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SRO-GEP.gms
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*-------------------------------------------------------------------------
* Universidad Pontificia Comillas de Madrid
* Optimization Techniques
* Diego Alejandro Tejada Arango
* Fecha: 05/03/2021
*-------------------------------------------------------------------------
$TITLE Static Robust Optimization (Scenario-based) - Generation Expansion Planning
* ========================================================================
* SETS DEFINITION
* ========================================================================
SETS
p "time periods (e.g., hours) " /h01 *h24 /
sc " scenarios " /sc01,sc02,sc03/
g "generation technologies" / wind, solar, ccgt, ocgt /
r(g) "subset of renewable technologies" / wind, solar/
;
* ========================================================================
* PARAMETERS AND SCALARS
* ========================================================================
SCALARS
pWeight "weight of representative period [days]" /365/
pENSCost "energy not supplied cost [kEUR/MWh]" /0.180/
;
PARAMETER
pDemand(p) "demand per time period [MW]"
/
h01 950
h02 870
h03 814
h04 779
h05 758
h06 751
h07 779
h08 834
h09 902
h10 956
h11 1010
h12 1023
h13 1018
h14 1010
h15 980
h16 965
h17 963
h18 997
h19 1093
h20 1114
h21 1115
h22 1107
h23 1053
h24 1035
/
;
TABLE pGenInfo(g,*) "generation information"
* kEUR/MWh kEUR/MW/year MW
VarCost InvCost UnitCap
ocgt 0.070 25 100
ccgt 0.050 40 400
wind 0.001 70 50
solar 0.000 50 10
;
TABLE pRenProf(p,r,sc) "renewable profile [p.u.]"
* sc01 -> low wind, high solar; sc02 -> avg wind and solar; sc03 -> high wind and low solar
wind.sc01 wind.sc02 wind.sc03 solar.sc01 solar.sc02 solar.sc03
h01 0.11 0.54 0.68 0.00 0.00 0.00
h02 0.11 0.54 0.69 0.00 0.00 0.00
h03 0.11 0.53 0.70 0.00 0.00 0.00
h04 0.11 0.52 0.71 0.00 0.00 0.00
h05 0.10 0.51 0.73 0.00 0.00 0.00
h06 0.10 0.50 0.74 0.02 0.00 0.00
h07 0.10 0.48 0.75 0.12 0.01 0.00
h08 0.09 0.47 0.76 0.30 0.07 0.01
h09 0.09 0.46 0.77 0.50 0.20 0.12
h10 0.09 0.45 0.78 0.66 0.36 0.28
h11 0.09 0.45 0.79 0.78 0.50 0.42
h12 0.09 0.45 0.80 0.83 0.57 0.51
h13 0.10 0.43 0.81 0.83 0.59 0.53
h14 0.12 0.41 0.81 0.78 0.54 0.50
h15 0.14 0.38 0.80 0.68 0.44 0.40
h16 0.15 0.35 0.79 0.53 0.29 0.23
h17 0.16 0.34 0.78 0.35 0.13 0.05
h18 0.16 0.35 0.77 0.17 0.03 0.00
h19 0.16 0.36 0.76 0.04 0.00 0.00
h20 0.15 0.38 0.75 0.00 0.00 0.00
h21 0.14 0.41 0.74 0.00 0.00 0.00
h22 0.13 0.43 0.74 0.00 0.00 0.00
h23 0.12 0.46 0.74 0.00 0.00 0.00
h24 0.12 0.48 0.74 0.00 0.00 0.00
;
* ========================================================================
* VARIABLES
* ========================================================================
INTEGER VARIABLE
vInstalUnits(g) "number of installed generation units [N]"
;
POSITIVE VARIABLE
vProduct(p,g,sc) "generation production per scenario [MW]"
vENS (p, sc) "energy not supplied per scenario [MW]"
;
FREE VARIABLES
vTotalCost "Total Cost = Investment + Operation [kEUR]"
vInvesCost "Total investment Cost [kEUR]"
vOperaCost "Worst operating Cost [kEUR]"
;
* ========================================================================
* EQUATIONS AND MODEL DEFINITION
* ========================================================================
EQUATIONS
eTotalCost "Total Cost = Investment + Operation [kEUR]"
eInvesCost "Total investment Cost [kEUR]"
eOperaCost( sc) " operating Cost per sc [kEUR]"
eBalance (p, sc) "power balance constriant [MW] "
eRenProd (p,g,sc) "renewable production constriant [MW] "
eMaxProd (p,g,sc) "generation production constraint [MW] "
;
eTotalCost.. vTotalCost =E= vInvesCost + vOperaCost
;
eInvesCost.. vInvesCost =E= SUM[g, pGenInfo(g,'InvCost')*pGenInfo(g,'UnitCap')*vInstalUnits(g)]
;
eOperaCost(sc).. vOperaCost =G= pWeight * SUM[(p,g),
+ pGenInfo(g,'VarCost')*vProduct(p,g,sc)
+ pENSCost *vENS (p, sc)]
;
eBalance(p,sc)..
SUM[g,vProduct(p,g,sc)] + vENS(p,sc) =E= pDemand(p)
;
eRenProd(p,r,sc)..
vProduct(p,r,sc) =L= pRenProf(p,r,sc) * pGenInfo(r,'UnitCap')*vInstalUnits(r)
;
eMaxProd(p,g,sc)$[not r(g)]..
vProduct(p,g,sc) =L= pGenInfo(g,'UnitCap')*vInstalUnits(g)
;
MODEL SRO_GEP / all /
;
* ========================================================================
* MODEL SOLUTION AND RESULTS
* ========================================================================
* option to find the solution to optimality
OPTION optcr=0;
SOLVE SRO_GEP USING MIP MINIMIZING vTotalCost
;
* result parameters
PARAMETERS
pInstalCap(g ) "installed capacity [MW] "
pScPrices (p,sc) "scenario prices [EUR/MWh]"
pEVPrices (p ) "expected value of prices [EUR/MWh]"
;
pInstalCap(g ) = pGenInfo(g,'UnitCap')*vInstalUnits.L(g);
pScPrices (p,sc) = eBalance.M(p,sc) *1e3 / [pWeight] ;
* gdx with all information
execute_unload 'SRO_GEP.gdx'