def testSimpleStorage(self):
"""Free Storage should backup Solar."""
solar = GridSource(SOLAR, 2.0e6, 0)
wind = GridSource(WIND, 5.0e6, 0)
ng = GridSource(NG, 1.0e10, 0)
storage = GridStorage(STORAGE, 0)
lp = self.lp
lp.add_nondispatchable_sources(solar, wind)
lp.add_dispatchable_sources(ng)
lp.add_storage(storage)
self.assertTrue(lp.solve())
npt.assert_almost_equal(solar.get_solution_values(),
np.array([4.0, 0, 0, 2.0]))
npt.assert_almost_equal(wind.get_solution_values(),
np.zeros(4))
npt.assert_almost_equal(ng.get_solution_values(),
np.zeros(4))
npt.assert_almost_equal(storage.get_solution_values(),
np.array([0, 1, 1, 1]))
npt.assert_almost_equal(storage.source.get_solution_values(),
np.array([0, 0, 0, 1]))
npt.assert_almost_equal(storage.sink.get_solution_values(),
np.array([1, 0, 0, 0]))
def testCheaperDispatchableOnly(self):
"""Two Dispatchable Sources. Cheaper one should fill demand."""
lp = self.lp
ng1 = self.ng
ng2 = GridSource(NG2, 2e6, 2e6)
lp.add_dispatchable_sources(ng1, ng2)
self.assertTrue(lp.solve())
npt.assert_almost_equal(ng1.get_solution_values(), self.demand_profile)
npt.assert_almost_equal(ng2.get_solution_values(), np.zeros(4))
self.assertAlmostEqual(ng1.get_nameplate_solution_value(),
max(self.demand_profile))
self.assertAlmostEqual(ng2.get_nameplate_solution_value(), 0.0)
def testCircularRecStorageFirstHourSource(self):
"""Verify that storage from first hour affects last hour."""
wind = GridSource(WIND, 2.0e6, 0)
storage = GridRecStorage(STORAGE, 0)
lp = self.lp
lp.add_nondispatchable_sources(wind)
lp.add_storage(storage)
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.array([2.0, 0.0]))
npt.assert_almost_equal(storage.get_solution_values(),
np.array([0.0, 1.0]))
npt.assert_almost_equal(storage.get_source_solution_values(),
np.array([-1.0, 1.0]))
def testCostConstraintCreation(self):
"""Verify cost constraint gets created upon initialization."""
lp = self.lp
ng = GridSource(NG, 1e6, 1e6)
lp.add_dispatchable_sources(ng)
self.assertIsNone(lp.minimize_costs_objective)
lp._initialize_solver()
self.assertIsNotNone(lp.minimize_costs_objective)
def testCircularRecStorageLastHourSource(self):
"""Verify that storage from last hour affects first hour."""
solar = GridSource(SOLAR, 2.0e6, 0)
storage = GridRecStorage(STORAGE, 0)
lp = self.lp
lp.add_nondispatchable_sources(solar)
lp.add_storage(storage)
self.assertTrue(lp.solve())
npt.assert_almost_equal(solar.get_solution_values(),
np.array([0.0, 2.0]))
npt.assert_almost_equal(storage.get_solution_values(),
np.array([1.0, 0.0]))
npt.assert_almost_equal(storage.get_source_solution_values(),
np.array([1.0, -1.0]))
def testPostProcessing(self):
lp = self.lp
wind = GridSource(WIND, 2.0e6, 0, is_rps_source=True)
ng = GridSource(NG, 1.0e6, 1.0e6)
storage = GridStorage(STORAGE, 1, 1, 1)
lp.add_nondispatchable_sources(wind)
lp.add_dispatchable_sources(ng)
lp.add_storage(storage)
lp.rps_percent = 20
self.assertTrue(lp.solve())
wind_solution = MockPostProcessingGridSourceSolver(wind)
storage_sink_solution = MockPostProcessingGridSourceSolver(storage.sink)
wind_solution.solution_values -= 0.1
with self.assertRaises(DemandNotSatisfiedError):
lp._post_process()
# After reset it shouldn't error out.
wind_solution.reset()
try:
lp._post_process()
except RuntimeError:
self.fail()
storage_sink_solution.solution_values += 20
with self.assertRaises(DemandNotSatisfiedError):
lp._post_process()
# After reset it shouldn't error out.
storage_sink_solution.reset()
try:
lp._post_process()
except RuntimeError:
self.fail()
lp.rps_demand *= 100
with self.assertRaises(RpsPercentNotMetError):
lp._post_process()
def testCombinedSolarWindNgRps(self):
"""Sweep RPS."""
