Sure, of course I have no problem with that.
Also, I realized I missed one detail: if there were any phase-shifters in
the network, I would also (initially) set their phase-shifts to zero. That
way you would obtain a truly pure reactive network. Then, when you work
your way ramping up real power, you would also want to ramp those
phase-shifts back to their original values as well.
--
Jose L. Marin
Gridquant España SL
Grupo AIA
On Fri, Aug 14, 2015 at 10:17 PM, Abhyankar, Shrirang G. abhy...@anl.gov
wrote:
Jose,
Would it be fine with you if the steps you’ve mentioned below are added
to MATPOWER FAQ#5 http://www.pserc.cornell.edu//matpower/#pfconvergence
Many a times, useful and detailed suggestions, such as what you’ve
enumerated, get lost in email exchanges and someone trying to pull up this
information has to resort to digging it out of the archive. It’ll be good
to have your steps up on the FAQ.
Thanks,
Shri
From: Jose Luis Marin mari...@gridquant.com
Reply-To: MATPOWER discussion forum matpowe...@list.cornell.edu
Date: Wednesday, August 12, 2015 at 2:42 AM
To: MATPOWER discussion forum matpowe...@list.cornell.edu
Subject: Re: convergence problem in runpf.
Mirish,
I couldn't help notice that you're building this model from scratch (well,
from a database) and you mentioned ***To make the problem simple I used
all buses as PQ buses except one slack bus*. This actually makes it
harder to converge, unless you have *very* accurate data on what the
reactive injections Q (on generator buses) should be.
May I suggest a different, incremental approach:
1. Start by keeping all generator buses you can as PV, instead of PQ.
They will help holding up the voltage profile. After all, a PV node is a
slack bus in what regards the reactive power injection.
2. For the loads, start by zeroing out PD (real power demand), but
keeping QD (reactive demand)
3. For generators, set the scheduled PG to zero
4. For lines transformers, zero out the resistance R
5. The resulting network will be a purely reactive power model. Now
run a powerflow. If this doesn't have a feasible powerflow solution, it is
because some branches have an X parameter that is too large (or
equivalently, some load QD is too large). Ramp down the profile of QD
until you see convergence.
6. Look at the resulting Q flows across branches, and try to detect
anomalously large values (i.e. clear outliers). They will help you uncover
values of X that may be wrong (too large). Also, keep an eye on negative X
coming from equivalents such as 3-winding transformers; they may also be
wrong.
7. Once you get that working, ramp up the values of PD on loads and PG
on generators (keeping an eye on the swing's resulting PG, in order to
redistribute big excesses).
8. Finally ramp up the resistance on lines.
The whole idea is based on the fact that, for transmission networks (lines
with RX), the reactive flows are like the backbone on which real power
flows can sort of ride on. Get a healthy backbone first, and then you
can start transporting real power.
Hope it helps,
--
Jose L. Marin
Gridquant España SL
Grupo AIA
On Wed, Aug 12, 2015 at 2:36 AM, Mirish Thakur mirishtha...@gmail.com
wrote:
Dear Mr.Shree,
Thank you very much for your help. As per your suggestion and FAQ I tried
to find out the problems.
The results I got-
1) Fast-decoupled power flow did not converge in 30 iterations.
2) By following http://www.pserc.cornell.edu/matpower/#pfconvergence
I tried to runcpf to get good initial guess and i got results like
step 1 : lambda = 0.084, corrector did not converge in 10 iterations.
Where lambda is 1 and for reducing steady state loading limitation I
reduced demand less than 60 % which also failed to converge the power flow.
3) Also I tried to run an optimal power flow according to Dr. Ray's
explanation given in following link-
*https://www.mail-archive.com/search?l=matpower-l@cornell.eduq=subject:%22Re%5C%3A+%5C%5BMatpower%5C%5D+3500+bus+simulation%22o=newest
https://www.mail-archive.com/search?l=matpower-l@cornell.eduq=subject:%22Re%5C%3A+%5C%5BMatpower%5C%5D+3500+bus+simulation%22o=newest
*
but got the results like-
MATPOWER Version 5.1, 20-Mar-2015 -- AC Optimal Power Flow
MATLAB Interior Point Solver -- MIPS, Version 1.2, 20-Mar-2015
(using built-in linear solver)
itobjective step size feascond gradcond compcond
costcond
-
0 1200199.7 2.41677 0.71 536.762
0
1 946197.39 15.531 1.3682 1.75871 525.914
0.209885
2 954529.91 15.405 0.766107 0.203773 297.341
0.00871422
3 954849.8 12.849 0.7277120.0545952 258.471
0.00033166
4 954629.03 13035 0.69114 0.107402
