def dist_col_Rodrigo_ss(init0, bnd_set):
# collocation polynomial parameters
# polynomial roots (Radau)
m = ConcreteModel()
m.i_flag = init0
# set of finite elements and collocation points
m.fe = Set(initialize=[1])
m.cp = Set(initialize=[1])
m.bnd_set = bnd_set
if bnd_set:
print("Bounds_set")
Ntray = 42
m.Ntray = Ntray
m.tray = Set(initialize=[i for i in range(1, Ntray + 1)])
def __init_feed(m, t):
if t == 21:
return 57.5294
else:
return 0
m.feed = Param(m.tray, initialize=__init_feed)
m.xf = Param(initialize=0.32) # feed mole fraction
m.hf = Param(initialize=9081.3) # feed enthalpy
m.hlm0 = Param(initialize=2.6786e-04)
m.hlma = Param(initialize=-0.14779)
m.hlmb = Param(initialize=97.4289)
m.hlmc = Param(initialize=-2.1045e04)
m.hln0 = Param(initialize=4.0449e-04)
m.hlna = Param(initialize=-0.1435)
m.hlnb = Param(initialize=121.7981)
m.hlnc = Param(initialize=-3.0718e04)
m.r = Param(initialize=8.3147)
m.a = Param(initialize=6.09648)
m.b = Param(initialize=1.28862)
m.c1 = Param(initialize=1.016)
m.d = Param(initialize=15.6875)
m.l = Param(initialize=13.4721)
m.f = Param(initialize=2.615)
m.gm = Param(initialize=0.557)
m.Tkm = Param(initialize=512.6)
m.Pkm = Param(initialize=8.096e06)
m.gn = Param(initialize=0.612)
m.Tkn = Param(initialize=536.7)
m.Pkn = Param(initialize=5.166e06)
m.CapAm = Param(initialize=23.48)
m.CapBm = Param(initialize=3626.6)
m.CapCm = Param(initialize=-34.29)
m.CapAn = Param(initialize=22.437)
m.CapBn = Param(initialize=3166.64)
m.CapCn = Param(initialize=-80.15)
m.pstrip = Param(initialize=250)
m.prect = Param(initialize=190)
def _p_init(m, t):
ptray = 9.39e04
if t <= 20:
return _p_init(m, 21) + m.pstrip * (21 - t)
elif 20 < t < m.Ntray:
return ptray + m.prect * (m.Ntray - t)
elif t == m.Ntray:
return 9.39e04
m.p = Param(m.tray, initialize=_p_init)
m.T29_des = Param(initialize=343.15)
m.T15_des = Param(initialize=361.15)
m.Dset = Param(initialize=1.83728)
m.Qcset = Param(initialize=1.618890)
m.Qrset = Param(initialize=1.786050)
m.Recset = Param()
m.alpha_T29 = Param(initialize=1)
m.alpha_T15 = Param(initialize=1)
m.alpha_D = Param(initialize=1)
m.alpha_Qc = Param(initialize=1)
m.alpha_Qr = Param(initialize=1)
m.alpha_Rec = Param(initialize=1)
def _alpha_init(m, i):
if i <= 21:
return 0.62
else:
return 0.35
m.alpha = Param(m.tray, initialize=_alpha_init)
ME0 = {}
ME0[1] = 123790.826443232
ME0[2] = 3898.34923206106
ME0[3] = 3932.11766868415
ME0[4] = 3950.13107445914
ME0[5] = 3960.01212104318
ME0[6] = 3965.37146944881
ME0[7] = 3968.25340380767
ME0[8] = 3969.78910997468
ME0[9] = 3970.5965548502
ME0[10] = 3971.0110096803
ME0[11] = 3971.21368740283
ME0[12] = 3971.30232788932
ME0[13] = 3971.32958547037
ME0[14] = 3971.32380573089
ME0[15] = 3971.30024105555
ME0[16] = 3971.26709591428
ME0[17] = 3971.22878249852
ME0[18] = 3971.187673073
ME0[19] = 3971.14504284211
ME0[20] = 3971.10157713182
ME0[21] = 3971.05764415189
ME0[22] = 3611.00216267141
ME0[23] = 3766.84741932423
ME0[24] = 3896.87907072814
