Dear Zimmerman,
Thanks for your kind response. As i understand, you mean that i should find
spatial correlation/joint distribution of all wind farms and put them in
transition matrix for each time interval. Please correct if i am wrong.

Regards,
Aamir Nawaz

On Tue, Sep 18, 2018 at 1:35 AM, Ray Zimmerman <[email protected]> wrote:

> Well, I confess I don’t follow the intentions of your code, but I think
> you may have some misunderstandings of what we mean by a “scenario” in
> MOST. Think of it as a possible “state” of the system at a particular time
> (not a set of trajectories through time). So to model wind, you will want
> to attempt to model the joint distribution of all of your wind locations as
> a set of probability weighted “scenarios” or states for that moment in time.
>
>     Ray
>
>
> On Sep 14, 2018, at 8:52 AM, Aamir Nawaz <[email protected]> wrote:
>
> Dear all,
> I want to find expected dispatch for IEEE 188 Bus system with 30% Wind
> farms where wind scenrios is nj=400 and for time period nt=12 hours. Please
> help where this code have problem.
>
> define_constants
> mpopt = mpoption('verbose', 0);
> mpc = loadcase(case118);
> nWF=fix(sum(mpc.gen(:,9))*0.3/100);%30% wind farms
> PVbus=find(mpc.bus(:,BUS_TYPE)~=1);
> xgd = loadxgendata(ex_xgd118, mpc);
> for i=1:nWF
>     [iwind(i), mpc, xgd] = addwind(ex_wind_dynmc118, mpc,xgd);
> end
> nt =12;nj=400;
> weibullpdf=wblpdf(0.01:0.01:nj*0.01,1:nj,1);
> transmat = {repmat(weibullpdf,nt,1)};
> profiles = getprofiles(uniformwindprofile(nj, nt), iwind);
> profiles = getprofiles('ex_load_profile118', profiles);
> mdi = loadmd(mpc, transmat, xgd, [], [], profiles);
> mpopt = mpoption('verbose', 0, 'most.dc_model', 1);
> mdo = most(mdi, mpopt);
> EPg = mdo.results.ExpectedDispatch
>
> But its giving expected dispatch for 1 hour only, instead of 12 hours. Can
> you point out my mistake?
>
>
>
>
>
> *Regards,Aamir Nawaz*
>
>
>

Reply via email to