solar = GridSource(SOLAR, 2.0e6, 0, is_rps_source=True)
wind = GridSource(WIND, 4.0e6, 0, is_rps_source=True)
ng = GridSource(NG, 0, 1.0e6)
lp = self.lp
lp.add_dispatchable_sources(ng)
lp.add_nondispatchable_sources(solar, wind)
# As rps is swept, it will fill RPS requirement with cheaper solar
# first then wind. NG is cheapest but not in RPS so it will fill
# in the blanks.
# Wind is really expensive so check and make sure the LP doesn't
# cheat by requesting more cheaper solar than it can actually use
# in order to satisfy rps. Instead, after it's maxed out on
# solar, it has to use the expensive wind.
for rps in np.arange(0, 1.2, 0.1):
lp.rps_percent = rps * 100.0
if lp.solve():
self.assertTrue(rps <= 1.0)
solar_nameplate = rps * 2 if rps <= 0.5 else 1.0
wind_nameplate = (rps - 0.5) * 2 if rps > 0.5 else 0.0
solar_golden_profile = self.profiles[SOLAR] * solar_nameplate
wind_golden_profile = self.profiles[WIND] * wind_nameplate
ng_golden_profile = (self.profiles[DEMAND] -
solar_golden_profile -
wind_golden_profile)
npt.assert_almost_equal(solar.get_solution_values(),
solar_golden_profile)
npt.assert_almost_equal(wind.get_solution_values(),
wind_golden_profile)
npt.assert_almost_equal(ng.get_solution_values(),
ng_golden_profile)
else:
# Ensure lp doesn't solve if rps > 1.0
self.assertTrue(rps > 1.0)
def setUp(self):
self.demand_profile = np.array([3.0, 0.0, 0.0, 3.0])
rng = pd.date_range('1/1/2011', periods=len(self.demand_profile), freq='H')
df = pd.DataFrame.from_dict(
{DEMAND: self.demand_profile,
SOLAR: np.array([2.0, 0.0, 0.0, 1.0]),
WIND: np.array([1.0, 0.0, 0.0, 0.0]),
TIME: rng}
)
self.profiles = df.set_index(TIME,
verify_integrity=True)
self.lp = LinearProgramContainer(self.profiles)
self.lp.add_demands(GridDemand(DEMAND))
self.solar = GridSource(SOLAR, 1e6, 1e6)
self.ng = GridSource(NG, 1e6, 1e6)
def testVariableCreation(self):
"""Check GridSource creates nameplate / timeslice variables."""
lp = self.lp
ng = GridSource(NG, 1e6, 1e6)
self.assertIsNone(ng.timeslice_variables)
self.assertIsNone(ng.nameplate_variable)
lp.add_dispatchable_sources(ng)
lp._initialize_solver()
self.assertIsNotNone(ng.nameplate_variable)
self.assertEqual(len(ng.timeslice_variables), lp.number_of_timeslices)
def testFreeStorageMeansCheapestSource(self):
"""Verify that free storage selects the cheapest energy supply."""
solar = GridSource(SOLAR, 2.0e6, 0)
wind = GridSource(WIND, 2.2e6, 0)
storage = GridStorage(STORAGE, 0)
lp = self.lp
lp.add_nondispatchable_sources(solar, wind)
lp.add_storage(storage)
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.zeros(2))
npt.assert_almost_equal(solar.get_solution_values(),
np.array([0.0, 2.0]))
npt.assert_almost_equal(storage.get_solution_values(),
np.array([1.0, 0.0]))
npt.assert_almost_equal(storage.source.get_solution_values(),
np.array([1.0, 0.0]))
npt.assert_almost_equal(storage.sink.get_solution_values(),
np.array([0.0, 1.0]))
def testSolutionValuesCalledBeforeSolve(self):
lp = LinearProgramContainer(self.dummy_profile)
ng = GridSource(NG, 1e6, 1e6)
lp.add_dispatchable_sources(ng)
with self.assertRaises(RuntimeError):
ng.get_solution_values()
with self.assertRaises(RuntimeError):
ng.get_nameplate_solution_value()
def testRpsStorage(self):
"""Storage credits rps if timeslice exceeds demand."""
