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Add test for unit commitment
Signed-off-by: Davey Elder <iandavidelder@gmail.com>
1 parent e59cdf0 commit f85e940

4 files changed

Lines changed: 190 additions & 0 deletions

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‎tests/conftest.py‎

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@@ -103,6 +103,7 @@ def refresh_databases() -> None:
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('materials.sql', 'materials.sqlite'),
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('simple_linked_tech.sql', 'simple_linked_tech.sqlite'),
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('storageville.sql', 'storageville.sqlite'),
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('test_week.sql', 'test_week.sqlite'),
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(None, 'utopia_stochastic.sqlite'),
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]
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@@ -221,6 +222,11 @@ def system_test_run(
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if myopic_overrides is not None:
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config.myopic_inputs = {**(config.myopic_inputs or {}), **myopic_overrides}
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# Allow parametrized tests to override myopic settings per case.
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time_sequencing_override = request.param.get('time_sequencing')
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if time_sequencing_override is not None:
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config.time_sequencing = time_sequencing_override
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sequencer = TemoaSequencer(config=config)
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sequencer.start()

‎tests/test_full_runs.py‎

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@@ -49,6 +49,12 @@ class MyopicStressCase(TypedDict):
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myopic: MyopicSettings
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class TimeSequenceCase(TypedDict):
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name: str
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filename: str
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time_sequencing: str
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myopic_stress_tests: list[MyopicStressCase] = [
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{
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'name': (
@@ -68,6 +74,16 @@ class MyopicStressCase(TypedDict):
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]
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time_sequence_tests: list[TimeSequenceCase] = [
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{
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'name': (f'test_week | {time_sequencing}'),
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'filename': 'config_test_week.toml',
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'time_sequencing': time_sequencing,
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}
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for time_sequencing in ['consecutive_days', 'representative_periods', 'seasonal_timeslices']
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]
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@pytest.mark.parametrize(
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'system_test_run',
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argvalues=legacy_config_files,
@@ -210,6 +226,33 @@ def test_myopic_stress_tests(
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)
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@pytest.mark.parametrize(
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'system_test_run',
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argvalues=time_sequence_tests,
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indirect=True,
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ids=[d['name'] for d in time_sequence_tests],
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)
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def test_time_sequence_tests(
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system_test_run: tuple[str, SolverResults | None, TemoaModel | None, TemoaSequencer],
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) -> None:
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_, _, _, sequencer = system_test_run
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import contextlib
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objectives = {
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'consecutive_days': 1445.875735,
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'representative_periods': 1467.912766,
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'seasonal_timeslices': 1467.912766,
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}
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with contextlib.closing(sqlite3.connect(sequencer.config.output_database)) as con:
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cur = con.cursor()
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res = cur.execute('SELECT SUM(total_system_cost) FROM main.output_objective').fetchone()
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obj = res[0]
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assert obj == pytest.approx(objectives[sequencer.config.time_sequencing], abs=0.00001), (
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'objective function value did not match expected for time sequencing test'
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)
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@pytest.mark.parametrize(
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'system_test_run',
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argvalues=stochastic_files,

‎tests/testing_configs/config_test_week.toml‎

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scenario = "test_week"
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scenario_mode = "perfect_foresight"
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extensions= ["unit_commitment"]
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input_database = "tests/testing_outputs/test_week.sqlite"
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output_database = "tests/testing_outputs/test_week.sqlite"
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neos = false
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solver_name = "appsi_highs"
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save_excel = false
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save_duals = false
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save_lp_file = false
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days_per_period = 7
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reserve_margin = "static"
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[MGA]
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slack = 0.1
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iterations = 4
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weight = "integer"
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[myopic]
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view_depth = 1
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step_size = 1
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evolving = false
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evolution_script = ''

