def t_hasPQcap(quiet=False):
"""Tests for C{hasPQcap}.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
t_begin(4, quiet)
## 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
gen = array([
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, 0, 12, 0, 2, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -15, 12, -15, 2, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 0, -2, 0, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 15, -2, 15, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 12, -2, 2, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, 0, 12, 0, 8, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -15, 12, -15, 8, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 0, -8, 0, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 15, -8, 15, 0, 0, 0, 0, 0],
[1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 12, -8, 8, 0, 0, 0, 0, 0]
])
t = 'hasPQcap(gen)'
t_is(hasPQcap(gen), [0,1,1,1,1,1,1,0,1,0,0], 12, t)
t = 'hasPQcap(gen, \'B\')'
t_is(hasPQcap(gen, 'B'), [0,1,1,1,1,1,1,0,1,0,0], 12, t)
t = 'hasPQcap(gen, \'U\')'
t_is(hasPQcap(gen, 'U'), [0,1,1,1,0,1,0,0,1,0,0], 12, t)
t = 'hasPQcap(gen, \'L\')'
t_is(hasPQcap(gen, 'L'), [0,1,0,1,1,1,1,0,0,0,0], 12, t)
t_end()
def t_hasPQcap(quiet=False):
"""Tests for C{hasPQcap}.
@author: Ray Zimmerman (PSERC Cornell)
"""
t_begin(4, quiet)
## 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
gen = array([[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
], [
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, 0, 12, 0, 2, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20,
-15, 12, -15, 2, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 0, -2, 0,
0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 15, -2,
15, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 12, -2,
2, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, 0, 12, 0, 8,
0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20,
-15, 12, -15, 8, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 0, -8, 0,
0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 15, -8,
15, 0, 0, 0, 0, 0
],
[
1, 10, 0, 10, -10, 1, 100, 1, 10, 2, 0, 20, -12, 12, -8,
8, 0, 0, 0, 0, 0
]])
t = 'hasPQcap(gen)'
t_is(hasPQcap(gen), [0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0], 12, t)
t = 'hasPQcap(gen, \'B\')'
t_is(hasPQcap(gen, 'B'), [0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0], 12, t)
t = 'hasPQcap(gen, \'U\')'
t_is(hasPQcap(gen, 'U'), [0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0], 12, t)
t = 'hasPQcap(gen, \'L\')'
t_is(hasPQcap(gen, 'L'), [0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0], 12, t)
t_end()
def makeApq(baseMVA, gen):
"""Construct linear constraints for generator capability curves.
Constructs the parameters for the following linear constraints
implementing trapezoidal generator capability curves, where
C{Pg} and C{Qg} are the real and reactive generator injections::
Apqh * [Pg, Qg] <= ubpqh
Apql * [Pg, Qg] <= ubpql
C{data} constains additional information as shown below.
Example::
Apqh, ubpqh, Apql, ubpql, data = makeApq(baseMVA, gen)
data['h'] [Qc1max-Qc2max, Pc2-Pc1]
data['l'] [Qc2min-Qc1min, Pc1-Pc2]
data['ipqh'] indices of gens with general PQ cap curves (upper)
data['ipql'] indices of gens with general PQ cap curves (lower)
@author: Ray Zimmerman (PSERC Cornell)
@author: Carlos E. Murillo-Sanchez (PSERC Cornell & Universidad
Autonoma de Manizales)
@author: Richard Lincoln
"""
data = {}
## data dimensions
ng = gen.shape[0] ## number of dispatchable injections
## which generators require additional linear constraints
## (in addition to simple box constraints) on (Pg,Qg) to correctly
## model their PQ capability curves
ipqh = find(hasPQcap(gen, 'U'))
ipql = find(hasPQcap(gen, 'L'))
npqh = ipqh.shape[0] ## number of general PQ capability curves (upper)
npql = ipql.shape[0] ## number of general PQ capability curves (lower)
## make Apqh if there is a need to add general PQ capability curves
## use normalized coefficient rows so multipliers have right scaling
## in $$/pu
if npqh > 0:
data["h"] = c_[gen[ipqh, QC1MAX] - gen[ipqh, QC2MAX],
gen[ipqh, PC2] - gen[ipqh, PC1]]
ubpqh = data["h"][:, 0] * gen[ipqh, PC1] + \
data["h"][:, 1] * gen[ipqh, QC1MAX]
for i in range(npqh):
tmp = linalg.norm(data["h"][i, :])
data["h"][i, :] = data["h"][i, :] / tmp
ubpqh[i] = ubpqh[i] / tmp
Apqh = sparse((data["h"].flatten('F'),
(r_[arange(npqh), arange(npqh)], r_[ipqh, ipqh + ng])),
(npqh, 2 * ng))
ubpqh = ubpqh / baseMVA
else:
data["h"] = array([])
Apqh = zeros((0, 2 * ng))
ubpqh = array([])
## similarly Apql
if npql > 0:
data["l"] = c_[gen[ipql, QC2MIN] - gen[ipql, QC1MIN],
gen[ipql, PC1] - gen[ipql, PC2]]
ubpql = data["l"][:, 0] * gen[ipql, PC1] + \
data["l"][:, 1] * gen[ipql, QC1MIN]
for i in range(npql):
tmp = linalg.norm(data["l"][i, :])
data["l"][i, :] = data["l"][i, :] / tmp
ubpql[i] = ubpql[i] / tmp
Apql = sparse((data["l"].flatten('F'),
(r_[arange(npql), arange(npql)], r_[ipql, ipql + ng])),
(npql, 2 * ng))
ubpql = ubpql / baseMVA
else:
data["l"] = array([])
Apql = zeros((0, 2 * ng))
ubpql = array([])
data["ipql"] = ipql
data["ipqh"] = ipqh
return Apqh, ubpqh, Apql, ubpql, data
def makeApq(baseMVA, gen):
"""Construct linear constraints for generator capability curves.
