Hi Victor and Ray, You are right, the problem is because of the initial point in the MIPS algorithm. I tried to change the solver (using MOSEK), and it helped in some cases. In the case of the transmission expansión planning (TEP) problem, I think that this issue did not interfere the evolutionary process most of the time, so I could get the optimal solution in most of the test cases. However, I think that if the convergence issue is solved, maybe the evolutionary algorithm would be more efficient.
Regards, Santiago 2013/9/13 Victor Hugo Hinojosa M. <[email protected]> > 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 didn’t 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 don’t 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. I’ve 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 doesn’t 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 doesn’t 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 doesn’t converge in 42 016 times (2.37%). I > attached an excel file where it’s possible to figure out the initial points > that the MIPS algorithm doesn’t converge considering 4 intervals. In the > row 339, it’s 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 I’d like to study again the problem. **** > > I hope your comments and ideas about the analysis carried out.**** > > Regards,**** > > Víctor**** > > ** ** > > ** ** > > *De:* [email protected] [mailto: > [email protected]] *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 <[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/ > > Albert Einstein, 400 > 13083-852, Campinas, SP, Brazil**** > > ** ** > -- Dr.-Ing. Santiago Torres IEEE Senior Member Power Systems Researcher