‎tests/testing_data/test_week.sql‎

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REPLACE INTO metadata VALUES('DB_MAJOR',4,'DB major version number');
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REPLACE INTO metadata VALUES('DB_MINOR',0,'DB minor version number');
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REPLACE INTO metadata_real VALUES('global_discount_rate',0.05000000000000000277,'Discount Rate for future costs');
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REPLACE INTO metadata_real VALUES('default_loan_rate',0.05000000000000000277,'Default Loan Rate if not specified in LoanRate table');
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REPLACE INTO sector_label VALUES('energy',NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d01','h01','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d02','h12','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d03','h20','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d04','h24','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d05','h01','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d06','h22','uc_cheap',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d05','h16','uc_expensive',0.0,NULL);
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REPLACE INTO capacity_factor_tech VALUES('region','d01','h16','uc_expensive',0.0,NULL);
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REPLACE INTO capacity_to_activity VALUES('region','uc_cheap',168.0,NULL,NULL);
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REPLACE INTO capacity_to_activity VALUES('region','uc_expensive',168.0,NULL,NULL);
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REPLACE INTO commodity VALUES('source','s',NULL,NULL);
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REPLACE INTO commodity VALUES('demand','d',NULL,NULL);
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REPLACE INTO commodity VALUES('co2','e',NULL,NULL);
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REPLACE INTO commodity VALUES('dummy','p',NULL,NULL);
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REPLACE INTO commodity_type VALUES('s','source commodity');
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REPLACE INTO commodity_type VALUES('a','annual commodity');
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REPLACE INTO commodity_type VALUES('p','physical commodity');
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REPLACE INTO commodity_type VALUES('d','demand commodity');
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REPLACE INTO commodity_type VALUES('e','emissions commodity');
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REPLACE INTO commodity_type VALUES('w','waste commodity');
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REPLACE INTO commodity_type VALUES('wa','waste annual commodity');
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REPLACE INTO commodity_type VALUES('wp','waste physical commodity');
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REPLACE INTO cost_emission VALUES('region',0,'co2',1.0,'$/kt',NULL);
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REPLACE INTO cost_fixed VALUES('region',0,'uc_cheap',0,8.0,'$/MWy',NULL);
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REPLACE INTO cost_fixed VALUES('region',0,'uc_expensive',0,10.0,'$/MWy',NULL);
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REPLACE INTO cost_invest VALUES('region','uc_cheap',0,8.0,'$/MW',NULL);
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REPLACE INTO cost_invest VALUES('region','uc_expensive',0,10.0,'$/MW',NULL);
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REPLACE INTO cost_invest VALUES('region','daily_storage',0,5.0,'$/MW',NULL);
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REPLACE INTO cost_invest VALUES('region','seasonal_storage',0,5.0,'$/MW',NULL);
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REPLACE INTO cost_variable VALUES('region',0,'uc_cheap',0,8.0,'$/MWh',NULL);
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REPLACE INTO cost_variable VALUES('region',0,'uc_expensive',0,10.0,'$/MWh',NULL);
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REPLACE INTO demand VALUES('region',0,'demand',168.0,'MWh',NULL);
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REPLACE INTO efficiency VALUES('region','source','uc_cheap',0,'dummy',1.0,'MW/MW',NULL);
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REPLACE INTO efficiency VALUES('region','source','uc_expensive',0,'dummy',1.0,'MW/MW',NULL);
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REPLACE INTO efficiency VALUES('region','dummy','demand_sink',0,'demand',1.0,'MW/MW',NULL);
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REPLACE INTO efficiency VALUES('region','dummy','daily_storage',0,'dummy',1.0,'MW/MW',NULL);
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REPLACE INTO efficiency VALUES('region','dummy','seasonal_storage',0,'dummy',1.0,'MW/MW',NULL);
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REPLACE INTO lifetime_tech VALUES('region','uc_cheap',1.0,NULL,NULL);
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REPLACE INTO lifetime_tech VALUES('region','uc_expensive',1.0,NULL,NULL);
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REPLACE INTO operator VALUES('e','equal to');
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REPLACE INTO operator VALUES('le','less than or equal to');
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REPLACE INTO operator VALUES('ge','greater than or equal to');
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REPLACE INTO limit_activity VALUES('region',0,'uc_expensive','ge',10.0,NULL,NULL);
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REPLACE INTO limit_activity VALUES('region',0,'uc_cheap','ge',10.0,NULL,NULL);
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REPLACE INTO limit_activity VALUES('region',0,'daily_storage','ge',10.0,NULL,NULL);
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REPLACE INTO limit_activity VALUES('region',0,'seasonal_storage','ge',10.0,NULL,NULL);
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REPLACE INTO limit_capacity VALUES('region',0,'uc_cheap','le',1.0,NULL,NULL);
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REPLACE INTO limit_capacity VALUES('region',0,'uc_expensive','le',2.0,NULL,NULL);
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REPLACE INTO ramp_down_hourly VALUES('region','uc_expensive',0.5,NULL);
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REPLACE INTO ramp_down_hourly VALUES('region','uc_cheap',0.5,NULL);
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REPLACE INTO ramp_up_hourly VALUES('region','uc_expensive',0.5,NULL);
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REPLACE INTO ramp_up_hourly VALUES('region','uc_cheap',0.5,NULL);
