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 R<<X), 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.edu&q=subject:%22Re%5C%3A+%5C%5BMatpower%5C%5D+3500+bus+simulation%22&o=newest >> <https://www.mail-archive.com/search?l=matpower-l@cornell.edu&q=subject:%22Re%5C%3A+%5C%5BMatpower%5C%5D+3500+bus+simulation%22&o=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) >> it objective 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 0.727712 0.0545952 258.471 >> 0.00033166 >> 4 954629.03 13035 0.69114 0.107402 258.048 >> 0.000228815 >> 5 954614.88 33406 0.692682 0.255673 257.828 >> 1.46744e-05 >> 6 954525.69 14111 0.579613 0.143897 256.765 >> 9.24569e-05 >> 7 954539.42 61648 0.581139 0.501345 255.994 >> 1.42362e-05 >> 8 954518.93 22452 0.573652 0.478609 255.465 >> 2.12443e-05 >> 9 954494.92 8540.4 0.556318 0.403754 254.653 >> 2.48944e-05 >> 10 954523.58 20366 0.556265 0.570707 254.104 >> 2.97206e-05 >> 11 954522.07 6142.4 0.554989 0.647881 256.561 >> 1.57288e-06 >> 12 954573.42 6192.9 0.513972 0.716706 253.604 >> 5.32434e-05 >> 13 954575.97 5912.1 0.509457 0.699751 252.612 >> 2.64406e-06 >> 14 954576.23 16534 0.509454 0.674865 253.278 >> 2.64555e-07 >> 15 954579.65 12324 0.509394 0.812237 252.966 >> 3.54362e-06 >> 16 954579.86 7650.3 0.509391 0.80973 252.948 >> 2.18359e-07 >> 17 954579.87 8185.1 0.509391 0.809591 252.947 >> 1.48635e-08 >> 18 954579.88 8696.2 0.509391 0.809411 252.945 >> 1.31087e-08 >> 19 954579.9 9392.5 0.50939 0.80927 252.943 >> 1.3818e-08 >> Numerically Failed >> >> Did not converge in 19 iterations. >> >> >>>>> Did NOT converge (3.71 seconds) <<<<< >> >> 4) But when I used spy(J) , to look jacobian matrix it gives me some >> strange distribution. Herewith I attached image of jacobian matrix. ( I >> have modeled transmission lines and transformers to get one single branch >> matrix e.g. branch_matrix=vertcat(transmission_lines,grid_transformer) >> which is similar to matpower test cases.). So could you please suggest me >> what necessary steps I should follow? >> Thank you for your time. >> >> Regards >> Mirish Thakur >> KIT, University. >> >> On Mon, Aug 10, 2015 at 7:14 PM, Abhyankar, Shrirang G. <abhy...@anl.gov> >> wrote: >> >>> I would suggest trying the following: >>> >>> >>> 1. Use the solution of a fast decoupled power flow or an optimal >>> power flow (with line limits and voltage limits relaxed) as the initial >>> guess for the power flow. >>> 2. Follow step 5 in >>> http://www.pserc.cornell.edu/matpower/#pfconvergence making CPF to >>> stop when the nose-point is reached. This can be done via results = >>> runcpf(mpcbase,mpctarget,mpoption(‘cpf.stop_at’,’NOSE’)). If >>> results.cpf.max_lam is >= 1, then it shows that the initial guess for the >>> power flow is the problem for its divergence. To obtain a ‘good’ initial >>> guess, run the continuation power flow again making it to stop exactly at >>> lam = 1 (the target case loading and generation) via results = >>> runcpf(mpcbase,mpctarget,mpoption(‘cpf.stop_at’,1.0)). You can then save >>> the results struct as a matpower case file (via savecase()). On the other >>> hand, if results.cpf.max_lam < 1, then the loading/generation in your >>> original case is beyond the system steady-state loading limit. >>> >>> Shri >>> From: Mirish Thakur <mirishtha...@gmail.com> >>> Reply-To: MATPOWER discussion forum <matpowe...@list.cornell.edu> >>> Date: Monday, August 10, 2015 at 10:44 AM >>> To: MATPOWER discussion forum <matpowe...@list.cornell.edu> >>> Subject: convergence problem in runpf. >>> >>> Dear Matpower Community, >>> >>> >>> I’m working on power flow project and have used grid data from database. >>> I have modelled all line parameters (R X B) in p.u. system, also same for >>> transformers and kept generator output until it satisfies active and >>> reactive power demand. For renewable generation, I specified as negative >>> demand on respective buses. I checked all possibilities mentioned in FAQ ( >>> http://www.pserc.cornell.edu/matpower/#pfconvergence ) but couldn’t >>> figure out problem. Also I checked (case_info) to see any island but got >>> full system without island. To make the problem simple I used all buses as >>> PQ buses except one slack bus. Also my casefile converges for rundcpf but >>> fails to runpf and gives error like ‘Newton's method power flow did not >>> converge in 10 iterations.’ Also I found that when I use following code- >>> >>> >>> opt = mpoption('OUT_BUS', 0, 'OUT_BRANCH', 0, 'VERBOSE', 2); >>> >>> mpc = loadcase('casefile'); >>> >>> results =runpf(mpc,opt); >>> >>> >>> may be it gives me divergence of PQ mismatch instead of convergence. >>> >>> >>> MATPOWER Version 5.1, 20-Mar-2015 -- AC Power Flow (Newton) >>> >>> >>> >>> it max P & Q mismatch (p.u.) >>> >>> ---- --------------------------- >>> >>> 0 2.296e+01 >>> >>> 1 1.729e+01 >>> >>> 2 2.450e+03 >>> >>> 3 2.352e+03 >>> >>> 4 6.962e+06 >>> >>> 5 1.740e+06 >>> >>> 6 4.352e+05 >>> >>> 7 1.753e+07 >>> >>> 8 4.382e+06 >>> >>> 9 3.322e+06 >>> >>> 10 8.303e+05 >>> >>> Newton's method power flow did not converge in 10 iterations. >>> >>> >>> >>> >>>>> Did NOT converge (0.23 seconds) <<<<< >>> >>> >>> >>> >>> >>> results = >>> >>> version: '2' >>> >>> baseMVA: 100 >>> >>> bus: [1086x13 double] >>> >>> gen: [467x21 double] >>> >>> branch: [2145x17 double] >>> >>> order: [1x1 struct] >>> >>> et: 0.2320 >>> >>> success: 0 >>> >>> I will be very thankful for your help. >>> >>> >>> Regards >>> >>> Mirish Thakur. >>> >>> KIT, University. >>> >>> >> >