My code just sets up the AC OPF problem as an NLP, then sends that to ipopt for 
optimization. I have tried tightening and relaxing ipopt's various tolerances, 
with no noticeable change in the output.

Thanks,
~Zev Friedman
________________________________
From: [email protected] 
[[email protected]] on behalf of Ray Zimmerman 
[[email protected]]
Sent: Wednesday, July 06, 2011 3:11 PM
To: MATPOWER discussion forum
Subject: Re: AC Modelling

Presumably your code also uses some iterative algorithm with some termination 
tolerance to determine what is "close enough". My guess is that your 
termination criterion needs to be tighter if you want a closer match.

By decreasing the termination tolerances , you should be able to make them as 
close as you like up to the point where you are limited by the precision of the 
calculations themselves.

--
Ray Zimmerman
Senior Research Associate
211 Warren Hall, Cornell University, Ithaca, NY 14853
phone: (607) 255-9645



On Jul 6, 2011, at 1:42 PM, Friedman, Zev Benjamin wrote:

Hello again,

I am still working on writing an AC OPF/Economic Dispatch model, using Matpower 
as a baseline, and I am getting some strange discrepancies between the two. I 
wrote a little checkpf function (using the mismatch check algorithms from 
Matpower's Newton power flow implementation) to compare my answers (which I 
have outputting in Matpower case format to make that easier), and I was hoping 
someone could help me make sense of that data.

The L-infinity norm of the mismatch ( maxerr=norm( V.*conj(Ybus*V) - Sbus, inf) 
) for my model is consistently much higher than Matpower's (on the order of 10x 
even on some of the simplest cases).

For example, on case9.m, I removed the line charging susceptance, Bc, by 
setting that column to 0 and using runopf in Matpower, then comparing the 
results to my model. Despite the fact that the maximum differences between real 
and reactive power and complex voltage at each bus is small (Pg_maxdiff=4.7e-4, 
Qg_maxdiff=5.82e-4, V_maxdiff=1.98e-6, Vangle_maxdiff=5.36e-7), for my model, 
maxerr=2.26e-5, but Matpower has maxerr=5.04e-6: a difference of a factor of 4. 
Is that reasonable to chalk up to noise in my calculations and conversions, or 
is that an unacceptably high error difference?

When line charging is included on case9.m (Using Bc/2=half of the value given 
in the case file, as that says it is the full line charging susceptance), I 
have maxerr=1.60e-5 and Matpower has maxerr=3.44e-6. So both models give lower 
max error, and Pg_maxdiff, V_maxdiff, Vangle_maxdiff are all close to the same 
order as without line charging (actually, Vangle_maxerr=0 in this case), but 
Qg_maxdiff=2.69e-2, which is several orders of magnitude larger than the other 
mismatches. Is this a result of small voltage differences and rounding error in 
conversions propagating, magnified by the inclusion of the Bc/2 term?

I have checked my equations numerous times, ensuring that my derivations are 
correct, so I am at a loss for what is causing this strangeness. Case9.m has no 
shunts or transformers, so the error isn't from those elements. Am I missing 
something fundamental about line charging susceptance? Even in the simplified 
case, what could be causing the large discrepancy between maxerr values?

Thanks again for your help,
~Zev Friedman

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