date:20170530

Re: question about co-simulation

2017-05-30 Thread Ray Zimmerman

What I would recommend is making a slight modification to newtonpf.m 
, 
where you insert at line 102 a call to a function defined by you, to which you 
pass the complex bus voltage vector V and anything else you need (e.g. Ybus, 
Sbus, etc.).  Inside that function you do whatever you need to to interface 
with OpenDSS.

Ray

> On May 29, 2017, at 11:31 PM, Jose Hector Vivas Navas  wrote:
> 
> Dear users, 
> 
> I have interest in perform a transmission (Matpower) - distribution (OpenDSS) 
> load flow by means of co-simulation. Is there anybody who knows how can I 
> access to each iteration of Matpower?
> 
> Thanks in advance.
> 
> Jose Vivas
> 
> École de Technologie Supérieure
> Montréal, Canada

Re: CPF - converted generator buses have 0 QG

2017-05-30 Thread Ray Zimmerman

Any chance this is a duplicate of issue #12 
? If so, it should be fixed in 
the current version on GitHub. If not, could you please submit a new issue 
 with a minimum working example 
(MWE) that I can use to reproduce the issue and look into it?

Thanks,

Ray
 


> On May 29, 2017, at 11:06 AM, Elis Nycander  wrote:
> 
> Hi,
> 
> I'm running a cpf. In the base case there are some generators which are at 
> their maximum generation limit, so these are converted to PQ buses in the 
> base case pf. Then, on row 272 and 284 in runcpf, the QG for these buses 
> becomes 0 since they are not updated like the other generator buses. So 
> instead of the generator being a PQ bus with Pmax, Qmax, I get a PQ bus with 
> Pmax, 0. Is it supposed to be like this or is it a bug? 
> 
> I tried changing the code but couldn't see any big difference in my case. 
> 
> Help is kindly appreciated,
> Elis

Re: α and β of each transmission line

2017-05-30 Thread Ray Zimmerman

The model used for the transmission line shown in Figure 3-1 in the User’s 
Manual. I’m not sure what you mean by the α and β of the transmission line. 
What do these parameters refer to?

   Ray



> On May 28, 2017, at 10:04 PM, Ameeratul Balqis  
> wrote:
> 
> Hello and good day,
> 
> I have been using command of 'runpf(casedata)' in MATPOWER in order to get 
> the power flow of the system case. However, I realized that the result did 
> not include the α and β of each transmission line. 
> 
> 1.How can I get the α and β of each transmission line? What command should I 
> use?
> 2.What is the .m file in order for me to able to learn more or edit the 
> equation of the α and β in the lines. 
> 
> I'm new in using MATPOWER so I hope I would get help and guidance regarding 
> the above problem I've stated.
> 
> Thank you

Re: How to indicate in MATPOWER the use of several substations in the cases of radial distribution systems?

2017-05-30 Thread Ray Zimmerman

I’m not sure I understand what you mean by a radial system with more than one 
substation. You definitely don’t want to set multiple buses of type REF, though 
you could use type PV for all but one of the substations, but that is 
equivalent to turning a radial system into a meshed system.

Ray


> On May 26, 2017, at 10:27 AM, Andrey Vieira  wrote:
> 
> Hi All! I have a question about the use of several substation bars in the 
> case of radial distribution systems with more than one substation.
> Examples:
>   A) Case 16 buses : it has 3 substations;
>   B) Case 135 buses: it has 2 substations;
>   C) Case 84 buses : it has 11 substations.
>
> In the case of 84 buses, for example, can I identify all substation buses 
> with different numberings and indicate that all 11 buses are of 
> type 3 in the mpc.bus matrix? Instead of numbering all 11 with the same 
> number (1 for exemplo)?
> 
> Can anybody advice on representation these sources in MATPOWER?
> 
> Andrey R Vieira

Re: Different results at repeated execution

2017-05-30 Thread Teiji Ponishi

Dear Olaf and Jean,

I am sorry for my insufficient information on this issue.

Actually, as I am not a expert on these software, it is difficult for me to
resolve it immediately.

First of all, I will try to resolve it by using knitro based on your paper
and knitro manual.

If it is difficult, I will try to change the solver to IPOPT/PARDISO with
parallel bitwise reproducible functionality.

