def runopf(casedata=None, ppopt=None, fname='', solvedcase=''):
"""Runs an optimal power flow.
@see: L{rundcopf}, L{runuopf}
@author: Ray Zimmerman (PSERC Cornell)
"""
## default arguments
if casedata is None:
casedata = join(dirname(__file__), 'case9')
ppopt = ppoption(ppopt)
##----- run the optimal power flow -----
r = opf(casedata, ppopt)
##----- output results -----
if fname:
fd = None
try:
fd = open(fname, "a")
except IOError as detail:
stderr.write("Error opening %s: %s.\n" % (fname, detail))
finally:
if fd is not None:
printpf(r, fd, ppopt)
fd.close()
else:
printpf(r, stdout, ppopt)
## save solved case
if solvedcase:
savecase(solvedcase, r)
return r
def runopf(casedata=None, ppopt=None, fname='', solvedcase=''):
"""Runs an optimal power flow.
@see: L{rundcopf}, L{runuopf}
@author: Ray Zimmerman (PSERC Cornell)
"""
## default arguments
if casedata is None:
casedata = join(dirname(__file__), 'case9')
ppopt = ppoption(ppopt)
##----- run the optimal power flow -----
r = opf(casedata, ppopt)
##----- output results -----
if fname:
fd = None
try:
fd = open(fname, "a")
except IOError as detail:
stderr.write("Error opening %s: %s.\n" % (fname, detail))
finally:
if fd is not None:
printpf(r, fd, ppopt)
fd.close()
else:
printpf(r, stdout, ppopt)
## save solved case
if solvedcase:
savecase(solvedcase, r)
return r
def dcopf(*args, **kw_args):
"""Solves a DC optimal power flow.
This is a simple wrapper function around L{opf} that sets the C{PF_DC}
option to C{True} before calling L{opf}.
See L{opf} for the details of input and output arguments.
@see: L{rundcopf}
@author: Ray Zimmerman (PSERC Cornell)
"""
ppc, ppopt = opf_args2(*args, **kw_args);
ppopt = ppoption(ppopt, PF_DC=1)
return opf(ppc, ppopt)
def dcopf(*args, **kw_args):
"""Solves a DC optimal power flow.
This is a simple wrapper function around L{opf} that sets the C{PF_DC}
option to C{True} before calling L{opf}.
See L{opf} for the details of input and output arguments.
@see: L{rundcopf}
@author: Ray Zimmerman (PSERC Cornell)
"""
ppc, ppopt = opf_args2(*args, **kw_args)
ppopt = ppoption(ppopt, PF_DC=1)
return opf(ppc, ppopt)
def runopf(casedata=None, ppopt=None, fname='', solvedcase=''):
"""Runs an optimal power flow.
@see: L{rundcopf}, L{runuopf}
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
## default arguments
if casedata is None:
casedata = join(dirname(__file__), 'case9')
ppopt = ppoption(ppopt)
##----- run the optimal power flow -----
r = opf(casedata, ppopt)
##----- output results -----
if fname:
fd = None
try:
fd = open(fname, "wb")
except IOError, detail:
stderr.write("Error opening %s: %s.\n" % (fname, detail))
finally:
def uopf(*args):
"""Solves combined unit decommitment / optimal power flow.
Solves a combined unit decommitment and optimal power flow for a single
time period. Uses an algorithm similar to dynamic programming. It proceeds
through a sequence of stages, where stage C{N} has C{N} generators shut
down, starting with C{N=0}. In each stage, it forms a list of candidates
(gens at their C{Pmin} limits) and computes the cost with each one of them
shut down. It selects the least cost case as the starting point for the
next stage, continuing until there are no more candidates to be shut down
or no more improvement can be gained by shutting something down.
If C{verbose} in ppopt (see L{ppoption} is C{true}, it prints progress
info, if it is > 1 it prints the output of each individual opf.
