def test_slack_in_generic_constraints_with_all_features():
inputs_database = 'test_files/historical_all.db'
con = sqlite3.connect('test_files/historical_all.db')
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
print(interval)
historical_inputs.load_interval(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.add_interconnectors_to_market()
market.add_generic_constraints_fcas_requirements()
market.set_unit_fcas_constraints()
market.set_unit_limit_constraints()
market.set_ramp_rate_limits()
market.set_unit_dispatch_to_historical_values(wiggle_room=0.003)
market.set_interconnector_flow_to_historical_values()
market.dispatch(calc_prices=False)
assert market.is_generic_constraint_slack_correct()
assert market.is_fcas_constraint_slack_correct()
assert market.is_regional_demand_meet()
def test_fcas_trapezium_scaled_availability():
inputs_database = 'test_files/historical_all.db'
con = sqlite3.connect('test_files/historical_all.db')
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
print(interval)
historical_inputs.load_interval(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.set_unit_fcas_constraints()
market.set_unit_limit_constraints()
market.set_unit_dispatch_to_historical_values(wiggle_room=0.0001)
market.dispatch(calc_prices=False)
avails = market.do_fcas_availabilities_match_historical()
# I think NEMDE might be getting avail calcs wrong when units are opperating on the slopes, and the slopes
# are vertical. They should be ignore 0 slope cofficients, maybe this is not happing because of floating
# point comparison.
if interval == '2019/01/29 18:10:00':
avails = avails[~(avails['unit'] == 'PPCCGT')]
if interval == '2019/01/07 19:35:00':
avails = avails[~(avails['unit'] == 'PPCCGT')]
assert avails['error'].abs().max() < 1.1
def test_all_units_and_service_dispatch_historically_present_in_market():
inputs_database = 'test_files/historical_all.db'
con = sqlite3.connect('test_files/historical_all.db')
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
historical_inputs.load_interval(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
assert market.all_dispatch_units_and_service_have_decision_variables()
def test_capacity_constraints():
inputs_database = 'test_files/historical_all.db'
con = sqlite3.connect(inputs_database)
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
print(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.set_unit_limit_constraints()
market.set_unit_dispatch_to_historical_values()
market.dispatch()
assert market.measured_violation_equals_historical_violation(
'unit_capacity', nempy_constraints=['unit_bid_capacity'])
def test_if_ramp_rates_calculated_correctly():
inputs_database = 'test_files/historical.db'
con = sqlite3.connect(inputs_database)
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
print(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.set_ramp_rate_limits()
market.set_unit_dispatch_to_historical_values()
market.dispatch()
assert market.measured_violation_equals_historical_violation(
historical_name='ramp_rate',
nempy_constraints=['ramp_up', 'ramp_down'])
with open('interval_with_violations.pickle', 'rb') as f:
interval_with_violations = pickle.load(f)
for interval, types in interval_with_violations.items():
if 'ramp_rate' in types:
print(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.set_ramp_rate_limits()
market.set_unit_dispatch_to_historical_values()
market.dispatch()
assert market.measured_violation_equals_historical_violation(
historical_name='ramp_rate',
nempy_constraints=['ramp_up', 'ramp_down'])
def test_slack_in_generic_constraints_use_fcas_requirements_interface():
inputs_database = 'test_files/historical_all.db'
con = sqlite3.connect('test_files/historical_all.db')
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='test_files/historical_xml_files')
for interval in get_test_intervals():
print(interval)
historical_inputs.load_interval(interval)
market = historical_market_builder.SpotMarket(
inputs_database=inputs_database,
inputs=historical_inputs,
interval=interval)
market.add_unit_bids_to_market()
market.add_interconnectors_to_market()
market.add_generic_constraints_fcas_requirements()
market.set_unit_dispatch_to_historical_values(wiggle_room=0.0001)
market.set_interconnector_flow_to_historical_values(wiggle_room=0.001)
market.dispatch(calc_prices=False)
market.market.get_elastic_constraints_violation_degree('generic')
assert market.all_constraints_presenet()
assert market.is_generic_constraint_slack_correct()
assert market.is_fcas_constraint_slack_correct()
import pickle
import sqlite3
from nempy.historical_inputs import loaders
import os
cwd = os.getcwd()
print(cwd)
con = sqlite3.connect('historical.db')
historical_inputs = loaders.HistoricalInputs(
market_management_system_database_connection=con,
nemde_xml_cache_folder='historical_xml_files')
interval_with_violations = \
historical_inputs.find_intervals_with_violations(limit=1000000,
start_year=2019, start_month=2,
end_year=2019, end_month=2)
with open('interval_with_violations.pickle', 'wb') as f:
pickle.dump(interval_with_violations, f, pickle.HIGHEST_PROTOCOL)