ME0[25] = 4004.98630195624
ME0[26] = 4092.49383654928
ME0[27] = 4161.86560059956
ME0[28] = 4215.98509169956
ME0[29] = 4257.69470716792
ME0[30] = 4289.54901779038
ME0[31] = 4313.71557755738
ME0[32] = 4331.9642075775
ME0[33] = 4345.70190802884
ME0[34] = 4356.02621744716
ME0[35] = 4363.78165047072
ME0[36] = 4369.61159802674
ME0[37] = 4374.00266939603
ME0[38] = 4377.32093116489
ME0[39] = 4379.84068162411
ME0[40] = 4381.76685527968
ME0[41] = 4383.25223100374
ME0[42] = 4736.04924276762
m.M_pred = Param(m.tray, initialize=ME0)
XE0 = {}
XE0[1] = 0.306547877605746
XE0[2] = 0.398184778678485
XE0[3] = 0.416675004386508
XE0[4] = 0.42676332128531
XE0[5] = 0.432244548463899
XE0[6] = 0.435193762178033
XE0[7] = 0.436764699693985
XE0[8] = 0.437589297877498
XE0[9] = 0.438010896454752
XE0[10] = 0.43821522113022
XE0[11] = 0.438302495819782
XE0[12] = 0.438326730875504
XE0[13] = 0.438317008813347
XE0[14] = 0.438288981487008
XE0[15] = 0.438251069561153
XE0[16] = 0.438207802087721
XE0[17] = 0.438161614415035
XE0[18] = 0.438113815737636
XE0[19] = 0.438065109638753
XE0[20] = 0.438015874079915
XE0[21] = 0.437966311972983
XE0[22] = 0.724835538043496
XE0[23] = 0.788208485334881
XE0[24] = 0.838605564838572
XE0[25] = 0.87793558673077
XE0[26] = 0.908189470853012
XE0[27] = 0.931224584141055
XE0[28] = 0.948635083197147
XE0[29] = 0.961724712952285
XE0[30] = 0.971527857048483
XE0[31] = 0.978848914860811
XE0[32] = 0.984304939392599
XE0[33] = 0.98836476845163
XE0[34] = 0.991382214572503
XE0[35] = 0.993622983870866
XE0[36] = 0.995285909293636
XE0[37] = 0.996519395295701
XE0[38] = 0.997433995899531
XE0[39] = 0.998111951760656
XE0[40] = 0.998614376770054
XE0[41] = 0.998986649363
XE0[42] = 0.999262443919619
m.x_pred = Param(m.tray, initialize=XE0)
# hold in each tray
def __m_init(m, i, j, t):
if m.i_flag:
if t < m.Ntray:
return 4000.
elif t == 1:
return 104340.
elif t == m.Ntray:
return 5000.
else:
return 0.
m.M = Var(m.fe, m.cp, m.tray, initialize=__m_init)
# m.M_0 = Var(m.fe, m.tray, initialize=1e07)
# temperatures
def __t_init(m, i, j, t):
if m.i_flag:
return ((370.781 - 335.753) / m.Ntray) * t + 370.781
else:
return 10.
m.T = Var(m.fe, m.cp, m.tray, initialize=__t_init)
# saturation pressures
m.pm = Var(m.fe, m.cp, m.tray, initialize=1e4)
m.pn = Var(m.fe, m.cp, m.tray, initialize=1e4)
# define l-v flowrate
def _v_init(m, i, j, t):
if m.i_flag:
return 44.
else:
return 0.
m.V = Var(m.fe, m.cp, m.tray, initialize=_v_init)
def _l_init(m, i, j, t):
if m.i_flag:
if 2 <= t <= 21:
return 83.
elif 22 <= t <= 42:
return 23
elif t == 1:
return 40
else:
return 0.
m.L = Var(m.fe, m.cp, m.tray, initialize=_l_init)
# mol frac l-v
def __x_init(m, i, j, t):
if m.i_flag:
return (0.999 / m.Ntray) * t
else:
return 1
m.x = Var(m.fe, m.cp, m.tray, initialize=__x_init)
#m.x_0 = Var(m.fe, m.tray)
# av
def __y_init(m, i, j, t):
if m.i_flag:
return ((0.99 - 0.005) / m.Ntray) * t + 0.005
else:
return 1
m.y = Var(m.fe, m.cp, m.tray, initialize=__y_init)
# enthalpy
m.hl = Var(m.fe, m.cp, m.tray, initialize=10000.)