@see: L{opf}, L{runuopf}
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization -----
t0 = time() ## start timer
## process input arguments
ppc, ppopt = opf_args2(*args)
## options
verbose = ppopt["VERBOSE"]
if verbose: ## turn down verbosity one level for calls to opf
ppopt = ppoption(ppopt, VERBOSE=verbose - 1)
##----- do combined unit commitment/optimal power flow -----
## check for sum(Pmin) > total load, decommit as necessary
on = find((ppc["gen"][:, GEN_STATUS] > 0)
& ~isload(ppc["gen"])) ## gens in service
onld = find((ppc["gen"][:, GEN_STATUS] > 0)
& isload(ppc["gen"])) ## disp loads in serv
load_capacity = sum(ppc["bus"][:, PD]) - sum(
ppc["gen"][onld, PMIN]) ## total load capacity
Pmin = ppc["gen"][on, PMIN]
while sum(Pmin) > load_capacity:
## shut down most expensive unit
avgPmincost = totcost(ppc["gencost"][on, :], Pmin) / Pmin
_, i = fairmax(avgPmincost) ## pick one with max avg cost at Pmin
i = on[i] ## convert to generator index
if verbose:
print(
'Shutting down generator %d so all Pmin limits can be satisfied.\n'
% i)
## set generation to zero
ppc["gen"][i, [PG, QG, GEN_STATUS]] = 0
## update minimum gen capacity
on = find((ppc["gen"][:, GEN_STATUS] > 0)
& ~isload(ppc["gen"])) ## gens in service
Pmin = ppc["gen"][on, PMIN]
## run initial opf
results = opf(ppc, ppopt)
## best case so far
results1 = deepcopy(results)
## best case for this stage (ie. with n gens shut down, n=0,1,2 ...)
results0 = deepcopy(results1)
ppc["bus"] = results0["bus"].copy(
) ## use these V as starting point for OPF
while True:
## get candidates for shutdown
candidates = find((results0["gen"][:, MU_PMIN] > 0)
& (results0["gen"][:, PMIN] > 0))
if len(candidates) == 0:
break
## do not check for further decommitment unless we
## see something better during this stage
done = True
for k in candidates:
## start with best for this stage
ppc["gen"] = results0["gen"].copy()
## shut down gen k
ppc["gen"][k, [PG, QG, GEN_STATUS]] = 0
## run opf
results = opf(ppc, ppopt)
## something better?
if results['success'] and (results["f"] < results1["f"]):
results1 = deepcopy(results)
k1 = k
done = False ## make sure we check for further decommitment
if done:
## decommits at this stage did not help, so let's quit
break
else:
## shutting something else down helps, so let's keep going
if verbose:
print('Shutting down generator %d.\n' % k1)
results0 = deepcopy(results1)
ppc["bus"] = results0["bus"].copy(
) ## use these V as starting point for OPF
## compute elapsed time
et = time() - t0
## finish preparing output
results0['et'] = et
return results0
def t_opf_ipopt(quiet=False):
"""Tests for IPOPT-based AC optimal power flow.
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
num_tests = 101
t_begin(num_tests, quiet)
tdir = dirname(__file__)
casefile = join(tdir, 't_case9_opf')
verbose = 0#not quiet
t0 = 'IPOPT : '
ppopt = ppoption(OPF_VIOLATION=1e-6, PDIPM_GRADTOL=1e-8,
PDIPM_COMPTOL=1e-8, PDIPM_COSTTOL=1e-9)
ppopt = ppoption(ppopt, OUT_ALL=0, VERBOSE=verbose, OPF_ALG=580)
## set up indices
ib_data = r_[arange(BUS_AREA + 1), arange(BASE_KV, VMIN + 1)]
ib_voltage = arange(VM, VA + 1)
ib_lam = arange(LAM_P, LAM_Q + 1)
ib_mu = arange(MU_VMAX, MU_VMIN + 1)
ig_data = r_[[GEN_BUS, QMAX, QMIN], arange(MBASE, APF + 1)]
ig_disp = array([PG, QG, VG])
ig_mu = arange(MU_PMAX, MU_QMIN + 1)
ibr_data = arange(ANGMAX + 1)