Thank you very much for your valuable comments.

best regards,

Teiji

2017-05-30 19:54 GMT+09:00 MAEGHT Jean :

> Dear Olaf,
> I don't agree with your analysis. The results shown by Teiji are
> deterministic. He made 2 series of 3 runs and the 2 series are identical.
> Jean
>
> >> But, after MATLAB was restarted, the same values of objective
> >> function can be obtained.
> >> 1st 8740.2
> >> 2nd8731.9
> >> 3rd 8728.3
> >> < MATLAB is shutdown and restarted >
> >> 4th 8740.2
> >> 5th 8731.9
> >> 6th 8728.3
>
> -Message d'origine-
> De : bounce-121567438-75398...@list.cornell.edu [mailto:bounce-121567438-
> 75398...@list.cornell.edu] De la part de Olaf Schenk
> Envoyé : mardi 30 mai 2017 11:57
> À : MATPOWER discussion forum 
> Objet : Re: Different results at repeated execution
>
> Dear Jean,
>
> I think that Teiji is referring to the problem that if you use the
> multiple-threaded version of KNITRO you will have different solutions even
> in the case of using the same initial starting point.
>
> Regards,
> Olaf
>
>
>
>
>
> On 30.05.2017 11:50, MAEGHT Jean wrote:
> > Dear Teiji,
> > Knitro is using interior point methods.
> > Interior point method are known to have bad properties regarding initial
> point (=if you start an interior point solver with an initial point which
> is already an optimal point, the solver will not figure it out and may even
> behave worse than starting from a dummy initial point).
> > But still, many times if you have a good guess or a good initial point,
> the solver may behave better.
> > When you run your series of OPFs, the result is used as initial point
> for the next OPF. This may explain different behavior of the solver.
> >
> > Implicit question: why are optimal values different?
> > 1/ as OPF is a non convex problem, you only get a local minimum, so
> > maybe you don't have the same local minimum each time 2/ stopping
> criteria are using tolerances; maybe within the tolerances you used, there
> are several solutions.
> >
> > For fine tuning of Knitro, you can see how we did in this paper:
> > https://arxiv.org/abs/1603.01533
> > page 4, section V.A.
> >
> > knitro matlab documentation:
> > https://www.artelys.com/tools/knitro_doc/3_referenceManual/knitromatla
> > bReference.html
> >
> > If you force V and theta to zero in your case before each run, you
> wshould always get the same result.
> >
> > Best regards,
> > --
> > Jean Maeght
> > RTE - R&D Division
> >
> >
> >
> > -Message d'origine-
> > De : bounce-121566163-75398...@list.cornell.edu
> > [mailto:bounce-121566163-75398...@list.cornell.edu] De la part de Olaf
> > Schenk Envoyé : lundi 29 mai 2017 09:51 À : MATPOWER discussion forum
> > ; Drosos Kourounis ;
> > Kardoš Juraj  Objet : Re: Different results at
> > repeated execution
> >
> > Hi Teiji,
> >
> > I suggest to use an optimizer that has parallel bitwise reproducible
> functionality.
> >
> > KNITRO is not able to give you identical results, but the
> > IPOPT/PARDISO
> > 5.0 binaries offers this functionality. You can it use the binaries
> > under "Matpower Libraries" on
> >
> > http://www.pardiso-project.org/#download
> >
> > Best,
> >
> > Olaf Schenk
> >
> >
> > On 27.05.2017 13:12, Teiji Ponishi wrote:
> >> Hi all,
> >>
> >> I use MATPOWER 5.1, and  knitro as a optimization solver.
> >>
> >> When I run the MATPOWER repeatedly, the values of objective function
> >> can be slightly reduced as follows:
> >>
> >> 1st 8740.2
> >> 2nd8731.9
> >> 3rd 8728.3
> >>
> >> But, after MATLAB was restarted, the same values of objective
> >> function can be obtained.
> >>
> >> 1st 8740.2
> >> 2nd8731.9
> >> 3rd 8728.3
> >> < MATLAB is shutdown and restarted >
> >> 4th 8740.2
> >> 5th 8731.9
> >> 6th 8728.3
> >>
> >> How do I obtain same results of MATPOWER without restarting MATLAB ?
> >>
> >> Best,
> >>
> >> Teiji
> > --
> > Prof. Dr. Olaf Schenk
> > Advanced Computing Laboratory
> > Institute of Computational Science
> > Università della Svizzera italiana **  Switzerland
> > Via Giuseppe Buffi 13  **  6900 Lugano
> > Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
> > Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch
> >
> >
> >
> >
> > "Ce message est destiné exclusivement aux personnes ou entités
> auxquelles il est adressé et peut contenir des informations privilégiées ou
> confidentielles. Si vous avez reçu ce document par erreur, merci de nous
> l'indiquer par retour, de ne pas le transmettre et de procéder à sa
> destruction.
> >
> > This mes