def __hv_init(m, i, j, t):
if m.i_flag:
if t < m.Ntray:
return 5e4
else:
return 0.0
m.hv = Var(m.fe, m.cp, m.tray, initialize=__hv_init)
# reboiler & condenser heat
m.Qc = Var(m.fe, m.cp, initialize=1.6e06)
m.D = Var(m.fe, m.cp, initialize=18.33)
# vol holdups
m.Vm = Var(m.fe, m.cp, m.tray, initialize=6e-05)
def __mv_init(m, i, j, t):
if m.i_flag:
if 1 < t < m.Ntray:
return 0.23
else:
return 0.0
m.Mv = Var(m.fe, m.cp, m.tray, initialize=__mv_init)
m.Mv1 = Var(m.fe, m.cp, initialize=8.57)
m.Mvn = Var(m.fe, m.cp, initialize=0.203)
def _bound_set(m):
if m.bnd_set:
for key, value in m.M.iteritems():
value.setlb(1.0)
value.setub(1e7)
for key, value in m.Vm.iteritems():
value.setlb(-1.0)
value.setub(1e4)
for key, value in m.Mv.iteritems():
value.setlb(0.155 + 1e-06)
value.setub(1e4)
for key, value in m.Mv1.iteritems():
value.setlb(8.5 + 1e-06)
value.setub(1e4)
for key, value in m.Mvn.iteritems():
value.setlb(0.17 + 1e-06)
value.setub(1e4)
for key, value in m.y.iteritems():
value.setlb(0.0)
value.setub(1.0)
for key, value in m.x.iteritems():
value.setlb(0.0)
value.setub(1.0)
for key, value in m.L.iteritems():
value.setlb(0.0)
for key, value in m.V.iteritems():
value.setlb(0.0)
_bound_set(m)
m.Rec = Param(m.fe, initialize=7.72700925775773761472464684629813e-01)
# m.Rec = Param(m.fe, initialize=0.05)
m.Qr = Param(m.fe, initialize=1.78604740940007800236344337463379E+06)
# m.Qr = Param(m.fe, initialize=1.5e+02)
# mass balances
def _MODEtr(m, i, j, k):
if j > 0 and 1 < k < Ntray:
return 0.0 == (m.V[i, j, k - 1] - m.V[i, j, k] + m.L[i, j, k + 1] -
m.L[i, j, k] + m.feed[k])
else:
return Constraint.Skip
m.MODEtr = Constraint(m.fe, m.cp, m.tray, rule=_MODEtr)
# m.L[i, j, 1] = B
def _MODEr(m, i, j):
if j > 0:
return 0.0 == (m.L[i, j, 2] - m.L[i, j, 1] - m.V[i, j, 1])
else:
return Constraint.Skip
m.MODEr = Constraint(m.fe, m.cp, rule=_MODEr)
def _MODEc(m, i, j):
if j > 0:
return 0.0 == (m.V[i, j, Ntray - 1] - m.L[i, j, Ntray] - m.D[i, j])
else:
return Constraint.Skip
m.MODEc = Constraint(m.fe, m.cp, rule=_MODEc)
def _XODEtr(m, i, j, t):
if j > 0 and 1 < t < Ntray:
return 0.0 == (m.V[i, j, t - 1] * (m.y[i, j, t - 1] - m.x[i, j, t]) + \
m.L[i, j, t + 1] * (m.x[i, j, t + 1] - m.x[i, j, t]) - \
m.V[i, j, t] * (m.y[i, j, t] - m.x[i, j, t]) + \
m.feed[t] * (m.xf - m.x[i, j, t]))
else:
return Constraint.Skip
m.XODEtr = Constraint(m.fe, m.cp, m.tray, rule=_XODEtr)
def _xoder(m, i, j):
if j > 0:
return 0.0 == (m.L[i, j, 2] * (m.x[i, j, 2] - m.x[i, j, 1]) - \
m.V[i, j, 1] * (m.y[i, j, 1] - m.x[i, j, 1]))
else:
return Constraint.Skip
m.xoder = Constraint(m.fe, m.cp, rule=_xoder)
def _xodec(m, i, j):
if j > 0:
return 0.0 == \
(m.V[i, j, Ntray - 1] * (m.y[i, j, Ntray - 1] - m.x[i, j, Ntray]))
else:
return Constraint.Skip
m.xodec = Constraint(m.fe, m.cp, rule=_xodec)
def _hrc(m, i, j):
if j > 0:
return m.D[i, j] - m.Rec[i] * m.L[i, j, Ntray] == 0
else:
return Constraint.Skip
m.hrc = Constraint(m.fe, m.cp, rule=_hrc)
# Energy balance
def _gh(m, i, j, t):