ibr_flow = arange(PF, QT + 1)
ibr_mu = array([MU_SF, MU_ST])
ibr_angmu = array([MU_ANGMIN, MU_ANGMAX])
## get solved AC power flow case from MAT-file
soln9_opf = loadmat(join(tdir, 'soln9_opf.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf['bus_soln']
gen_soln = soln9_opf['gen_soln']
branch_soln = soln9_opf['branch_soln']
f_soln = soln9_opf['f_soln'][0]
## run OPF
t = t0
r = runopf(casefile, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
## run with automatic conversion of single-block pwl to linear costs
t = ''.join([t0, '(single-block PWL) : '])
ppc = loadcase(casefile)
ppc['gencost'][2, NCOST] = 2
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
xr = r_[r['var']['val']['Va'], r['var']['val']['Vm'], r['var']['val']['Pg'],
r['var']['val']['Qg'], 0, r['var']['val']['y']]
t_is(r['x'], xr, 8, [t, 'check on raw x returned from OPF'])
## get solved AC power flow case from MAT-file
soln9_opf_Plim = loadmat(join(tdir, 'soln9_opf_Plim.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_Plim['bus_soln']
gen_soln = soln9_opf_Plim['gen_soln']
branch_soln = soln9_opf_Plim['branch_soln']
f_soln = soln9_opf_Plim['f_soln'][0]
## run OPF with active power line limits
t = ''.join([t0, '(P line lim) : '])
ppopt1 = ppoption(ppopt, OPF_FLOW_LIM=1)
r = runopf(casefile, ppopt1)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
##----- test OPF with quadratic gen costs moved to generalized costs -----
ppc = loadcase(casefile)
ppc['gencost'] = array([
[2, 1500, 0, 3, 0.11, 5, 0],
[2, 2000, 0, 3, 0.085, 1.2, 0],
[2, 3000, 0, 3, 0.1225, 1, 0]
])
r = runopf(ppc, ppopt)
bus_soln, gen_soln, branch_soln, f_soln, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
branch_soln = branch_soln[:, :MU_ST + 1]
A = None
l = array([])
u = array([])
nb = ppc['bus'].shape[0] # number of buses
ng = ppc['gen'].shape[0] # number of gens
thbas = 0; thend = thbas + nb
vbas = thend; vend = vbas + nb
pgbas = vend; pgend = pgbas + ng
# qgbas = pgend; qgend = qgbas + ng
nxyz = 2 * nb + 2 * ng
N = sparse((ppc['baseMVA'] * ones(ng), (arange(ng), arange(pgbas, pgend))), (ng, nxyz))
fparm = ones((ng, 1)) * array([[1, 0, 0, 1]])
ix = argsort(ppc['gen'][:, 0])
H = 2 * spdiags(ppc['gencost'][ix, 4], 0, ng, ng, 'csr')
Cw = ppc['gencost'][ix, 5]
ppc['gencost'][:, 4:7] = 0
## run OPF with quadratic gen costs moved to generalized costs
t = ''.join([t0, 'w/quadratic generalized gen cost : '])
r = opf(ppc, A, l, u, ppopt, N, fparm, H, Cw)
f, bus, gen, branch, success = \
r['f'], r['bus'], r['gen'], r['branch'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(r['cost']['usr'], f, 12, [t, 'user cost'])
##----- run OPF with extra linear user constraints & costs -----
## single new z variable constrained to be greater than or equal to
## deviation from 1 pu voltage at bus 1, linear cost on this z
## get solved AC power flow case from MAT-file
soln9_opf_extras1 = loadmat(join(tdir, 'soln9_opf_extras1.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_extras1['bus_soln']
gen_soln = soln9_opf_extras1['gen_soln']
branch_soln = soln9_opf_extras1['branch_soln']
f_soln = soln9_opf_extras1['f_soln'][0]
row = [0, 0, 1, 1]
col = [9, 24, 9, 24]
A = sparse(([-1, 1, 1, 1], (row, col)), (2, 25))
u = array([Inf, Inf])
l = array([-1, 1])
N = sparse(([1], ([0], [24])), (1, 25)) ## new z variable only