RE: Different results at repeated execution

2017-05-30 Thread MAEGHT Jean

Dear Olaf,
I don't agree with your analysis. The results shown by Teiji are deterministic. 
He made 2 series of 3 runs and the 2 series are identical.
Jean

>> But, after MATLAB was restarted, the same values of objective
>> function can be obtained.
>> 1st 8740.2
>> 2nd8731.9
>> 3rd 8728.3
>> < MATLAB is shutdown and restarted >
>> 4th 8740.2
>> 5th 8731.9
>> 6th 8728.3

-Message d'origine-
De : bounce-121567438-75398...@list.cornell.edu 
[mailto:bounce-121567438-75398...@list.cornell.edu] De la part de Olaf Schenk
Envoyé : mardi 30 mai 2017 11:57
À : MATPOWER discussion forum 
Objet : Re: Different results at repeated execution

Dear Jean,

I think that Teiji is referring to the problem that if you use the 
multiple-threaded version of KNITRO you will have different solutions even in 
the case of using the same initial starting point.

Regards,
Olaf





On 30.05.2017 11:50, MAEGHT Jean wrote:
> Dear Teiji,
> Knitro is using interior point methods.
> Interior point method are known to have bad properties regarding initial 
> point (=if you start an interior point solver with an initial point which is 
> already an optimal point, the solver will not figure it out and may even 
> behave worse than starting from a dummy initial point).
> But still, many times if you have a good guess or a good initial point, the 
> solver may behave better.
> When you run your series of OPFs, the result is used as initial point for the 
> next OPF. This may explain different behavior of the solver.
>
> Implicit question: why are optimal values different?
> 1/ as OPF is a non convex problem, you only get a local minimum, so
> maybe you don't have the same local minimum each time 2/ stopping criteria 
> are using tolerances; maybe within the tolerances you used, there are several 
> solutions.
>
> For fine tuning of Knitro, you can see how we did in this paper:
> https://arxiv.org/abs/1603.01533
> page 4, section V.A.
>
> knitro matlab documentation:
> https://www.artelys.com/tools/knitro_doc/3_referenceManual/knitromatla
> bReference.html
>
> If you force V and theta to zero in your case before each run, you wshould 
> always get the same result.
>
> Best regards,
> --
> Jean Maeght
> RTE - R&D Division
>
>
>
> -Message d'origine-
> De : bounce-121566163-75398...@list.cornell.edu
> [mailto:bounce-121566163-75398...@list.cornell.edu] De la part de Olaf
> Schenk Envoyé : lundi 29 mai 2017 09:51 À : MATPOWER discussion forum
> ; Drosos Kourounis ;
> Kardoš Juraj  Objet : Re: Different results at
> repeated execution
>
> Hi Teiji,
>
> I suggest to use an optimizer that has parallel bitwise reproducible 
> functionality.
>
> KNITRO is not able to give you identical results, but the
> IPOPT/PARDISO
> 5.0 binaries offers this functionality. You can it use the binaries
> under "Matpower Libraries" on
>
> http://www.pardiso-project.org/#download
>
> Best,
>
> Olaf Schenk
>
>
> On 27.05.2017 13:12, Teiji Ponishi wrote:
>> Hi all,
>>
>> I use MATPOWER 5.1, and  knitro as a optimization solver.
>>
>> When I run the MATPOWER repeatedly, the values of objective function
>> can be slightly reduced as follows:
>>
>> 1st 8740.2
>> 2nd8731.9
>> 3rd 8728.3
>>
>> But, after MATLAB was restarted, the same values of objective
>> function can be obtained.
>>
>> 1st 8740.2
>> 2nd8731.9
>> 3rd 8728.3
>> < MATLAB is shutdown and restarted >
>> 4th 8740.2
>> 5th 8731.9
>> 6th 8728.3
>>
>> How do I obtain same results of MATPOWER without restarting MATLAB ?
>>
>> Best,
>>
>> Teiji
> --
> Prof. Dr. Olaf Schenk
> Advanced Computing Laboratory
> Institute of Computational Science
> Università della Svizzera italiana **  Switzerland
> Via Giuseppe Buffi 13  **  6900 Lugano
> Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
> Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch
>
>
>
>
> "Ce message est destiné exclusivement aux personnes ou entités auxquelles il 
> est adressé et peut contenir des informations privilégiées ou 
> confidentielles. Si vous avez reçu ce document par erreur, merci de nous 
> l'indiquer par retour, de ne pas le transmettre et de procéder à sa 
> destruction.
>
> This message is solely intended for the use of the individual or entity to 
> which it is addressed and may contain information that is privileged or 
> confidential. If you have received this communication by error, please notify 
> us immediately by electronic mail, do not disclose it and delete the original 
> message."