if j > 0 and 1 < t < Ntray:
return 0.0 \
== (m.V[i, j, t-1] * (m.hv[i, j, t-1] - m.hl[i, j, t]) + m.L[i, j, t+1] * (m.hl[i, j, t+1] - m.hl[i, j, t]) - m.V[i, j, t] * (m.hv[i, j, t] - m.hl[i, j, t]) + m.feed[t] * (m.hf - m.hl[i, j, t]))
# return m.M[i, j, t] * (m.xdot[i, j, t] * ((m.hlm0 - m.hln0) * m.T[i, j, t]**3 + (m.hlma - m.hlna) * m.T[i, j, t]**2 + (m.hlmb - m.hlnb) * m.T[i, j, t] + m.hlmc - m.hlnc) + m.Tdot[i, j, t]*(3*m.hln0*m.T[i, j, t]**2 + 2*m.hlna * m.T[i, j, t] + m.hlnb + m.x[i, j, t]*(3*(m.hlm0 - m.hln0) * m.T[i, j, t]**2 + 2 * (m.hlma - m.hlna) * m.T[i, j, t] + m.hlmb - m.hlnb))) \
# M[i, q, c] * ( xdot[i, q, c] * (( hlm0 - hln0) * T[i, q, c] ^ 3 + ( hlma - hlna) * T[i, q, c] ^ 2 + ( hlmb - hlnb) * T[i, q, c] + hlmc - hlnc) + Tdot[i, q, c]*(3* hln0 * T[i, q, c] ^ 2 +2 * hlna * T[i, q, c] + hlnb + x[i, q, c]*(3*( hlm0 - hln0) * T[i, q, c] ^ 2 + 2 * ( hlma - hlna) * T[i, q, c] + hlmb - hlnb))) =
# V[i - 1, q, c]*(hv[i - 1, q, c] - hl[i, q, c]) + L[i + 1, q, c]*(hl[i + 1, q, c] - hl[i, q, c]) - V[i, q, c] * ( hv[i, q, c] - hl[i, q, c]) + feed[i] * ( hf - hl[i, q, c]);
else:
return Constraint.Skip
# M[i,q,c] *( xdot[i,q,c]* ((hlm0 - hln0) * T[i,q,c]^3 + ( hlma - hlna) * T[i,q,c]^2 + ( hlmb - hlnb) * T[i,q,c] + hlmc - hlnc) + Tdot[i,q,c] *(3* hln0* T[i,q,c]^2 + 2* hlna* T[i,q,c] + hlnb + x[i,q,c]* (3*( hlm0 - hln0) *T[i,q,c]^2 + 2* (hlma - hlna) *T[i,q,c]+ hlmb - hlnb)))
# V[i-1,q,c] *( hv[i-1,q,c] - hl[i,q,c] ) + L[i+1,q,c]* ( hl[i+1,q,c] - hl[i,q,c] ) - V[i,q,c] * ( hv[i,q,c] - hl[i,q,c]) + feed[i] * (hf - hl[i,q,c])
m.gh = Constraint(m.fe, m.cp, m.tray, rule=_gh)
def _ghb(m, i, j):
if j > 0:
return 0.0 == \
(m.L[i, j, 2] * (m.hl[i, j, 2] - m.hl[i, j, 1]) - m.V[i, j, 1] * (m.hv[i, j, 1] - m.hl[i, j, 1]) + m.Qr[i])
# M[1,q,c]* ( xdot[1,q,c] * (( hlm0 - hln0) *T[1,q,c]^3 + (hlma - hlna)* T[1,q,c]^2 + ( hlmb - hlnb) *T[1,q,c] + hlmc - hlnc) + Tdot[1,q,c]* (3* hln0 * T[1,q,c]^2 + 2 * hlna * T[1,q,c] + hlnb + x[1,q,c] * (3 * ( hlm0 - hln0) * T[1,q,c]^2 + 2*( hlma - hlna) *T[1,q,c] + hlmb - hlnb))) =
# L[2,q,c]* ( hl[2,q,c] - hl[1,q,c] ) - V[1,q,c] * ( hv[1,q,c] - hl[1,q,c] ) + Qr[q] ;
else:
return Constraint.Skip
m.ghb = Constraint(m.fe, m.cp, rule=_ghb)
def _ghc(m, i, j):
if j > 0:
return 0.0 == \
(m.V[i, j, Ntray - 1] * (m.hv[i, j, Ntray - 1] - m.hl[i, j, Ntray]) - m.Qc[i, j])
#M[Ntray, q, c] * (xdot[Ntray, q, c] * ((hlm0 - hln0) * T[Ntray, q, c] ^ 3 + (hlma - hlna) * T[Ntray, q, c] ^ 2 + (hlmb - hlnb) * T[Ntray, q, c] + hlmc - hlnc) + Tdot[Ntray, q, c] * (3 * hln0 * T[Ntray, q, c] ^ 2 + 2 * hlna * T[Ntray, q, c] + hlnb + x[Ntray, q, c] * (3 * ( hlm0 - hln0) * T[Ntray, q, c] ^ 2 + 2 * (hlma - hlna) * T[Ntray, q, c] + hlmb - hlnb))) =
# V[Ntray - 1, q, c] * (hv[Ntray - 1, q, c] - hl[Ntray, q, c]) - Qc[q, c];
else:
return Constraint.Skip
