def setup_runtimes(self, options, stats_manager: StatsManager):
_round = self._round
runtime_path = os.path.join(options.output_directory, 'runtimes.csv')
runtime_file = open(runtime_path, 'w', newline='')
ops_runtime_columns = {
"Date": lambda ops: str(ops.timestamp.date()),
"Hour": lambda ops: ops.timestamp.hour,
"Minute": lambda ops: ops.timestamp.minute,
"Type": lambda ops: "SCED",
"Solve Time": lambda ops: _round(ops.sced_runtime)
}
ops_runtime_writer = CsvReporter.from_dict(runtime_file,
ops_runtime_columns)
stats_manager.register_for_sced_stats(ops_runtime_writer.write_record)
if options.sced_frequency_minutes != 60:
hr_runtime_columns = {
"Date": lambda hourly: str(hourly.date),
"Hour": lambda hourly: hourly.hour,
"Minute": lambda hourly: 0,
"Type": lambda hourly: "Hourly Average",
"Solve Time":
lambda hourly: _round(hourly.average_sced_runtime)
}
hr_runtime_writer = CsvReporter.from_dict(runtime_file,
hr_runtime_columns,
write_headers=False)
stats_manager.register_for_hourly_stats(
hr_runtime_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: runtime_file.close())
def setup_hourly_summary(self, options, stats_manager: StatsManager):
_round = self._round
hourly_path = os.path.join(options.output_directory,
'hourly_summary.csv')
hourly_file = open(hourly_path, 'w', newline='')
hourly_columns = {
'Date':
lambda hourly: str(hourly.date),
'Hour':
lambda hourly: hourly.hour,
'TotalCosts':
lambda hourly: _round(hourly.total_costs),
'FixedCosts':
lambda hourly: _round(hourly.fixed_costs),
'VariableCosts':
lambda hourly: _round(hourly.variable_costs),
'LoadShedding':
lambda hourly: _round(hourly.load_shedding),
'OverGeneration':
lambda hourly: _round(hourly.over_generation),
'ReserveShortfall':
lambda hourly: _round(hourly.reserve_shortfall),
'RenewablesUsed':
lambda hourly: _round(hourly.renewables_used),
'RenewablesCurtailment':
lambda hourly: _round(hourly.renewables_curtailment),
'Demand':
lambda hourly: _round(hourly.total_demand),
'Price':
lambda hourly: _round(hourly.price)
}
hourly_writer = CsvReporter.from_dict(hourly_file, hourly_columns)
stats_manager.register_for_hourly_stats(hourly_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: hourly_file.close())
def setup_hourly_gen_summary(self, options, stats_manager: StatsManager):
hourly_gen_path = os.path.join(options.output_directory,
'hourly_gen_summary.csv')
hourly_gen_file = open(hourly_gen_path, 'w', newline='')
hourly_gen_columns = {
'Date':
lambda hourly: str(hourly.date),
'Hour':
lambda hourly: hourly.hour,
'Load shedding':
lambda hourly: hourly.load_shedding,
'Reserve shortfall':
lambda hourly: hourly.reserve_shortfall,
'Available reserves':
lambda hourly: hourly.available_reserve,
'Over generation':
lambda hourly: hourly.over_generation,
'Reserve Price DA':
lambda hourly: hourly.planning_reserve_price
if options.compute_market_settlements else None,
'Reserve Price RT':
lambda hourly: hourly.reserve_RT_price
}
hourly_gen_writer = CsvReporter.from_dict(hourly_gen_file,
hourly_gen_columns)
stats_manager.register_for_hourly_stats(hourly_gen_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: hourly_gen_file.close())
def write_overall_stats(overall: OverallStats):
overall_path = os.path.join(options.output_directory,
'overall_simulation_output.csv')
overall_file = open(overall_path, 'w', newline='')
overall_cols = {
'Total demand':
lambda overall: _round(overall.cumulative_demand),
'Total fixed costs':
lambda overall: _round(overall.total_overall_fixed_costs),
'Total generation costs':
lambda overall: _round(overall.total_overall_generation_costs),
'Total costs':
lambda overall: _round(overall.total_overall_costs),
'Total load shedding':
lambda overall: _round(overall.total_overall_load_shedding),
'Total over generation':
lambda overall: _round(overall.total_overall_over_generation),
'Total reserve shortfall':
lambda overall: _round(overall.total_overall_reserve_shortfall
),
'Total renewables curtailment':
lambda overall: _round(overall.
total_overall_renewables_curtailment),
'Total on/offs':
lambda overall: overall.total_on_offs,
'Total sum on/off ramps':
lambda overall: _round(overall.total_sum_on_off_ramps),
'Total sum nominal ramps':
lambda overall: _round(overall.total_sum_nominal_ramps),
'Maximum observed demand':
lambda overall: _round(overall.max_hourly_demand),
'Overall renewables penetration rate':
lambda overall: _round(overall.