--
Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana **  Switzerland
Via Giuseppe Buffi 13  **  6900 Lugano
Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch




"Ce message est destiné exclusivement aux personnes ou entités auxquelles il 
est a

Re: Different results at repeated execution

2017-05-30 Thread Olaf Schenk


Dear Jean,

I think that Teiji is referring to the problem that if you use the 
multiple-threaded version of KNITRO you will have different solutions 
even in the case of using the same initial starting point.


Regards,
Olaf





On 30.05.2017 11:50, MAEGHT Jean wrote:

Dear Teiji,
Knitro is using interior point methods.
Interior point method are known to have bad properties regarding initial point 
(=if you start an interior point solver with an initial point which is already 
an optimal point, the solver will not figure it out and may even behave worse 
than starting from a dummy initial point).
But still, many times if you have a good guess or a good initial point, the 
solver may behave better.
When you run your series of OPFs, the result is used as initial point for the 
next OPF. This may explain different behavior of the solver.

Implicit question: why are optimal values different?
1/ as OPF is a non convex problem, you only get a local minimum, so maybe you 
don't have the same local minimum each time
2/ stopping criteria are using tolerances; maybe within the tolerances you 
used, there are several solutions.

For fine tuning of Knitro, you can see how we did in this paper:
https://arxiv.org/abs/1603.01533
page 4, section V.A.

knitro matlab documentation:
https://www.artelys.com/tools/knitro_doc/3_referenceManual/knitromatlabReference.html

If you force V and theta to zero in your case before each run, you wshould 
always get the same result.

Best regards,
--
Jean Maeght
RTE - R&D Division



-Message d'origine-
De : bounce-121566163-75398...@list.cornell.edu 
[mailto:bounce-121566163-75398...@list.cornell.edu] De la part de Olaf Schenk
Envoyé : lundi 29 mai 2017 09:51
À : MATPOWER discussion forum ; Drosos Kourounis 
; Kardoš Juraj 
Objet : Re: Different results at repeated execution

Hi Teiji,

I suggest to use an optimizer that has parallel bitwise reproducible 
functionality.

KNITRO is not able to give you identical results, but the IPOPT/PARDISO
5.0 binaries offers this functionality. You can it use the binaries under "Matpower 
Libraries" on

http://www.pardiso-project.org/#download

Best,

Olaf Schenk


On 27.05.2017 13:12, Teiji Ponishi wrote:

Hi all,

I use MATPOWER 5.1, and  knitro as a optimization solver.

When I run the MATPOWER repeatedly, the values of objective function
can be slightly reduced as follows:

1st 8740.2
2nd8731.9
3rd 8728.3

But, after MATLAB was restarted, the same values of objective function
can be obtained.

1st 8740.2
2nd8731.9
3rd 8728.3
< MATLAB is shutdown and restarted >
4th 8740.2
5th 8731.9
6th 8728.3

How do I obtain same results of MATPOWER without restarting MATLAB ?

Best,

Teiji

--
Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana **  Switzerland
Via Giuseppe Buffi 13  **  6900 Lugano
Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch




"Ce message est destiné exclusivement aux personnes ou entités auxquelles il 
est adressé et peut contenir des informations privilégiées ou confidentielles. Si 
vous avez reçu ce document par erreur, merci de nous l'indiquer par retour, de ne 
pas le transmettre et de procéder à sa destruction.

