def main(args):
generators, loads, _, times, _, data = parsedir()
generators = [gen for gen in generators if gen.is_controllable]
gen_data = data["generators"]
if args["min"] == 0:
args["min"] = 1.1 * gen_data.pmin.sum()
if args["max"] == 0:
args["max"] = 0.99 * gen_data.pmax.sum()
load_values = np.arange(args["min"], args["max"], args["interval"])
results = DataFrame(columns=["prices", "committed", "last_committed"],
index=load_values)
committed_gen_names = Index([])
for load_val in load_values:
print(load_val)
loads_times = make_loads_times(Pd=load_val)
power_system, times = solve_problem(generators,
do_reset_config=False,
**loads_times)
t = times[0]
results.loc[load_val, "prices"] = power_system.buses[0].price(t)
statuses = Series(
dict([(gen.name, gen.status(t).value)
for gen in power_system.generators()]))
results.loc[load_val, "committed"] = statuses.sum()
results.loc[load_val, "last_committed"] = statuses[
statuses == 1].index.difference(committed_gen_names)
committed_gen_names = statuses[statuses == 1].index
if (load_values[-1] == 0.99 *
gen_data.pmax.sum()) and (statuses.sum() != len(generators)):
print("warning: uncommitted generation:")
print((gen_data.set_index("name").loc[statuses[statuses == 0].index]))
results.to_csv(joindir(user_config.directory, "ed_sweep.csv"))
if args["hide_units_committed"]:
ax = results.prices.plot(drawstyle="steps")
else:
ax = results[["prices", "committed"]].plot(drawstyle="steps",
secondary_y=["committed"])
ax.right_ax.set_ylabel("Units committed")
ax.set_xlabel("System Load (MW)")
ax.set_ylabel("Estimated System Price ($/MWh)")
plt.savefig(joindir(user_config.directory, "ed_sweep.png"))
def main(args):
generators, loads, _, times, _, data = parsedir()
generators = filter(lambda gen: gen.is_controllable, generators)
gen_data = data['generators']
if args['min'] == 0:
args['min'] = 1.1 * gen_data.pmin.sum()
if args['max'] == 0:
args['max'] = 0.99 * gen_data.pmax.sum()
load_values = np.arange(args['min'], args['max'], args['interval'])
results = DataFrame(columns=['prices', 'committed', 'last_committed'],
index=load_values)
committed_gen_names = Index([])
for load_val in load_values:
print load_val
loads_times = make_loads_times(Pd=load_val)
power_system, times = solve_problem(generators,
do_reset_config=False,
**loads_times)
t = times[0]
results.ix[load_val, 'prices'] = power_system.buses[0].price(t)
statuses = Series(
dict([(gen.name, gen.status(t).value)
for gen in power_system.generators()]))
results.ix[load_val, 'committed'] = statuses.sum()
results.ix[load_val, 'last_committed'] = \
statuses[statuses == 1].index.diff(committed_gen_names)
committed_gen_names = statuses[statuses == 1].index
if (load_values[-1] == 0.99 * gen_data.pmax.sum()) and \
(statuses.sum() != len(generators)):
print('warning: uncommitted generation:')
print(gen_data.set_index('name').ix[statuses[statuses == 0].index])
results.to_csv(joindir(user_config.directory, 'ed_sweep.csv'))
if args['hide_units_committed']:
ax = results.prices.plot(drawstyle='steps')
else:
ax = results[['prices', 'committed']].plot(drawstyle='steps',
secondary_y=['committed'])
ax.right_ax.set_ylabel('Units committed')
ax.set_xlabel('System Load (MW)')
ax.set_ylabel('Estimated System Price ($/MWh)')
plt.savefig(joindir(user_config.directory, 'ed_sweep.png'))
def main(args):
generators, loads, _, times, _, data = parsedir()
generators = filter(lambda gen: gen.is_controllable, generators)
gen_data = data['generators']
if args['min'] == 0:
args['min'] = 1.1 * gen_data.pmin.sum()
if args['max'] == 0:
args['max'] = 0.99 * gen_data.pmax.sum()
load_values = np.arange(args['min'], args['max'], args['interval'])
results = DataFrame(columns=['prices', 'committed', 'last_committed'], index=load_values)
committed_gen_names = Index([])
for load_val in load_values:
print load_val
loads_times = make_loads_times(Pd=load_val)
power_system, times = solve_problem(generators,
do_reset_config=False, **loads_times)
t = times[0]
results.ix[load_val, 'prices'] = power_system.buses[0].price(t)
statuses = Series(dict([(gen.name, gen.status(t).value)
for gen in power_system.generators()]))
results.ix[load_val, 'committed'] = statuses.sum()
results.ix[load_val, 'last_committed'] = \
statuses[statuses == 1].index.difference(committed_gen_names)
committed_gen_names = statuses[statuses == 1].index
if (load_values[-1] == 0.99 * gen_data.pmax.sum()) and \
(statuses.sum() != len(generators)):
print('warning: uncommitted generation:')
print(gen_data.set_index('name').ix[statuses[statuses == 0].index])
results.to_csv(joindir(user_config.directory, 'ed_sweep.csv'))
if args['hide_units_committed']:
ax = results.prices.plot(drawstyle='steps')
else:
ax = results[['prices', 'committed']].plot(drawstyle='steps', secondary_y=['committed'])
ax.right_ax.set_ylabel('Units committed')
ax.set_xlabel('System Load (MW)')
ax.set_ylabel('Estimated System Price ($/MWh)')
plt.savefig(joindir(user_config.directory, 'ed_sweep.png'))
def check_pmin():
user_config.directory = os.path.join(basedir, 'uc')
generators, loads, _, times, _, data = parsedir()
assert(data['generators'].pmin.tolist() ==
map(lambda gen: gen.pmin, generators))
def check_pmin():
user_config.directory = os.path.join(basedir, 'uc')
generators, loads, _, times, _, data = parsedir()
assert(data['generators'].pmin.tolist() == \
map(lambda gen: gen.pmin, generators))