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REPLACE INTO ramp_up_hourly VALUES('region','seasonal_storage',0.5,NULL);
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REPLACE INTO ramp_up_hourly VALUES('region','daily_storage',0.5,NULL);
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REPLACE INTO region VALUES('region',NULL);REPLACE INTO storage_duration VALUES('region','daily_storage',1.0,NULL);
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REPLACE INTO storage_duration VALUES('region','seasonal_storage',1.0,NULL);
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REPLACE INTO technology_type VALUES('p','production technology');
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REPLACE INTO technology_type VALUES('pb','baseload production technology');
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REPLACE INTO technology_type VALUES('ps','storage production technology');
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REPLACE INTO time_of_day VALUES(1,'h01',1.0,NULL);
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REPLACE INTO time_of_day VALUES(2,'h02',1.0,NULL);
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REPLACE INTO time_of_day VALUES(3,'h03',1.0,NULL);
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REPLACE INTO time_of_day VALUES(4,'h04',1.0,NULL);
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REPLACE INTO time_of_day VALUES(5,'h05',1.0,NULL);
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REPLACE INTO time_of_day VALUES(6,'h06',1.0,NULL);
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REPLACE INTO time_of_day VALUES(7,'h07',1.0,NULL);
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REPLACE INTO time_of_day VALUES(8,'h08',1.0,NULL);
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REPLACE INTO time_of_day VALUES(9,'h09',1.0,NULL);
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REPLACE INTO time_of_day VALUES(10,'h10',1.0,NULL);
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REPLACE INTO time_of_day VALUES(11,'h11',1.0,NULL);
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REPLACE INTO time_of_day VALUES(12,'h12',1.0,NULL);
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REPLACE INTO time_of_day VALUES(13,'h13',1.0,NULL);
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REPLACE INTO time_of_day VALUES(14,'h14',1.0,NULL);
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REPLACE INTO time_of_day VALUES(15,'h15',1.0,NULL);
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REPLACE INTO time_of_day VALUES(16,'h16',1.0,NULL);
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REPLACE INTO time_of_day VALUES(17,'h17',1.0,NULL);
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REPLACE INTO time_of_day VALUES(18,'h18',1.0,NULL);
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REPLACE INTO time_of_day VALUES(19,'h19',1.0,NULL);
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REPLACE INTO time_of_day VALUES(20,'h20',1.0,NULL);
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REPLACE INTO time_of_day VALUES(21,'h21',1.0,NULL);
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REPLACE INTO time_of_day VALUES(22,'h22',1.0,NULL);
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REPLACE INTO time_of_day VALUES(23,'h23',1.0,NULL);
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REPLACE INTO time_of_day VALUES(24,'h24',1.0,NULL);
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REPLACE INTO time_period VALUES(0,0,'f');
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REPLACE INTO time_period VALUES(1,1,'f');
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REPLACE INTO time_period_type VALUES('e','existing vintages');
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REPLACE INTO time_period_type VALUES('f','future');REPLACE INTO technology VALUES('uc_cheap','p','energy',NULL,NULL,0,0,0,0,0,0,0,0,NULL);
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REPLACE INTO technology VALUES('uc_expensive','p','energy',NULL,NULL,0,0,0,0,0,0,0,0,NULL);
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REPLACE INTO technology VALUES('demand_sink','p','energy',NULL,NULL,1,0,0,0,0,0,0,0,NULL);
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REPLACE INTO technology VALUES('daily_storage','ps','energy',NULL,NULL,0,0,0,0,0,0,0,0,NULL);
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REPLACE INTO technology VALUES('seasonal_storage','ps','energy',NULL,NULL,0,0,0,0,0,0,0,1,NULL);
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REPLACE INTO time_season VALUES(1,'d01',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(2,'d02',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(3,'d03',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(4,'d04',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(5,'d05',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(6,'d06',0.1428571428571428493,'1/7');
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REPLACE INTO time_season VALUES(7,'d07',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(1,'d01','d03',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(2,'d02','d05',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(3,'d03','d01',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(4,'d04','d07',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(5,'d05','d04',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(6,'d06','d06',0.1428571428571428493,'1/7');
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REPLACE INTO time_season_sequential VALUES(7,'d07','d02',0.1428571428571428493,'1/7');
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REPLACE INTO unit_commitment VALUES('region','uc_cheap',0.2000000000000000111,0.5,1.0,3,5,0,NULL,NULL);
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REPLACE INTO unit_commitment VALUES('region','uc_expensive',0.2000000000000000111,0.5,1.0,2,1,1,NULL,NULL);
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REPLACE INTO unit_commitment_startup_cost VALUES('region','uc_expensive',5.0,NULL,NULL);
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REPLACE INTO unit_commitment_startup_cost VALUES('region','uc_cheap',4.0,NULL,NULL);
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REPLACE INTO unit_commitment_startup_emissions VALUES('region','co2','uc_expensive',5.0,NULL,NULL);
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REPLACE INTO unit_commitment_startup_emissions VALUES('region','co2','uc_cheap',4.0,NULL,NULL);
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REPLACE INTO unit_commitment_startup_input VALUES('region','source','uc_expensive',5.0,NULL,NULL);
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REPLACE INTO unit_commitment_startup_input VALUES('region','source','uc_cheap',4.0,NULL,NULL);

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