Constructs the parameters for the following linear constraints
implementing trapezoidal generator capability curves, where
C{Pg} and C{Qg} are the real and reactive generator injections::
Apqh * [Pg, Qg] <= ubpqh
Apql * [Pg, Qg] <= ubpql
C{data} constains additional information as shown below.
Example::
Apqh, ubpqh, Apql, ubpql, data = makeApq(baseMVA, gen)
data['h'] [Qc1max-Qc2max, Pc2-Pc1]
data['l'] [Qc2min-Qc1min, Pc1-Pc2]
data['ipqh'] indices of gens with general PQ cap curves (upper)
data['ipql'] indices of gens with general PQ cap curves (lower)
@author: Ray Zimmerman (PSERC Cornell)
@author: Carlos E. Murillo-Sanchez (PSERC Cornell & Universidad
Autonoma de Manizales)
"""
data = {}
## data dimensions
ng = gen.shape[0] ## number of dispatchable injections
## which generators require additional linear constraints
## (in addition to simple box constraints) on (Pg,Qg) to correctly
## model their PQ capability curves
ipqh = find( hasPQcap(gen, 'U') )
ipql = find( hasPQcap(gen, 'L') )
npqh = ipqh.shape[0] ## number of general PQ capability curves (upper)
npql = ipql.shape[0] ## number of general PQ capability curves (lower)
## make Apqh if there is a need to add general PQ capability curves
## use normalized coefficient rows so multipliers have right scaling
## in $$/pu
if npqh > 0:
data["h"] = c_[gen[ipqh, QC1MAX] - gen[ipqh, QC2MAX],
gen[ipqh, PC2] - gen[ipqh, PC1]]
ubpqh = data["h"][:, 0] * gen[ipqh, PC1] + \
data["h"][:, 1] * gen[ipqh, QC1MAX]
for i in range(npqh):
tmp = linalg.norm(data["h"][i, :])
data["h"][i, :] = data["h"][i, :] / tmp
ubpqh[i] = ubpqh[i] / tmp
Apqh = sparse((data["h"].flatten('F'),
(r_[arange(npqh), arange(npqh)], r_[ipqh, ipqh+ng])),
(npqh, 2*ng))
ubpqh = ubpqh / baseMVA
else:
data["h"] = array([])
Apqh = zeros((0, 2*ng))
ubpqh = array([])
## similarly Apql
if npql > 0:
data["l"] = c_[gen[ipql, QC2MIN] - gen[ipql, QC1MIN],
gen[ipql, PC1] - gen[ipql, PC2]]
ubpql = data["l"][:, 0] * gen[ipql, PC1] + \
data["l"][:, 1] * gen[ipql, QC1MIN]
for i in range(npql):
tmp = linalg.norm(data["l"][i, :])
data["l"][i, :] = data["l"][i, :] / tmp
ubpql[i] = ubpql[i] / tmp
Apql = sparse((data["l"].flatten('F'),
(r_[arange(npql), arange(npql)], r_[ipql, ipql+ng])),
(npql, 2*ng))
ubpql = ubpql / baseMVA
else:
data["l"] = array([])
Apql = zeros((0, 2*ng))
ubpql = array([])
data["ipql"] = ipql
data["ipqh"] = ipqh
return Apqh, ubpqh, Apql, ubpql, data