#M[Ntray, q, c] * ( xdot[Ntray, q, c] * (( hlm0 - hln0) * T[Ntray, q, c] ^ 3 + ( hlma - hlna) * T[Ntray, q, c] ^ 2 +(hlmb - hlnb) * T[Ntray, q, c] + hlmc - hlnc) + Tdot[Ntray, q, c] * (3 * hln0 * T[Ntray, q, c] ^ 2 + 2 * hlna * T[Ntray, q, c] + hlnb + x[Ntray, q, c] * (3 * ( hlm0 - hln0) * T[Ntray, q, c] ^ 2 + 2 * (hlma - hlna) * T[Ntray, q, c] + hlmb - hlnb))) =
# V[Ntray - 1, q, c] * (hv[Ntray - 1, q, c] - hl[Ntray, q, c]) - Qc[q, c];
m.ghc = Constraint(m.fe, m.cp, rule=_ghc)
def _hkl(m, i, j, t):
if j > 0:
return m.hl[i, j, t] == m.x[i, j, t] * (
m.hlm0 * m.T[i, j, t]**3 + m.hlma * m.T[i, j, t]**2 +
m.hlmb * m.T[i, j, t] + m.hlmc) + (1 - m.x[i, j, t]) * (
m.hln0 * m.T[i, j, t]**3 + m.hlna * m.T[i, j, t]**2 +
m.hlnb * m.T[i, j, t] + m.hlnc)
# hl[i, q, c] = x[i, q, c]*( hlm0 * T[i, q, c] ^ 3 + hlma * T[i, q, c] ^ 2 + hlmb * T[i, q, c] + hlmc ) + (1 - x[i, q, c] )*( hln0 * T[i, q, c] ^ 3 + hlna* T[i, q, c] ^ 2 + hlnb * T[i, q, c] + hlnc);
else:
return Constraint.Skip
# hl[i,q,c] = x[i,q,c]* ( hlm0* T[i,q,c]^3 + hlma * T[i,q,c]^2 + hlmb* T[i,q,c] + hlmc) + (1 - x[i,q,c])* ( hln0 *T[i,q,c] ^ 3 + hlna* T[i,q,c]^2 + hlnb *T[i,q,c] + hlnc) ;
m.hkl = Constraint(m.fe, m.cp, m.tray, rule=_hkl)
def _hkv(m, i, j, t):
if j > 0 and t < Ntray:
return m.hv[i, j, t] == m.y[i, j, t] * (
m.hlm0 * m.T[i, j, t]**3 + m.hlma * m.T[i, j, t]**2 +
m.hlmb * m.T[i, j, t] + m.hlmc +
m.r * m.Tkm * sqrt(1 - (m.p[t] / m.Pkm) *
(m.Tkm / m.T[i, j, t])**3) *
(m.a - m.b * m.T[i, j, t] / m.Tkm + m.c1 *
(m.T[i, j, t] / m.Tkm)**7 + m.gm *
(m.d - m.l * m.T[i, j, t] / m.Tkm + m.f *
(m.T[i, j, t] / m.Tkm)**7))) + (1 - m.y[i, j, t]) * (
m.hln0 * m.T[i, j, t]**3 + m.hlna * m.T[i, j, t]**2 +
m.hlnb * m.T[i, j, t] + m.hlnc +
m.r * m.Tkn * sqrt(1 - (m.p[t] / m.Pkn) *
(m.Tkn / m.T[i, j, t])**3) *
(m.a - m.b * m.T[i, j, t] / m.Tkn + m.c1 *
(m.T[i, j, t] / m.Tkn)**7 + m.gn *
(m.d - m.l * m.T[i, j, t] / m.Tkn + m.f *
(m.T[i, j, t] / m.Tkn)**7)))
else:
return Constraint.Skip
# hv[i,q,c] = y[i,q,c] * (hlm0 * T[i,q,c]^3 + hlma* T[i,q,c]^2 + hlmb * T[i,q,c] + hlmc + r* Tkm* sqrt(1 - ( p[i]/ Pkm)* ( Tkm/ T[i,q,c]) ^ 3 )*(a - b* T[i,q,c]/ Tkm + c1* ( T[i,q,c] / Tkm) ^7 + gm* ( d - l * T[i,q,c] /Tkm + f*( T[i,q,c] / Tkm)^7 ))) + (1 - y[i,q,c] )* ( hln0 * T[i,q,c] ^3 + hlna* T[i,q,c]^ 2 + hlnb* T[i,q,c] + hlnc + r * Tkn* sqrt(1 - ( p[i]/Pkn )*( Tkn/ T[i,q,c] )^3 )*( a - b * T[i,q,c] / Tkn + c1 * ( T[i,q,c] / Tkn)^7 + gn*( d - l* T[i,q,c]/ Tkn + f*( T[i,q,c] / Tkn) ^7 ))) ;
m.hkv = Constraint(m.fe, m.cp, m.tray, rule=_hkv)
def _lpm(m, i, j, t):
if j > 0:
return m.pm[i, j,
t] == exp(m.CapAm - m.CapBm / (m.T[i, j, t] + m.CapCm))
else:
return Constraint.Skip
m.lpm = Constraint(m.fe, m.cp, m.tray, rule=_lpm)
def _lpn(m, i, j, t):
if j > 0:
return m.pn[i, j,
t] == exp(m.CapAn - m.CapBn / (m.T[i, j, t] + m.CapCn))
else:
return Constraint.Skip
m.lpn = Constraint(m.fe, m.cp, m.tray, rule=_lpn)
def _dp(m, i, j, t):
if j > 0:
return m.p[t] == m.pm[i, j, t] * m.x[i, j, t] + (
1 - m.x[i, j, t]) * m.pn[i, j, t]
else:
return Constraint.Skip
m.dp = Constraint(m.fe, m.cp, m.tray, rule=_dp)
def _gy0(m, i, j):
if j > 0:
return m.y[i, j, 1] == m.x[i, j, 1] * m.pm[i, j, 1] / m.p[1]