This message is solely intended for the use of the individual or entity to which it 
is addressed and may contain information that is privileged or confidential. If you 
have received this communication by error, please notify us immediately by 
electronic mail, do not disclose it and delete the original message."


--
Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana **  Switzerland
Via Giuseppe Buffi 13  **  6900 Lugano
Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch

RE: Different results at repeated execution

2017-05-30 Thread MAEGHT Jean

Dear Teiji,
Knitro is using interior point methods.
Interior point method are known to have bad properties regarding initial point 
(=if you start an interior point solver with an initial point which is already 
an optimal point, the solver will not figure it out and may even behave worse 
than starting from a dummy initial point).
But still, many times if you have a good guess or a good initial point, the 
solver may behave better.
When you run your series of OPFs, the result is used as initial point for the 
next OPF. This may explain different behavior of the solver.

Implicit question: why are optimal values different?
1/ as OPF is a non convex problem, you only get a local minimum, so maybe you 
don't have the same local minimum each time
2/ stopping criteria are using tolerances; maybe within the tolerances you 
used, there are several solutions.

For fine tuning of Knitro, you can see how we did in this paper:
https://arxiv.org/abs/1603.01533
page 4, section V.A.

knitro matlab documentation:
https://www.artelys.com/tools/knitro_doc/3_referenceManual/knitromatlabReference.html

If you force V and theta to zero in your case before each run, you wshould 
always get the same result.

Best regards,
--
Jean Maeght
RTE - R&D Division

-Message d'origine-
De : bounce-121566163-75398...@list.cornell.edu 
[mailto:bounce-121566163-75398...@list.cornell.edu] De la part de Olaf Schenk
Envoyé : lundi 29 mai 2017 09:51
À : MATPOWER discussion forum ; Drosos Kourounis 
; Kardoš Juraj 
Objet : Re: Different results at repeated execution

Hi Teiji,

I suggest to use an optimizer that has parallel bitwise reproducible 
functionality.

KNITRO is not able to give you identical results, but the IPOPT/PARDISO
5.0 binaries offers this functionality. You can it use the binaries under 
"Matpower Libraries" on

http://www.pardiso-project.org/#download

Best,

Olaf Schenk

On 27.05.2017 13:12, Teiji Ponishi wrote:
> Hi all,
>
> I use MATPOWER 5.1, and  knitro as a optimization solver.
>
> When I run the MATPOWER repeatedly, the values of objective function
> can be slightly reduced as follows:
>
> 1st 8740.2
> 2nd8731.9
> 3rd 8728.3
>
> But, after MATLAB was restarted, the same values of objective function
> can be obtained.
>
> 1st 8740.2
> 2nd8731.9
> 3rd 8728.3
> < MATLAB is shutdown and restarted >
> 4th 8740.2
> 5th 8731.9
> 6th 8728.3
>
> How do I obtain same results of MATPOWER without restarting MATLAB ?
>
> Best,
>
> Teiji

--
Prof. Dr. Olaf Schenk
Advanced Computing Laboratory
Institute of Computational Science
Università della Svizzera italiana **  Switzerland
Via Giuseppe Buffi 13  **  6900 Lugano
Phone: +41 (0) 79 368 22 81**  Fax.: +41 (0)58 666 45 36
Email: olaf.sch...@usi.ch  **  http://www.ics.inf.usi.ch

"Ce message est destiné exclusivement aux personnes ou entités auxquelles il 
est adressé et peut contenir des informations privilégiées ou confidentielles. 
Si vous avez reçu ce document par erreur, merci de nous l'indiquer par retour, 
de ne pas le transmettre et de procéder à sa destruction.

This message is solely intended for the use of the individual or entity to 
which it is addressed and may contain information that is privileged or 
confidential. If you have received this communication by error, please notify 
us immediately by electronic mail, do not disclose it and delete the original 
message."

Re: question about co-simulation

Re: CPF - converted generator buses have 0 QG

Re: α and β of each transmission line

Re: How to indicate in MATPOWER the use of several substations in the cases of radial distribution systems?

Re: Different results at repeated execution

RE: Different results at repeated execution

Re: Different results at repeated execution

RE: Different results at repeated execution

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