Unfortunately, I can’t say anything about the divergence of the power flow by looking at the Jacobian spy plot. The Jacobian spy plot looks fine to me based on how the equations and variables are ordered for MATPOWER’s power flow. Please send me the test case (offline) and I’ll try to debug further.
Shri You could also try to check whether your case is insolvable http://www.pserc.cornell.edu/Matpower/docs/ref/matpower5.1/extras/sdp_pf/insolvablepfsos.html From: Mirish Thakur <mirishtha...@gmail.com<mailto:mirishtha...@gmail.com>> Reply-To: MATPOWER discussion forum <matpowe...@list.cornell.edu<mailto:matpowe...@list.cornell.edu>> Date: Tuesday, August 11, 2015 at 7:36 PM To: MATPOWER discussion forum <matpowe...@list.cornell.edu<mailto:matpowe...@list.cornell.edu>> Subject: Re: convergence problem in runpf. 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 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<mailto: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<mailto:mirishtha...@gmail.com>> Reply-To: MATPOWER discussion forum <matpowe...@list.cornell.edu<mailto:matpowe...@list.cornell.edu>> Date: Monday, August 10, 2015 at 10:44 AM To: MATPOWER discussion forum <matpowe...@list.cornell.edu<mailto: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.