lp = self.lp
wind = GridSource(WIND, 2.0e6, 0, is_rps_source=True)
ng = GridSource(NG, 0, 1.0e6)
storage = GridRecStorage(STORAGE, 1, 1, 1)
lp.add_nondispatchable_sources(wind)
lp.add_dispatchable_sources(ng)
lp.add_storage(storage)
demand_at_0 = self.profiles[DEMAND][0]
demand_at_1 = self.profiles[DEMAND][1]
total = sum(self.profiles[DEMAND])
for rps in range(0, 120, 10):
lp.rps_percent = rps
rps_total = total * rps / 100.0
# Wind is only on for one time-slice.
wind_at_0 = rps_total
wind_nameplate = wind_at_0
golden_wind = wind_nameplate * self.profiles[WIND]
# Either we charge at 0, or ng fills remaining.
if wind_at_0 >= demand_at_0:
storage_at_0 = wind_at_0 - demand_at_0
ng_at_0 = 0
else:
storage_at_0 = 0
ng_at_0 = demand_at_0 - wind_at_0
# Discharge everything at 1.
storage_discharge_power = storage_at_0
ng_at_1 = demand_at_1 - storage_discharge_power
if lp.solve():
self.assertTrue(rps <= 100)
npt.assert_almost_equal(wind.get_solution_values(),
golden_wind)
npt.assert_almost_equal(ng.get_solution_values(),
np.array([ng_at_0, ng_at_1]))
# Storage at t=1 shows what charged at t=0.
npt.assert_almost_equal(storage.get_solution_values(),
np.array([0.0, storage_at_0]))
else:
# Verify no convergence because we asked for a ridiculous rps number.
self.assertTrue(rps > 100)
def testMaxPowerCheaperDispatchable(self):
"""Two Dispatchable Sources. Cheaper one fills up to max_power."""
lp = self.lp
max_power = 1
ng1 = GridSource(NG, 1e6, 1e6, max_power=max_power)
ng2 = GridSource(NG2, 2e6, 2e6)
lp.add_dispatchable_sources(ng1, ng2)
self.assertTrue(lp.solve())
max_power_profile = np.array([max_power, 0, 0, max_power])
remaining = self.demand_profile - max_power_profile
npt.assert_almost_equal(ng1.get_solution_values(), max_power_profile)
npt.assert_almost_equal(ng2.get_solution_values(), remaining)
self.assertAlmostEqual(ng1.get_nameplate_solution_value(),
max(max_power_profile))
self.assertAlmostEqual(ng2.get_nameplate_solution_value(),
max(remaining))
def testMaxEnergyCheaperDispatchable(self):
"""Two Dispatchable Sources. Cheaper one fills up to max_energy."""
lp = self.lp
max_energy = 1.0
ng1 = GridSource(NG, 1e6, 1e6, max_energy=max_energy)
ng2 = GridSource(NG2, 2e6, 2e6)
lp.add_dispatchable_sources(ng1, ng2)
self.assertTrue(lp.solve())
demand_profiles = self.demand_profile
demand_energy = sum(demand_profiles)
max_energy_profile = (max_energy / demand_energy) * demand_profiles
remaining = demand_profiles - max_energy_profile
npt.assert_almost_equal(ng1.get_solution_values(), max_energy_profile)
npt.assert_almost_equal(ng2.get_solution_values(), remaining)
self.assertAlmostEqual(ng1.get_nameplate_solution_value(),
max(max_energy_profile))
self.assertAlmostEqual(ng2.get_nameplate_solution_value(),
max(remaining))
def setUp(self):
self.demand_profile = np.array(
[0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0])
impulse_profile = np.zeros(len(self.demand_profile))
impulse_profile[0] = 1.0
self.impulse = impulse_profile
rng = pd.date_range('1/1/2011', periods=len(self.demand_profile), freq='H')
df = pd.DataFrame.from_dict(
{DEMAND: self.demand_profile,
SOLAR: impulse_profile,
TIME: rng}
)
self.profiles = df.set_index(TIME,
verify_integrity=True)
self.lp = LinearProgramContainer(self.profiles)
self.lp.add_demands(GridDemand(DEMAND))
self.solar = GridSource(SOLAR, 1e6, 1e6)
def testCircularRecAccounting(self):
"""Verify that RECs get stored and accounted for properly."""