else:
return Constraint.Skip
m.gy0 = Constraint(m.fe, m.cp, rule=_gy0)
def _gy(m, i, j, t):
if j > 0 and 1 < t < Ntray:
return m.y[i, j, t] == m.alpha[t] * m.x[i, j, t] * m.pm[
i, j, t] / m.p[t] + (1 - m.alpha[t]) * m.y[i, j, t - 1]
#y[i, q, c] = alpha[i] * x[i, q, c] * pm[i, q, c] / p[i] + (1 - alpha[i]) * y[i - 1, q, c];
else:
return Constraint.Skip
m.gy = Constraint(m.fe, m.cp, m.tray, rule=_gy)
def _dMV(m, i, j, t):
if j > 0 and 1 < t < Ntray:
return m.Mv[i, j, t] == m.Vm[i, j, t] * m.M[i, j, t]
else:
return Constraint.Skip
m.dMV = Constraint(m.fe, m.cp, m.tray, rule=_dMV)
def _dMv1(m, i, j):
if j > 0:
return m.Mv1[i, j] == m.Vm[i, j, 1] * m.M[i, j, 1]
else:
return Constraint.Skip
m.dMv1 = Constraint(m.fe, m.cp, rule=_dMv1)
def _dMvn(m, i, j):
if j > 0:
return m.Mvn[i, j] == m.Vm[i, j, Ntray] * m.M[i, j, Ntray]
else:
return Constraint.Skip
m.dMvn = Constraint(m.fe, m.cp, rule=_dMvn)
def _hyd(m, i, j, t):
if j > 0 and 1 < t < Ntray:
return m.L[i, j, t] * m.Vm[i, j, t] == 0.166 * (m.Mv[i, j, t] -
0.155)**1.5
# L[i,q,c]* Vm[i,q,c] = 0.166 * ( Mv[i,q,c] - 0.155)^1.5 ;
else:
return Constraint.Skip
m.hyd = Constraint(m.fe, m.cp, m.tray, rule=_hyd)
def _hyd1(m, i, j):
if j > 0:
return m.L[i, j, 1] * m.Vm[i, j,
1] == 0.166 * (m.Mv1[i, j] - 8.5)**1.5
else:
return Constraint.Skip
# L[i,q,c]*Vm[i,q,c] = 0.166*(Mv[i,q,c] - 0.155)^1.5 ;
m.hyd1 = Constraint(m.fe, m.cp, rule=_hyd1)
def _hydN(m, i, j):
if j > 0:
return m.L[i, j, Ntray] * m.Vm[i, j, Ntray] == 0.166 * (
m.Mvn[i, j] - 0.17)**1.5
else:
return Constraint.Skip
# L[i,q,c]*Vm[i,q,c] = 0.166*(Mv[i,q,c] - 0.155)^1.5 ;
m.hydN = Constraint(m.fe, m.cp, rule=_hydN)
def _dvm(m, i, j, t):
if j > 0:
return m.Vm[i, j, t] == m.x[i, j, t] * (
(1 / 2288) * 0.2685**
(1 +
(1 - m.T[i, j, t] / 512.4)**0.2453)) + (1 - m.x[i, j, t]) * (
(1 / 1235) * 0.27136**(1 +
(1 - m.T[i, j, t] / 536.4)**0.24))
else:
return Constraint.Skip
# Vm[i,q,c] = x[i,q,c] * ( 1/2288 * 0.2685^ (1 + (1 - T[i,q,c] /512.4)^0.2453)) + (1 - x[i,q,c]) * (1/1235 * 0.27136^ (1 + (1 - T[i,q,c] /536.4)^ 0.24)) ;
m.dvm = Constraint(m.fe, m.cp, m.tray, rule=_dvm)
return m
mod.pm = Var(mod.t, mod.tray, initialize=1e4)
mod.pn = Var(mod.t, mod.tray, initialize=1e4)
# Vapor mole flowrate
mod.V = Var(mod.t, mod.tray, initialize=44.0)
def _l_init(m, i, k):
if 2 <= k <= 21:
return 83.
elif 22 <= k <= 42:
return 23
elif k == 1:
return 40
# Liquid mole flowrate
mod.L = Var(mod.t, mod.tray, initialize=_l_init)
# Vapor mole frac & diff var
mod.y = Var(mod.t, mod.tray,
initialize=lambda m, i, k: ((0.99 - 0.005) / m.Ntray) * k + 0.005)
# Liquid enthalpy # enthalpy
mod.hl = Var(mod.t, mod.tray, initialize=10000.)
# Liquid enthalpy # enthalpy
mod.hv = Var(mod.t, mod.tray, initialize=5e+04)
# Re-boiler & condenser heat
mod.Qc = Var(mod.t, initialize=1.6e06)
mod.D = Var(mod.t, initialize=18.33)
# vol holdups
mod.Vm = Var(mod.t, mod.tray, initialize=6e-05)
def create_model(self):
"""
Create and return the mathematical model.
