Dear pr zemmerman I thank you very much Can you send to me a link to some vedios that explain Most tool as sransmat constitution for a network or other associated files -- Envoyé depuis l'application Yahoo Email App pour Android vendredi, 17 janvier 2020, 11:50PM +01:00 de Ray Daniel Zimmerman r...@cornell.edu :
>Hi Carlos, > >1. You need not use ex_transmat() at all. It was simply a convenience >function used to create the transmat cell array of transmission probability >matrices for each period. You can write your own function to create your own >general cell array of matrices which can certainly vary by period. > >2. From Table 5-3 in the MOST User’s Manual, you’ll see that the 3rd dimension >of the values field of a profile corresponds to the indices specified by the >rows field. In the example rows = 1 and the 3rd dimension of values is a >singleton. If you set rows to a vector, say rows = [1; 3; 4] , then >values(:, :, 1) , then values(:, :, 2) and then values(:, :, 3) would >correspond to the values for wind units 1, 3, and 4 respectively. > >3. I’m not sure I follow the question. In neither case are we optimizing >explicit individual trajectories. We are optimizing the cost of a set of >probability weighted scenarios (and transitions) with certain costs and >constraints on the envelope > of trajectories. > >4. Not exactly. It is actually an approximation of a multi-stage problem, >where the full multi-stage decision tree is approximated with a Markovian >decision process. Reference [5] in > the manual (also ref 5 at https://matpower.org/publications/ ) attempts to > explain this. > >Hope this helps, > > Ray > >[5] A. J. Lamadrid, D. Munoz-Alvarez, C. E. Murillo-Sanchez, R. D. Zimmerman, >H. D. Shin and R. J. Thomas, “Using the MATPOWER Optimal Scheduling Tool to >Test Power System Operation Methodologies Under Uncertainty,” Sustainable >Energy, IEEE Transactions on, > vol. 10, no. 3, pp. 1280–1289, July 2019. DOI: 10.1109/TSTE.2018.2865454 > > >>On Jan 15, 2020, at 11:04 AM, Carlos Ferrandon Cervantes < >>ferrand...@gmail.com> wrote: >>Hello everyone: >> >>I've been working with MOST for some time now; specifically with the unit >>commitment problem. I have been able to add some linearised constraints to >>it, but now I face the challenge of using the stochastic programming option >>in MOST. I've followed >> the example "most_ex7_suc" for these cases: Stochastic Unit Commitment - >> Individual Trajectories and Stochastic Unit Commitment - Full Transition >> Probabilities and my questions are the next ones: >> >>1. I've realised that in the matrix "transmat", only the first column is full >>with the three scenarios' probabilities, but for the rest of the columns we >>have the identity matrix size 3x3 for each time step.Then the >>"scenario_probs" variable is >> computed/updated with the operation: mdi.tstep(t).TransMat * >> mdi.CostWeights(1, 1:mdi.idx.nj(t-1), t-1). My question is: Can these >> scenario probabilities change through time? I mean, that for every column we >> could have different scenario probabilities in >> "transmat". And if this was the case, what changes would be needed for the >> function "ex_transmat" to reflect these changes? >> >>2. For the wind input in the example "most_ex7_suc" we have three different >>values of wind. I am assuming they belong to the three scenarios specified >>but only for that wind input. If we had different wind inputs from different >>buses, what would >> the arrangement of windprofiles.values(:,:,:) be? >> >>3. How can we see the difference betwen the Individual Trajectories and Full >>Transition Probabilities case? I've understood from the manual that the >>system "stays" in one path in the case of Individual Trajectories, but for >>the Full Transition >> Probabilities how can we see the transition between the three scenarios' >> possible paths? >> >>4. Can we that MOST is a Two-Stage model in Full Stochastic Programming then? >> >>Right now Im only working with the full system, i.e. no contingencies. >> >>As usual, thank you so much in advance, >> >>-- >>Carlos Ferrandon
