def test_pm_tnep_cigre_dc():
# get the grid
net = cigre_grid()
# add the possible new lines
define_possible_new_lines(net)
# check if max line loading percent is violated (should be)
pp.runpp(net)
print("Max line loading prior to optimization:")
print(net.res_line.loading_percent.max())
assert np.any(net["res_line"].loc[:, "loading_percent"] >
net["line"].loc[:, "max_loading_percent"])
# run power models tnep optimization
pp.runpm_tnep(net, pm_solver="juniper", pm_model="DCPPowerModel"
) # gurobi is a better option, but not for travis
# print the information about the newly built lines
print("These lines are to be built:")
print(net["res_ne_line"])
# set lines to be built in service
lines_to_built = net["res_ne_line"].loc[net["res_ne_line"].loc[:, "built"],
"built"].index
net["line"].loc[lines_to_built, "in_service"] = True
# run a power flow calculation again and check if max_loading percent is still violated
pp.runpp(net)
# check max line loading results
assert not np.any(net["res_line"].loc[:, "loading_percent"] >
net["line"].loc[:, "max_loading_percent"])
print("Max line loading after the optimization:")
print(net.res_line.loading_percent.max())
def test_pm_tnep():
net = tnep_grid()
# check if max line loading percent is violated (should be)
pp.runpp(net)
assert np.any(net["res_line"].loc[:, "loading_percent"] >
net["line"].loc[:, "max_loading_percent"])
# run power models tnep optimization
pp.runpm_tnep(net, pm_model="ACPPowerModel")
# set lines to be built in service
lines_to_built = net["res_ne_line"].loc[net["res_ne_line"].loc[:, "built"], "built"].index
net["line"].loc[lines_to_built, "in_service"] = True
# run a power flow calculation again and check if max_loading percent is still violated
pp.runpp(net)
# check max line loading results
assert not np.any(net["res_line"].loc[:, "loading_percent"] >
net["line"].loc[:, "max_loading_percent"])
def run_pm_tnep(net, **settings):
logger.debug("Starting PowerModels.jl TNEP:")
lines = set()
# these steps are the decreasing line loading limits so that we get different measures
# we need this becaus: DCP 80% I_max != DCP 90% I_max
steps = [.9, .95, 1.]
step1_sol = []
# time limits for PowerModels.jl solver
pm_time_limits = {"pm_time_limit": settings["pm_time_limit"],
"pm_nl_time_limit": settings["pm_nl_time_limit"],
"pm_mip_time_limit": settings["pm_mip_time_limit"]}
for step in steps:
logger.debug(f"starting PowerModels.jl TNEP with with max. line loading {step}")
# reduce the max. line loading
net.line.loc[:, "max_loading_percent"] = settings["i_lim"] * step
net.ne_line.loc[:, "max_loading_percent"] = settings["i_lim"] * step
try:
# runs PowerModels.jl TNEP
pp.runpm_tnep(net, pm_model=settings["model"], pm_solver=settings["solver"], pm_log_level=1,
pm_time_limits=pm_time_limits)
except:
logger.error("power models failed.")
continue
# the PowerModels.jl solution
sol = net["res_ne_line"].loc[net["res_ne_line"].loc[:, "built"], "built"].index
if step == 1.:
# 90% solution of PowerModels (probably not AC feasible)
step1_sol = sol
# all lines 'recommended' by the TNEP opt
lines |= set(list(sol))
# reset the limits to the original value
net.ne_line.loc[:, "max_loading_percent"] = settings["i_lim"]
net.line.loc[:, "max_loading_percent"] = settings["i_lim"]
if len(step1_sol):
# check if the best PowerModels.jl solution is good
check_pm_solution(net, step1_sol)
return lines, step1_sol