Dear Dr Zimmerman and to whomever is reading this,
due to sending it first to the wrong address, i already got an answer
from DR. Zimmermann, but i have additional questions(so you might want
to start at the first mail a little bit down here)
My additional Questions:
1: The thing is, that these tight limit will occur in my Project
sometimes and in the post process some matlab code will decide whether
to build new/enlarge existing Branches or keep them the way they are.
(And after that starting at the beginning with small changes in power
production and demand. And this for about 20 times. And all this
together about different strategies and a lot of different scenarios)
And for this i need to ensure that even in tight cases i can get
feasible result. Supply shortage is a possible result for me.
I want to calculates how much maximal unmet demand i have and which
strategy give me the least unmet demand over the most scenarios
and In my opinion one possible result of my given case could be
:
Generation(Bus 1: 300MW, Bus4: 100MW)
Branch Date
From 1 to 2: 100MW
From 1 to 3: 150MW
From 2 to 4: -100MW
From 3 to 4: 50MW
So does anybody see a potential solution to this problem with Matpower
Thank you all for your time
regards,
christian Stiller
Am 17.04.2014 15:15, schrieb Ray Zimmerman:
/(Btw, this kind of question should be addressed to
[email protected] <mailto:[email protected]>, not
[email protected] <mailto:[email protected]>)./
/
/
Two things …
1. It appears that your problem is infeasible. Try increasing the
limit on the first branch to 150 or above and it should solve just
fine. You may want to recheck the simple, clean solution you got on paper.
2. When the OPF is unsuccessful, the numerical values of any of the
results are typically meaningless.
--
Ray Zimmerman
Senior Research Associate
B30 Warren Hall, Cornell University, Ithaca, NY 14853
phone: (607) 255-9645
On Apr 17, 2014, at 8:51 AM, Christian Stiller
<[email protected]
<mailto:[email protected]>> wrote:
Dear Dr Zimmerman and to whomever is reading this,
*The Short Version of my Problem:*
I have a simple, reduced to the minimum, 4 bus dc opf case where i
want to get the maximum possible power flow while the given limits
are never violated. The model of the grid is a very very very reduced
one. Only the transmission capacity is given for the edges and on the
nodes the real power demand and the maximum real power output. Not More!
/
My Problem/is , that if the production capacity or the transmission
line capacity comes to the limit, matpower gives me very strange
results (and especially these "thight" cases are the interessting
ones for my project and will occure sometimes). It says that it did
NOT converge and "exiting, one ore more variables have grown more
than 100000times" . So for example in the Results i can find
exploding cost or nearly no generation but extreme transmission. the
results make no sense at all, on paper the problem has a very simple
and clean solution.
so if you could help me, maybe somebody knows an answer (not possible
would be an answer too)
I tried using mosek to solve that case but it gave me onyly zero's as
result
Matlab 2012b and the newest matpower (4.1)
regards and thank you for your Time,
Christian Stiller
*A more detailed Version of my Case an Problem with the m file attached*
/My Case/
In my Beachlor Thesis I want to demonstrate the method of Robust
Decision Making at the example of the planning of the powergrid.
(like: where should we build new lines in an existing grind so that
the system is robust in future uncertain scenarios).
The model of the grid is a very very very reduced one. Only the
transmission capacity is given for the edges and on the nodes the
real power demand and the maximum real power output.
For that Methode I need to test a set of different strategies on a
large set of possible uncertain scenarios(power generation and
consumption are uncertain in and given range), to find that strategie
which gives a good performance(cost or max unmet power) over the most
scenarios. And in each scenario I have to calculate for each
strategie for each year(till2030) if there is a need to build new
transmission lines. (There are also Reserve Power and dispatchable
loads with specific costs given, but first I wanted to get the simple
Version workingand calculate the reserve and disp. Loads after the
transmission) )
So I need to calculate the maximum possible Flow given a certain
Network in which no limits (edge capacity and generator output) are
violated! For that (because of the limits)only OptimalpowerFlow works
in Matpower, so I have to set the generation cost to something. So I
use “rundcopf(‘’)”. The generation cost is set to the same value on
all generators and all edges have the same resistance.
The goal is to find the edges which are at limit to know where to
invest in new lines.
/My Problem/is now, that if the production capacity or the
transmission capacity comes to the limit, matpower gives me very
strange results (and that case will happen sometimes). From exploding
cost,to nearly no generation but extreme transmission, the results
make no sense at all, on paper the problem has a very simple and
clean solution.
(I also tried working with dispatchable loads, but even when no
dispatchable loads where theoretically needed, matpower dispatched
some part of the loads. Which I think has to to with the costs given
for production and dispatching
My opinion is, that Matpower has problems finding a solution because
of this very simple case and the given very strict limits. (Even
setting different resistances (x) in the branch date or/and setting
different generation costs doesn’t change the strange results.)
RDM.m
function mpc = case4gs
%CASE4GS Power flow data for 4 bus, 2 gen case from Grainger & Stevenson.
% Please see CASEFORMAT for details on the case file format.
%
% This is the 4 bus example from pp. 337-338 of "Power System Analysis",
% by John Grainger, Jr., William Stevenson, McGraw-Hill, 1994.
% MATPOWER
% $Id: case4gs.m,v 1.4 2010/03/10 18:08:14 ray Exp $
%% MATPOWER Case Format : Version 2
mpc.version = '2';
%%----- Power Flow Data -----%%
%% system MVA base
mpc.baseMVA = 100;
%% bus data
% bus_i type Pd Qd Gs Bs area Vm Va
baseKV zone Vmax Vmin
mpc.bus = [
1 3 50 0 0 0 1 1 0
230 1 1.1 0.9;
2 1 200 0 0 0 1 1 0
230 1 1.1 0.9;
3 1 100 0 0 0 1 1 0
230 1 1.1 0.9;
4 2 50 0 0 0 1 1 0
230 1 1.1 0.9;
];
%% generator data
% bus Pg Qg Qmax Qmin Vg mBase status Pmax
Pmin Pc1 Pc2 Qc1min Qc1max Qc2min Qc2max ramp_agc ramp_10
ramp_30 ramp_q apf
mpc.gen = [
1 0 0 100 -100 1 100 1 400 0
0 0 0 0 0 0 0 0 0 0
0;
4 0 0 100 -100 1 100 1 100
0 0 0 0 0 0 0 0 0 0
0 0;
];
%% branch data
% fbus tbus r x b rateA rateB rateC ratio
angle status angmin angmax
mpc.branch = [
1 2 0 0.05 0 100 100 100 0
0 1 -360 360;
1 3 0 0.05 0 200 200 200 0
0 1 -360 360;
2 4 0 0.05 0 200 200 200 0
0 1 -360 360;
3 4 0 0.05 0 200 200 200 0
0 1 -360 360;
];
%% generator cost data
% 1 startup shutdown n x1 y1 ... xn
yn
% 2 startup shutdown n c(n-1) ... c0
mpc.gencost = [
1 0 0 2 0 1 400 400;
1 0 0 2 0 1 100 100;
];
