Optimisation with multiple combinations of inequality constraints that must be run simultaneously
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Hi I am trying to code a linear optimisation using linprog to determine the optimum number of PV (x1) and WT (x2) units under a given objective function shown below
f = [((CRF.*Panel_capacity./PV_energy)+OM_PV)((CRF.*WT_capacity/WT_energy)+OM_WT)];
Apart from CRF which is a constant, I have 27 selections for "Panel capacity" and "PVenergy" and "OM_PV" and 3 selections of "WT_capacity", "WTenergy" and "OM_WT".
I am trying to run linprog to examine the optimum x1 and x2 values for all the 27 and 3 combinations (which in total are 27*3 = 81 possible combinations). Therefore I am hoping for an output in some form similar to say:
5*x1,2 and 10*x2,3 which would mean the optimum combination is 5 units of the second PV panel (from the 27 in total) and 10 units of the third WT .
My inequality constraint is the following
b = Demand_vector;
Where "Demand_vector" is a 8760x1 vector -same for all cases.
A = [PV WT];
Where PV is currently a 8760x1 and WT is an 8760x1 to have a total 8760x2 matrix of A (this should give me a 2x1 vector of x's which is what I'm looking for).
However, as I mentioned above, I have 27 different PV's and 3 WT's (of the same type i.e 8760x1 which I want to examine all simultaneously and really need help in how to format the code for :
objective function - f (at the moment it doesn't account for all combs)
inequality constraint A = (at the moment it doesn't account for all combs)
Any help in how to format this linprog optimisation would be extremely appreciated, please let me know if more info is required.
Thank you
2 Comments
Sean de Wolski
on 29 Jun 2012
It would really help if you could provide a mat file with the data on free web hosting site.
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