fparm = array([[1, 0, 0, 1]]) ## w = r = z
H = sparse((1, 1)) ## no quadratic term
Cw = array([100.0])
t = ''.join([t0, 'w/extra constraints & costs 1 : '])
r = opf(casefile, A, l, u, ppopt, N, fparm, H, Cw)
f, bus, gen, branch, success = \
r['f'], r['bus'], r['gen'], r['branch'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(r['var']['val']['z'], 0.025419, 6, [t, 'user variable'])
t_is(r['cost']['usr'], 2.5419, 4, [t, 'user cost'])
##----- test OPF with capability curves -----
ppc = loadcase(join(tdir, 't_case9_opfv2'))
## remove angle diff limits
ppc['branch'][0, ANGMAX] = 360
ppc['branch'][8, ANGMIN] = -360
## get solved AC power flow case from MAT-file
soln9_opf_PQcap = loadmat(join(tdir, 'soln9_opf_PQcap.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_PQcap['bus_soln']
gen_soln = soln9_opf_PQcap['gen_soln']
branch_soln = soln9_opf_PQcap['branch_soln']
f_soln = soln9_opf_PQcap['f_soln'][0]
## run OPF with capability curves
t = ''.join([t0, 'w/capability curves : '])
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
##----- test OPF with angle difference limits -----
ppc = loadcase(join(tdir, 't_case9_opfv2'))
## remove capability curves
ppc['gen'][ix_(arange(1, 3),
[PC1, PC2, QC1MIN, QC1MAX, QC2MIN, QC2MAX])] = zeros((2, 6))
## get solved AC power flow case from MAT-file
soln9_opf_ang = loadmat(join(tdir, 'soln9_opf_ang.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_ang['bus_soln']
gen_soln = soln9_opf_ang['gen_soln']
branch_soln = soln9_opf_ang['branch_soln']
f_soln = soln9_opf_ang['f_soln'][0]
## run OPF with angle difference limits
t = ''.join([t0, 'w/angle difference limits : '])
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 1, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(branch[:, ibr_angmu ], branch_soln[:, ibr_angmu ], 2, [t, 'branch angle mu'])
##----- test OPF with ignored angle difference limits -----
## get solved AC power flow case from MAT-file
soln9_opf = loadmat(join(tdir, 'soln9_opf.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf['bus_soln']
gen_soln = soln9_opf['gen_soln']
branch_soln = soln9_opf['branch_soln']
f_soln = soln9_opf['f_soln'][0]
## run OPF with ignored angle difference limits
t = ''.join([t0, 'w/ignored angle difference limits : '])
ppopt1 = ppoption(ppopt, OPF_IGNORE_ANG_LIM=1)
r = runopf(ppc, ppopt1)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
## ang limits are not in this solution data, so let's remove them
branch[0, ANGMAX] = 360
branch[8, ANGMIN] = -360
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_end()
def uopf(*args):
"""Solves combined unit decommitment / optimal power flow.
Solves a combined unit decommitment and optimal power flow for a single
time period. Uses an algorithm similar to dynamic programming. It proceeds
through a sequence of stages, where stage C{N} has C{N} generators shut
down, starting with C{N=0}. In each stage, it forms a list of candidates
(gens at their C{Pmin} limits) and computes the cost with each one of them
shut down. It selects the least cost case as the starting point for the
next stage, continuing until there are no more candidates to be shut down
or no more improvement can be gained by shutting something down.
If C{verbose} in ppopt (see L{ppoption} is C{true}, it prints progress
info, if it is > 1 it prints the output of each individual opf.