"""
if options.DEBUG:
logging.info("Creating model for day %d" % self.day_id)
# Obtain the orders book
book = self.orders
complexOrders = self.complexOrders
# Create the optimization model
model = ConcreteModel()
model.periods = Set(initialize=book.periods)
maxPeriod = max(book.periods)
model.bids = Set(initialize=range(len(book.bids)))
model.L = Set(initialize=book.locations)
model.sBids = Set(initialize=[
i for i in range(len(book.bids)) if book.bids[i].type == 'SB'
])
model.bBids = Set(initialize=[
i for i in range(len(book.bids)) if book.bids[i].type == 'BB'
])
model.cBids = RangeSet(len(complexOrders)) # Complex orders
model.C = RangeSet(len(self.connections))
model.directions = RangeSet(2) # 1 == up, 2 = down TODO: clean
# Variables
model.xs = Var(model.sBids, domain=Reals,
bounds=(0.0, 1.0)) # Single period bids acceptance
model.xb = Var(model.bBids, domain=Binary) # Block bids acceptance
model.xc = Var(model.cBids, domain=Binary) # Complex orders acceptance
model.pi = Var(model.L * model.periods,
domain=Reals,
bounds=self.priceCap) # Market prices
model.s = Var(model.bids, domain=NonNegativeReals) # Bids
model.sc = Var(model.cBids, domain=NonNegativeReals) # complex orders
model.complexVolume = Var(model.cBids, model.periods,
domain=Reals) # Bids
model.pi_lg_up = Var(model.cBids * model.periods,
domain=NonNegativeReals) # Market prices
model.pi_lg_down = Var(model.cBids * model.periods,
domain=NonNegativeReals) # Market prices
model.pi_lg = Var(model.cBids * model.periods,
domain=Reals) # Market prices
def flowBounds(m, c, d, t):
capacity = self.connections[c - 1].capacity_up[t] if d == 1 else \
self.connections[c - 1].capacity_down[t]
return (0, capacity)
model.f = Var(model.C * model.directions * model.periods,
domain=NonNegativeReals,
bounds=flowBounds)
model.u = Var(model.C * model.directions * model.periods,
domain=NonNegativeReals)
# Objective
def primalObj(m):
# Single period bids cost
expr = summation(
{i: book.bids[i].price * book.bids[i].volume
for i in m.sBids}, m.xs)
# Block bids cost
expr += summation(
{
i: book.bids[i].price * sum(book.bids[i].volumes.values())
for i in m.bBids
}, m.xb)
return -expr
if options.PRIMAL and not options.DUAL:
model.obj = Objective(rule=primalObj, sense=maximize)
def primalDualObj(m):
return primalObj(m) + sum(1e-5 * m.xc[i] for i in model.cBids)
if options.PRIMAL and options.DUAL:
model.obj = Objective(rule=primalDualObj, sense=maximize)
# Complex order constraint
if options.PRIMAL and options.DUAL:
model.deactivate_suborders = ConstraintList()
for o in model.cBids:
sub_ids = complexOrders[o - 1].ids
curves = complexOrders[o - 1].curves
for id in sub_ids:
bid = book.bids[id]
if bid.period <= complexOrders[o - 1].SSperiods and bid.price == \
curves[bid.period].bids[0].price:
pass # This bid, first step of the cruve in the scheduled stop periods, is not automatically deactivated when MIC constraint is not satisfied
else:
model.deactivate_suborders.add(
model.xs[id] <= model.xc[o])
# Ramping constraints for complex orders
def complex_volume_def_rule(m, o, p):
sub_ids = complexOrders[o - 1].ids
return m.complexVolume[o, p] == sum(m.xs[i] * book.bids[i].volume
for i in sub_ids
if book.bids[i].period == p)
if options.PRIMAL:
model.complex_volume_def = Constraint(model.cBids,
model.periods,
rule=complex_volume_def_rule)
def complex_lg_down_rule(m, o, p):
if p + 1 > maxPeriod or complexOrders[o - 1].ramp_down == None:
return Constraint.Skip
else:
return m.complexVolume[o, p] - m.complexVolume[o, p + 1] <= complexOrders[
o - 1].ramp_down * \
m.xc[o]
if options.PRIMAL and options.APPLY_LOAD_GRADIENT:
model.complex_lg_down = Constraint(model.cBids,
model.periods,
rule=complex_lg_down_rule)
def complex_lg_up_rule(m, o, p):
if p + 1 > maxPeriod or complexOrders[o - 1].ramp_up == None:
return Constraint.Skip
else:
return m.complexVolume[o, p + 1] - m.complexVolume[
o, p] <= complexOrders[o - 1].ramp_up
if options.PRIMAL and options.APPLY_LOAD_GRADIENT:
model.complex_lg_up = Constraint(
model.cBids, model.periods,
rule=complex_lg_up_rule) # Balance constraint
# Energy balance constraints
balanceExpr = {l: {t: 0.0 for t in model.periods} for l in model.L}
for i in model.sBids: # Simple bids
bid = book.bids[i]
balanceExpr[bid.location][bid.period] += bid.volume * model.xs[i]
for i in model.bBids: # Block bids
bid = book.bids[i]
for t, v in bid.volumes.items():
balanceExpr[bid.location][t] += v * model.xb[i]
def balanceCstr(m, l, t):
export = 0.0
for c in model.C:
if self.connections[c - 1].from_id == l:
export += m.f[c, 1, t] - m.f[c, 2, t]
elif self.connections[c - 1].to_id == l:
export += m.f[c, 2, t] - m.f[c, 1, t]
return balanceExpr[l][t] == export
