by MATPOWER for the
MIPS solver was simply an attempt to begin at some interior point, so I'm
not surprised at all to hear that selecting a different starting point can
sometimes result in convergence of case that ran into numerical problems.
What wasn't clear to me was whether your tests suggest a way of selecting a
starting point that is likely to be consistently better than the one
currently being used. Or is it just an issue of when one doesn't work, try
a different one?
--
Ray Zimmerman
Senior Research Associate
B30 Warren Hall, Cornell University, Ithaca, NY 14853
phone: (607) 255-9645
On Sep 13, 2013, at 4:21 PM, Victor Hugo Hinojosa M. <
<mailto:[email protected]> [email protected]> wrote:
Dear Professor Zimmerman and Santiago,
I had the same problem that Santiago mentioned when I applied an
evolutionary algorithm to the static and dynamic transmission expansion
planning problem (TEP). The algorithm was based on local random search, so
many configurations from the solution space were analyzed. I realized that
some configuration didnt converge the Matpower, and I was trying to find
out about this problem.
For example, in the Garver test system I applied the evolutionary algorithm
to the static problem, and I obtained the attached configuration where MIPS
algorithm numerically failed. In the same way, I considered virtual
generators (bus 2, 4 and 5).
The MIPS algorithm dont solve the DC-OPF problem for this configuration
mpopt=mpoption; mpopt=mpoption('OPF_ALG',200,'VERBOSE',3);
rundcopf(garver_no_CV,mpopt);.
This problem occurs due to the initial point that the MIPS algorithm use. In
the MIPS solver, the initial point is obtained considering the average power
between the minimal and maximal power for each generator. When I changed the
initial point to the minimal power generation (x0=[0 0 0 0 0 0]), the MIPS
algorithm converges.
I had conducted some proofs in order to determine some initial points where
the algorithm has convergence problems. Ive divided each generator range,
so the MIPS algorithm can consider different initial points. I included
three analysis.
In first case, I divided the power range in 8 intervals for each generator,
so I can combine the power for each generator as initial point. The total
points that the algorithm must consider is 531 441 (9^6). For these points,
the MIPS algorithm doesnt converge in 15 078 times (2.84%). In the second,
I divided in 9 intervals, so the total points is 10^6. In this case, the
MIPS algorithm doesnt converge in 14 492 times (1.45%). Finally, I divided
in 10 intervals, so the total points is 11^6. In this case, the MIPS
algorithm doesnt converge in 42 016 times (2.37%). I attached an excel file
where its possible to figure out the initial points that the MIPS algorithm
doesnt converge considering 4 intervals. In the row 339, its possible to
see the initial point used by Matpower.
I had the same problem when I used the MIPS algorithm considering the power
generator as decision variable. The solution could be to consider another
initial point, but Id like to study again the problem.
I hope your comments and ideas about the analysis carried out.
Regards,
Víctor
De: <mailto:[email protected]>
[email protected] [mailto:bounce-96622322-12657875@
<http://list.cornell.edu> list.cornell.edu] En nombre de Ray Zimmerman
Enviado el: martes, 28 de mayo de 2013 11:34
Para: MATPOWER discussion forum
Asunto: Re: Reasons for non convergence of optimal power flows
Islands should not be a problem as long as there is a REF bus in the island
and the available generation is sufficient to meet the load in each island.
So (1) is a definite possibility, but (2) shouldn't be an issue.
Insufficient reactive power range to keep voltage magnitudes within range,
and overly restrictive branch flow limits could be other causes of an
infeasible OPF problem. Aside from things that can cause the problem to
actually be infeasible, there are also numerical issues that can affect
feasible problems. These can be the result of large ranges in parameters
(branch impedances, generator costs, etc.). In these cases, often a
different solver or algorithm may be able to solve the problem successfully.
Hope this helps,
--
Ray Zimmerman
Senior Research Associate
419A Warren Hall, Cornell University, Ithaca, NY 14853
phone: (607) 255-9645
On May 20, 2013, at 1:21 PM, Santiago Torres <
<mailto:[email protected]> [email protected]> wrote:
Dear Ray, I my resarch work I am using many transmission topologies and also
I am using ficticious generators in order to get optimal power convergence
for those different transmission topologies. Using those artificial or
ficticious generators in all exclusive load buses is suposed to help for
convergence, however in practice I am getting some transmission
configurations that do not achieve convergence.
I am thinking in the following reasons:
1) Too strict power generation limits of ficticious generators.
2) Some topologies with islanded nodes.
Can you think in other reasons?
Islanded nodes is a non convergence cause in Matpower?
Best Regards,
Santiago
--
Dr.-Ing. Santiago Torres
IEEE Senior Member
Post-Doctoral Fellow
School of Electrical and Computer Engineering
University of Campinas, Campinas, SP, Brazil
<http://www.dsee.fee.unicamp.br/> http://www.dsee.fee.unicamp.br/
Albert Einstein, 400
13083-852, Campinas, SP, Brazil
<garver_no_CV.m><No_CV_analysis.xlsx>
garver_no_CV.M
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