@see: L{opf}, L{runuopf}
@author: Ray Zimmerman (PSERC Cornell)
@author: Richard Lincoln
"""
##----- initialization -----
t0 = time() ## start timer
## process input arguments
ppc, ppopt = opf_args2(*args)
## options
verbose = ppopt["VERBOSE"]
if verbose: ## turn down verbosity one level for calls to opf
ppopt = ppoption(ppopt, VERBOSE=verbose - 1)
##----- do combined unit commitment/optimal power flow -----
## check for sum(Pmin) > total load, decommit as necessary
on = find( (ppc["gen"][:, GEN_STATUS] > 0) & ~isload(ppc["gen"]) ) ## gens in service
onld = find( (ppc["gen"][:, GEN_STATUS] > 0) & isload(ppc["gen"]) ) ## disp loads in serv
load_capacity = sum(ppc["bus"][:, PD]) - sum(ppc["gen"][onld, PMIN]) ## total load capacity
Pmin = ppc["gen"][on, PMIN]
while sum(Pmin) > load_capacity:
## shut down most expensive unit
avgPmincost = totcost(ppc["gencost"][on, :], Pmin) / Pmin
_, i = fairmax(avgPmincost) ## pick one with max avg cost at Pmin
i = on[i] ## convert to generator index
if verbose:
print('Shutting down generator %d so all Pmin limits can be satisfied.\n' % i)
## set generation to zero
ppc["gen"][i, [PG, QG, GEN_STATUS]] = 0
## update minimum gen capacity
on = find( (ppc["gen"][:, GEN_STATUS] > 0) & ~isload(ppc["gen"]) ) ## gens in service
Pmin = ppc["gen"][on, PMIN]
## run initial opf
results = opf(ppc, ppopt)
## best case so far
results1 = deepcopy(results)
## best case for this stage (ie. with n gens shut down, n=0,1,2 ...)
results0 = deepcopy(results1)
ppc["bus"] = results0["bus"].copy() ## use these V as starting point for OPF
while True:
## get candidates for shutdown
candidates = find((results0["gen"][:, MU_PMIN] > 0) & (results0["gen"][:, PMIN] > 0))
if len(candidates) == 0:
break
## do not check for further decommitment unless we
## see something better during this stage
done = True
for k in candidates:
## start with best for this stage
ppc["gen"] = results0["gen"].copy()
## shut down gen k
ppc["gen"][k, [PG, QG, GEN_STATUS]] = 0
## run opf
results = opf(ppc, ppopt)
## something better?
if results['success'] and (results["f"] < results1["f"]):
results1 = deepcopy(results)
k1 = k
done = False ## make sure we check for further decommitment
if done:
## decommits at this stage did not help, so let's quit
break
else:
## shutting something else down helps, so let's keep going
if verbose:
print('Shutting down generator %d.\n' % k1)
results0 = deepcopy(results1)
ppc["bus"] = results0["bus"].copy() ## use these V as starting point for OPF
## compute elapsed time
et = time() - t0
## finish preparing output
results0['et'] = et
return results0
def t_opf_pips(quiet=False):
"""Tests for PIPS-based AC optimal power flow.
@author: Ray Zimmerman (PSERC Cornell)
"""
num_tests = 101
t_begin(num_tests, quiet)
tdir = dirname(__file__)
casefile = join(tdir, 't_case9_opf')
verbose = 0#not quiet
t0 = 'PIPS : '
ppopt = ppoption(OPF_VIOLATION=1e-6, PDIPM_GRADTOL=1e-8,
PDIPM_COMPTOL=1e-8, PDIPM_COSTTOL=1e-9)
ppopt = ppoption(ppopt, OUT_ALL=0, VERBOSE=verbose, OPF_ALG=560)
## set up indices
ib_data = r_[arange(BUS_AREA + 1), arange(BASE_KV, VMIN + 1)]
ib_voltage = arange(VM, VA + 1)
ib_lam = arange(LAM_P, LAM_Q + 1)
ib_mu = arange(MU_VMAX, MU_VMIN + 1)
ig_data = r_[[GEN_BUS, QMAX, QMIN], arange(MBASE, APF + 1)]
ig_disp = array([PG, QG, VG])
ig_mu = arange(MU_PMAX, MU_QMIN + 1)
