Hello, This test case was published in this paper, were indications on how to solve it with matpower are given. Looking into the zip file on arxiv web site, you will also find some matlab code to run opfs, using Knitro.
https://arxiv.org/abs/1603.01533 .tar.gz file : https://arxiv.org/e-print/1603.01533 AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE Cédric Josz<https://arxiv.org/search/math?searchtype=author&query=Josz%2C+C>, Stéphane Fliscounakis<https://arxiv.org/search/math?searchtype=author&query=Fliscounakis%2C+S>, Jean Maeght<https://arxiv.org/search/math?searchtype=author&query=Maeght%2C+J>, Patrick Panciatici<https://arxiv.org/search/math?searchtype=author&query=Panciatici%2C+P> (Submitted on 4 Mar 2016 (v1<https://arxiv.org/abs/1603.01533v1>), last revised 30 Mar 2016 (this version, v3)) In this paper, we publish nine new test cases in MATPOWER format. Four test cases are French very high-voltage grid generated by the offline plateform of iTesla: part of the data was sampled. Four test cases are RTE snapshots of the full French very high-voltage and high-voltage grid that come from French SCADAs via the Convergence software. The ninth and largest test case is a pan-European ficticious data set that stems from the PEGASE project. It complements the four PEGASE test cases that we previously published in MATPOWER version 5.1 in March 2015. We also provide a MATLAB code to transform the data into standard mathematical optimization format. Computational results confirming the validity of the data are presented in this paper. Best regards, [logo] Jean MAEGHT RTE – R&D Division PES - Direction de la R&D T+33 658 248 320 jean.mae...@rte-france.com<mailto:jean.mae...@rte-france.com> De : bounce-123756981-75398...@list.cornell.edu [mailto:bounce-123756981-75398...@list.cornell.edu] De la part de Aamir Nawaz Envoyé : jeudi 18 juillet 2019 17:59 À : matpower-l@cornell.edu Objet : case13659pegase Dear Researchers, I have tried to execute the following and error comes. Can anyone explain why algorithm like PDIPM fails to solve this large system? However, i have solved it using evolutionary algorithm and it is converged. Is there any limit of number of dimensions for PDIPM or others? If no, then suggest me how i can solve it or suggest any other algorithm like SDPOPF etc. I waiting for your kind reply. runopf(case13659pegase) MATPOWER Version 6.0, 16-Dec-2016 -- AC Optimal Power Flow PDIPMOPF Version 4.1, Build 18, 11-Nov-2011 Copyright (c) 2007-2011 by Power System Engineering Research Center (PSERC) >>>>> Did NOT converge (4.42 seconds) <<<<< -- Regards, Aamir Nawaz. "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."