if options.PRIMAL:
model.balance = Constraint(model.L * book.periods,
rule=balanceCstr)
# Surplus of single period bids
def sBidSurplus(m, i): # For the "usual" step orders
bid = book.bids[i]
if i in self.plain_single_orders:
return m.s[i] >= (m.pi[bid.location, bid.period] -
bid.price) * bid.volume
else:
return Constraint.Skip
if options.DUAL:
model.sBidSurplus = Constraint(model.sBids, rule=sBidSurplus)
# Surplus definition for complex suborders accounting for impact of load gradient condition
if options.DUAL:
model.complex_sBidSurplus = ConstraintList()
for o in model.cBids:
sub_ids = complexOrders[o - 1].ids
l = complexOrders[o - 1].location
for i in sub_ids:
bid = book.bids[i]
model.complex_sBidSurplus.add(
model.s[i] >=
(model.pi[l, bid.period] + model.pi_lg[o, bid.period] -
bid.price) * bid.volume)
def LG_price_def_rule(m, o, p):
l = complexOrders[o - 1].location
exp = 0
if options.APPLY_LOAD_GRADIENT:
D = complexOrders[o - 1].ramp_down
U = complexOrders[o - 1].ramp_up
if D is not None:
exp += (m.pi_lg_down[o, p - 1] if p > 1 else
0) - (m.pi_lg_down[o, p] if p < maxPeriod else 0)
if U is not None:
exp -= (m.pi_lg_up[o, p - 1] if p > 1 else
0) - (m.pi_lg_up[o, p] if p < maxPeriod else 0)
return m.pi_lg[o, p] == exp
if options.DUAL:
model.LG_price_def = Constraint(model.cBids,
model.periods,
rule=LG_price_def_rule)
# Surplus of block bids
def bBidSurplus(m, i):
bid = book.bids[i]
bidVolume = -sum(bid.volumes.values())
bigM = (self.priceCap[1] -
self.priceCap[0]) * bidVolume # FIXME tighten BIGM
return m.s[i] + sum([
m.pi[bid.location, t] * -v for t, v in bid.volumes.items()
]) >= bid.cost * bidVolume + bigM * (1 - m.xb[i])
if options.DUAL:
model.bBidSurplus = Constraint(model.bBids, rule=bBidSurplus)
# Surplus of complex orders
def cBidSurplus(m, o):
complexOrder = complexOrders[o - 1]
sub_ids = complexOrder.ids
if book.bids[sub_ids[0]].volume > 0: # supply
bigM = sum((self.priceCap[1] - book.bids[i].price) *
book.bids[i].volume for i in sub_ids)
else:
bigM = sum((book.bids[i].price - self.priceCap[0]) *
book.bids[i].volume for i in sub_ids)
return m.sc[o] + bigM * (1 - m.xc[o]) >= sum(m.s[i]
for i in sub_ids)
if options.DUAL:
model.cBidSurplus = Constraint(model.cBids, rule=cBidSurplus)
# Surplus of complex orders
def cBidSurplus_2(m, o):
complexOrder = complexOrders[o - 1]
expr = 0
for i in complexOrder.ids:
bid = book.bids[i]
if (bid.period <= complexOrder.SSperiods) and (
bid.price
== complexOrder.curves[bid.period].bids[0].price):
expr += m.s[i]
return m.sc[o] >= expr
if options.DUAL:
model.cBidSurplus_2 = Constraint(
model.cBids, rule=cBidSurplus_2) # MIC constraint
def cMIC(m, o):
complexOrder = complexOrders[o - 1]
if complexOrder.FT == 0 and complexOrder.VT == 0:
return Constraint.Skip
expr = 0
bigM = complexOrder.FT
for i in complexOrder.ids:
bid = book.bids[i]
if (bid.period <= complexOrder.SSperiods) and (
bid.price
== complexOrder.curves[bid.period].bids[0].price):
bigM += (bid.volume * (self.priceCap[1] - bid.price)
) # FIXME assumes order is supply
expr += bid.volume * m.xs[i] * (bid.price - complexOrder.VT)
return m.sc[o] + expr + bigM * (1 - m.xc[o]) >= complexOrder.FT
if options.DUAL and options.PRIMAL:
model.cMIC = Constraint(model.cBids, rule=cMIC)
# Dual connections capacity
def dualCapacity(m, c, t):
exportPrices = 0.0
for l in m.L:
if l == self.connections[c - 1].from_id:
exportPrices += m.pi[l, t]
elif l == self.connections[c - 1].to_id:
exportPrices -= m.pi[l, t]
return m.u[c, 1, t] - m.u[c, 2, t] + exportPrices == 0.0
if options.DUAL:
model.dualCapacity = Constraint(model.C * model.periods,
rule=dualCapacity)
# Dual optimality
def dualObj(m):
dualObj = summation(m.s) + summation(m.sc)
for o in m.cBids:
sub_ids = complexOrders[o - 1].ids
for id in sub_ids:
dualObj -= m.s[
id] # Remove contribution of complex suborders which were accounted for in prevous summation over single bids
if options.APPLY_LOAD_GRADIENT:
ramp_down = complexOrders[o - 1].ramp_down
ramp_up = complexOrders[o - 1].ramp_up
for p in m.periods:
if p == maxPeriod:
continue
if ramp_down is not None:
dualObj += ramp_down * m.pi_lg_down[
o, p] # Add contribution of load gradient
if ramp_up is not None:
dualObj += ramp_up * m.pi_lg_up[
o, p] # Add contribution of load gradient
for c in model.C:
for t in m.periods:
dualObj += self.connections[c - 1].capacity_up[t] * m.u[c,
1,
t]
dualObj += self.connections[c -
1].capacity_down[t] * m.u[c, 2,
t]
return dualObj
if not options.PRIMAL:
model.obj = Objective(rule=dualObj, sense=minimize)
def primalEqualsDual(m):
return primalObj(m) >= dualObj(m)
if options.DUAL and options.PRIMAL:
model.primalEqualsDual = Constraint(rule=primalEqualsDual)
self.model = model