overall_renewables_penetration_rate),
'Cumulative average price':
lambda overall: _round(overall.cumulative_average_price)
}
if options.compute_market_settlements:
overall_cols.update({
'Total energy payments':
lambda overall: _round(overall.total_energy_payments),
'Total reserve payments':
lambda overall: _round(overall.total_reserve_payments),
'Total uplift payments':
lambda overall: _round(overall.total_uplift_payments),
'Total payments':
lambda overall: _round(overall.total_payments),
'Cumulative average payments':
lambda overall: _round(overall.cumulative_average_payments)
})
overall_reporter = CsvReporter.from_dict(overall_file,
overall_cols)
overall_reporter.write_record(overall)
overall_file.close()
def setup_runtimes(self, options, stats_manager: StatsManager):
runtime_path = os.path.join(options.output_directory, 'runtimes.csv')
runtime_file = open(runtime_path, 'w', newline='')
runtime_columns = {
"Date": lambda hourly: str(hourly.date),
"Hour": lambda hourly: hourly.hour + 1,
"Type": lambda hourly: "SCED",
"Solve Time": lambda hourly: hourly.sced_runtime
}
runtime_writer = CsvReporter.from_dict(runtime_file, runtime_columns)
stats_manager.register_for_hourly_stats(runtime_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: runtime_file.close())
def setup_daily_summary(self, options, stats_manager: StatsManager):
daily_path = os.path.join(options.output_directory,
'daily_summary.csv')
daily_file = open(daily_path, 'w', newline='')
daily_columns = {
'Date': lambda daily: str(daily.date),
'Demand': lambda daily: daily.this_date_demand,
'Renewables available':
lambda daily: daily.this_date_renewables_available,
'Renewables used': lambda daily: daily.this_date_renewables_used,
'Renewables penetration rate': lambda daily: daily.
this_date_renewables_penetration_rate, ############ TODO: Implement ##############
'Average price': lambda daily: daily.this_date_average_price,
'Fixed costs': lambda daily: daily.this_date_fixed_costs,
'Generation costs': lambda daily: daily.this_date_variable_costs,
'Load shedding': lambda daily: daily.this_date_load_shedding,
'Over generation': lambda daily: daily.this_date_over_generation,
'Reserve shortfall':
lambda daily: daily.this_date_reserve_shortfall,
'Renewables curtailment':
lambda daily: daily.this_date_renewables_curtailment,
'Number on/offs': lambda daily: daily.this_date_on_offs,
'Sum on/off ramps': lambda daily: daily.this_date_sum_on_off_ramps,
'Sum nominal ramps':
lambda daily: daily.this_date_sum_nominal_ramps
}
if options.compute_market_settlements:
daily_columns.update({
'Renewables energy payments':
lambda daily: daily.this_date_renewable_energy_payments,
'Renewables uplift payments':
lambda daily: daily.this_date_renewable_uplift,
'Thermal energy payments':
lambda daily: daily.this_date_thermal_energy_payments,
'Thermal uplift payments':
lambda daily: daily.this_date_thermal_uplift,
'Total energy payments':
lambda daily: daily.this_date_energy_payments,
'Total uplift payments':
lambda daily: daily.this_date_uplift_payments,
'Total reserve payments':
lambda daily: daily.this_date_reserve_payments,
'Total payments':
lambda daily: daily.this_date_total_payments,
'Average payments':
lambda daily: daily.this_date_average_payments,
})
daily_writer = CsvReporter.from_dict(daily_file, daily_columns)
stats_manager.register_for_daily_stats(daily_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: daily_file.close())
def setup_hourly_gen_summary(self, options, stats_manager: StatsManager):
_round = self._round
hourly_gen_path = os.path.join(options.output_directory,
'hourly_gen_summary.csv')
hourly_gen_file = open(hourly_gen_path, 'w', newline='')
hourly_gen_columns = {
'Date':
lambda hourly: str(hourly.date),
'Hour':
lambda hourly: hourly.hour,
'Load shedding':
lambda hourly: _round(hourly.load_shedding),
'Reserve shortfall':
lambda hourly: _round(hourly.total_reserve_shortfall),
'Available headroom':
lambda hourly: _round(hourly.total_thermal_headroom),
'Over generation':
lambda hourly: _round(hourly.over_generation)
}
hourly_gen_writer = CsvReporter.from_dict(hourly_gen_file,
hourly_gen_columns)
stats_manager.register_for_hourly_stats(hourly_gen_writer.write_record)
stats_manager.register_for_overall_stats(
lambda overall: hourly_gen_file.close())