ibr_data = arange(ANGMAX + 1)
ibr_flow = arange(PF, QT + 1)
ibr_mu = array([MU_SF, MU_ST])
ibr_angmu = array([MU_ANGMIN, MU_ANGMAX])
## get solved AC power flow case from MAT-file
soln9_opf = loadmat(join(tdir, 'soln9_opf.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf['bus_soln']
gen_soln = soln9_opf['gen_soln']
branch_soln = soln9_opf['branch_soln']
f_soln = soln9_opf['f_soln'][0]
## run OPF
t = t0
r = runopf(casefile, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
## run with automatic conversion of single-block pwl to linear costs
t = ''.join([t0, '(single-block PWL) : '])
ppc = loadcase(casefile)
ppc['gencost'][2, NCOST] = 2
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
xr = r_[r['var']['val']['Va'], r['var']['val']['Vm'], r['var']['val']['Pg'],
r['var']['val']['Qg'], 0, r['var']['val']['y']]
t_is(r['x'], xr, 8, [t, 'check on raw x returned from OPF'])
## get solved AC power flow case from MAT-file
soln9_opf_Plim = loadmat(join(tdir, 'soln9_opf_Plim.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_Plim['bus_soln']
gen_soln = soln9_opf_Plim['gen_soln']
branch_soln = soln9_opf_Plim['branch_soln']
f_soln = soln9_opf_Plim['f_soln'][0]
## run OPF with active power line limits
t = ''.join([t0, '(P line lim) : '])
ppopt1 = ppoption(ppopt, OPF_FLOW_LIM=1)
r = runopf(casefile, ppopt1)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
##----- test OPF with quadratic gen costs moved to generalized costs -----
ppc = loadcase(casefile)
ppc['gencost'] = array([
[2, 1500, 0, 3, 0.11, 5, 0],
[2, 2000, 0, 3, 0.085, 1.2, 0],
[2, 3000, 0, 3, 0.1225, 1, 0]
])
r = runopf(ppc, ppopt)
bus_soln, gen_soln, branch_soln, f_soln, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
branch_soln = branch_soln[:, :MU_ST + 1]
A = None
l = array([])
u = array([])
nb = ppc['bus'].shape[0] # number of buses
ng = ppc['gen'].shape[0] # number of gens
thbas = 0; thend = thbas + nb
vbas = thend; vend = vbas + nb
pgbas = vend; pgend = pgbas + ng
# qgbas = pgend; qgend = qgbas + ng
nxyz = 2 * nb + 2 * ng
N = sparse((ppc['baseMVA'] * ones(ng), (arange(ng), arange(pgbas, pgend))), (ng, nxyz))
fparm = ones((ng, 1)) * array([[1, 0, 0, 1]])
ix = argsort(ppc['gen'][:, 0])
H = 2 * spdiags(ppc['gencost'][ix, 4], 0, ng, ng, 'csr')
Cw = ppc['gencost'][ix, 5]
ppc['gencost'][:, 4:7] = 0
## run OPF with quadratic gen costs moved to generalized costs
t = ''.join([t0, 'w/quadratic generalized gen cost : '])
r = opf(ppc, A, l, u, ppopt, N, fparm, H, Cw)
f, bus, gen, branch, success = \
r['f'], r['bus'], r['gen'], r['branch'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(r['cost']['usr'], f, 12, [t, 'user cost'])
##----- run OPF with extra linear user constraints & costs -----
## single new z variable constrained to be greater than or equal to
## deviation from 1 pu voltage at bus 1, linear cost on this z
## get solved AC power flow case from MAT-file
soln9_opf_extras1 = loadmat(join(tdir, 'soln9_opf_extras1.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_extras1['bus_soln']
gen_soln = soln9_opf_extras1['gen_soln']
branch_soln = soln9_opf_extras1['branch_soln']
f_soln = soln9_opf_extras1['f_soln'][0]
row = [0, 0, 1, 1]
col = [9, 24, 9, 24]
A = sparse(([-1, 1, 1, 1], (row, col)), (2, 25))
u = array([Inf, Inf])
l = array([-1, 1])
N = sparse(([1], ([0], [24])), (1, 25)) ## new z variable only