lp = self.lp
solar = GridSource(SOLAR, 2e6, 2e6, is_rps_source=True)
wind = GridSource(WIND, 1e6, 1e6)
storage = GridRecStorage(STORAGE, 1, 1, 1, discharge_efficiency=0.5)
lp.add_nondispatchable_sources(solar, wind)
lp.add_storage(storage)
for rps in np.arange(0, 110, 10):
lp.rps_percent = rps
self.assertTrue(lp.solve())
npt.assert_almost_equal(solar.get_solution_values(),
self.profiles[SOLAR].values *
rps / storage.discharge_efficiency)
npt.assert_almost_equal(wind.get_solution_values(),
self.profiles[WIND] *
(100 - rps) / storage.discharge_efficiency)
rps_credit = np.array([v.solution_value()
for v in lp.rps_credit_variables[0]])
self.assertAlmostEqual(sum(rps_credit), rps)
rec_storage = storage.rec_storage
no_rec_storage = storage.no_rec_storage
npt.assert_almost_equal(rps_credit,
rec_storage.source.get_solution_values() *
storage.discharge_efficiency)
npt.assert_almost_equal(self.profiles[DEMAND] - rps_credit,
no_rec_storage.source.get_solution_values() *
storage.discharge_efficiency)
def testStorageNameplateCost(self):
"""Keep increasing storage costs until ng finally wins out."""
wind = GridSource(WIND, 1.0e6, 0)
storage = GridRecStorage(STORAGE, 0)
ng = GridSource(NG, 4.6e6, 0)
lp = self.lp
lp.add_nondispatchable_sources(wind)
lp.add_dispatchable_sources(ng)
lp.add_storage(storage)
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.array([2.0, 0.0]))
npt.assert_almost_equal(ng.get_solution_values(),
np.zeros(2))
# Change costs. Total wind + storage cost is now (2 + 1)E6.
# Still less than ng costs.
storage.charge_nameplate_cost = 1.0e6
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.array([2.0, 0.0]))
npt.assert_almost_equal(ng.get_solution_values(),
np.zeros(2))
# Change Costs. Total wind + storage cost is now (2 + 1 + 1)E6.
# Still less than ng costs.
storage.storage_nameplate_cost = 1.0e6
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.array([2.0, 0.0]))
npt.assert_almost_equal(ng.get_solution_values(),
np.zeros(2))
# Change costs. Total wind + storage cost is now
# (2 + 1 + 1 + 1)E6. Now more than ng costs.
storage.discharge_nameplate_cost = 1.0e6
self.assertTrue(lp.solve())
npt.assert_almost_equal(wind.get_solution_values(),
np.zeros(2))
npt.assert_almost_equal(ng.get_solution_values(),
np.array([1.0, 1.0]))
def testAddNonDispatchableSourceWithoutProfile(self):
"""Ensure NonDispatchable Source without profile gets error."""
with self.assertRaises(KeyError):
lp = LinearProgramContainer(self.dummy_profile)
lp.add_nondispatchable_sources(GridSource(NG, 1e6, 1e6))
def testAddDispatchableSourceWithProfile(self):
"""Ensure Dispatchable Source with profile gets error."""
with self.assertRaises(KeyError):
lp = LinearProgramContainer(pd.DataFrame({NG: np.ones(4)}))
lp.add_dispatchable_sources(GridSource(NG, 1e6, 1e6))