fparm = array([[1, 0, 0, 1]]) ## w = r = z
H = sparse((1, 1)) ## no quadratic term
Cw = array([100.0])
t = ''.join([t0, 'w/extra constraints & costs 1 : '])
r = opf(casefile, A, l, u, ppopt, N, fparm, H, Cw)
f, bus, gen, branch, success = \
r['f'], r['bus'], r['gen'], r['branch'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(r['var']['val']['z'], 0.025419, 6, [t, 'user variable'])
t_is(r['cost']['usr'], 2.5419, 4, [t, 'user cost'])
##----- test OPF with capability curves -----
ppc = loadcase(join(tdir, 't_case9_opfv2'))
## remove angle diff limits
ppc['branch'][0, ANGMAX] = 360
ppc['branch'][8, ANGMIN] = -360
## get solved AC power flow case from MAT-file
soln9_opf_PQcap = loadmat(join(tdir, 'soln9_opf_PQcap.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_PQcap['bus_soln']
gen_soln = soln9_opf_PQcap['gen_soln']
branch_soln = soln9_opf_PQcap['branch_soln']
f_soln = soln9_opf_PQcap['f_soln'][0]
## run OPF with capability curves
t = ''.join([t0, 'w/capability curves : '])
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
##----- test OPF with angle difference limits -----
ppc = loadcase(join(tdir, 't_case9_opfv2'))
## remove capability curves
ppc['gen'][ix_(arange(1, 3),
[PC1, PC2, QC1MIN, QC1MAX, QC2MIN, QC2MAX])] = zeros((2, 6))
## get solved AC power flow case from MAT-file
soln9_opf_ang = loadmat(join(tdir, 'soln9_opf_ang.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf_ang['bus_soln']
gen_soln = soln9_opf_ang['gen_soln']
branch_soln = soln9_opf_ang['branch_soln']
f_soln = soln9_opf_ang['f_soln'][0]
## run OPF with angle difference limits
t = ''.join([t0, 'w/angle difference limits : '])
r = runopf(ppc, ppopt)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 1, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_is(branch[:, ibr_angmu ], branch_soln[:, ibr_angmu ], 2, [t, 'branch angle mu'])
##----- test OPF with ignored angle difference limits -----
## get solved AC power flow case from MAT-file
soln9_opf = loadmat(join(tdir, 'soln9_opf.mat'), struct_as_record=True)
## defines bus_soln, gen_soln, branch_soln, f_soln
bus_soln = soln9_opf['bus_soln']
gen_soln = soln9_opf['gen_soln']
branch_soln = soln9_opf['branch_soln']
f_soln = soln9_opf['f_soln'][0]
## run OPF with ignored angle difference limits
t = ''.join([t0, 'w/ignored angle difference limits : '])
ppopt1 = ppoption(ppopt, OPF_IGNORE_ANG_LIM=1)
r = runopf(ppc, ppopt1)
bus, gen, branch, f, success = \
r['bus'], r['gen'], r['branch'], r['f'], r['success']
## ang limits are not in this solution data, so let's remove them
branch[0, ANGMAX] = 360
branch[8, ANGMIN] = -360
t_ok(success, [t, 'success'])
t_is(f, f_soln, 3, [t, 'f'])
t_is( bus[:, ib_data ], bus_soln[:, ib_data ], 10, [t, 'bus data'])
t_is( bus[:, ib_voltage], bus_soln[:, ib_voltage], 3, [t, 'bus voltage'])
t_is( bus[:, ib_lam ], bus_soln[:, ib_lam ], 3, [t, 'bus lambda'])
t_is( bus[:, ib_mu ], bus_soln[:, ib_mu ], 2, [t, 'bus mu'])
t_is( gen[:, ig_data ], gen_soln[:, ig_data ], 10, [t, 'gen data'])
t_is( gen[:, ig_disp ], gen_soln[:, ig_disp ], 3, [t, 'gen dispatch'])
t_is( gen[:, ig_mu ], gen_soln[:, ig_mu ], 3, [t, 'gen mu'])
t_is(branch[:, ibr_data ], branch_soln[:, ibr_data ], 10, [t, 'branch data'])
t_is(branch[:, ibr_flow ], branch_soln[:, ibr_flow ], 3, [t, 'branch flow'])
t_is(branch[:, ibr_mu ], branch_soln[:, ibr_mu ], 2, [t, 'branch mu'])
t_end()
