def _area_reconfigure_prices(self, validate=True, **kwargs):
if validate:
validate_pv_device_price(**kwargs)
if key_in_dict_and_not_none(kwargs, 'initial_selling_rate'):
self.offer_update.initial_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['initial_selling_rate'])
if key_in_dict_and_not_none(kwargs, 'final_selling_rate'):
self.offer_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['final_selling_rate'])
if key_in_dict_and_not_none(kwargs, 'energy_rate_decrease_per_update'):
self.offer_update.energy_rate_change_per_update = \
read_arbitrary_profile(InputProfileTypes.IDENTITY,
kwargs['energy_rate_decrease_per_update'])
if key_in_dict_and_not_none(kwargs, 'fit_to_limit'):
self.offer_update.fit_to_limit = kwargs['fit_to_limit']
if key_in_dict_and_not_none(kwargs, 'update_interval'):
if isinstance(kwargs['update_interval'], int):
update_interval = duration(minutes=kwargs['update_interval'])
else:
update_interval = kwargs['update_interval']
self.offer_update.update_interval = update_interval
if key_in_dict_and_not_none(kwargs, 'use_market_maker_rate'):
self.use_market_maker_rate = kwargs['use_market_maker_rate']
self._validate_rates()
self.offer_update.update_offer(self)
def __init__(
self,
initial_rate,
final_rate,
fit_to_limit=True,
energy_rate_change_per_update=None,
update_interval=duration(
minutes=ConstSettings.GeneralSettings.DEFAULT_UPDATE_INTERVAL),
rate_limit_object=max):
self.fit_to_limit = fit_to_limit
self.initial_rate = read_arbitrary_profile(InputProfileTypes.IDENTITY,
initial_rate)
self.final_rate = read_arbitrary_profile(InputProfileTypes.IDENTITY,
final_rate)
if fit_to_limit is False:
self.energy_rate_change_per_update = \
read_arbitrary_profile(InputProfileTypes.IDENTITY,
energy_rate_change_per_update)
else:
self.energy_rate_change_per_update = None
self.update_interval = update_interval
self.update_counter = read_arbitrary_profile(
InputProfileTypes.IDENTITY, 0)
self.number_of_available_updates = 0
self.rate_limit_object = rate_limit_object
def test_if_storage_doesnt_buy_too_expensive(storage_strategy_test3, area_test3):
from d3a.models.read_user_profile import read_arbitrary_profile, InputProfileTypes
storage_strategy_test3.bid_update.initial_rate = \
read_arbitrary_profile(InputProfileTypes.IDENTITY, 0)
storage_strategy_test3.bid_update.final_rate = \
read_arbitrary_profile(InputProfileTypes.IDENTITY, 1)
storage_strategy_test3.event_activate()
storage_strategy_test3.event_tick()
assert len(storage_strategy_test3.accept_offer.calls) == 0
def __init__(
self,
risk: int = GeneralSettings.DEFAULT_RISK,
initial_capacity_kWh: float = StorageSettings.MIN_ALLOWED_SOC *
StorageSettings.CAPACITY,
initial_soc: float = None,
initial_rate_option: int = StorageSettings.INITIAL_RATE_OPTION,
energy_rate_decrease_option: int = StorageSettings.
RATE_DECREASE_OPTION,
energy_rate_decrease_per_update: float = GeneralSettings.
ENERGY_RATE_DECREASE_PER_UPDATE, # NOQA
battery_capacity_kWh: float = StorageSettings.CAPACITY,
max_abs_battery_power_kW: float = StorageSettings.MAX_ABS_POWER,
break_even: Union[tuple, dict] = (StorageSettings.BREAK_EVEN_BUY,
StorageSettings.BREAK_EVEN_SELL),
balancing_energy_ratio: tuple = (
BalancingSettings.OFFER_DEMAND_RATIO,
BalancingSettings.OFFER_SUPPLY_RATIO),
cap_price_strategy: bool = False,
min_allowed_soc=None):
if min_allowed_soc is None:
min_allowed_soc = StorageSettings.MIN_ALLOWED_SOC
break_even = read_arbitrary_profile(InputProfileTypes.IDENTITY,
break_even)
self._validate_constructor_arguments(risk, initial_capacity_kWh,
initial_soc, battery_capacity_kWh,
break_even, min_allowed_soc)
self.break_even = break_even
self.min_selling_rate = list(break_even.values())[0][1]
BaseStrategy.__init__(self)
OfferUpdateFrequencyMixin.__init__(self, initial_rate_option,
energy_rate_decrease_option,
energy_rate_decrease_per_update)
# Normalize min/max buying rate profiles before passing to the bid mixin
self.min_buying_rate_profile = read_arbitrary_profile(
InputProfileTypes.IDENTITY, StorageSettings.MIN_BUYING_RATE)
self.max_buying_rate_profile = {k: v[1] for k, v in break_even.items()}
BidUpdateFrequencyMixin.__init__(
self,
initial_rate_profile=self.min_buying_rate_profile,
final_rate_profile=self.max_buying_rate_profile)
self.risk = risk
self.state = StorageState(
initial_capacity_kWh=initial_capacity_kWh,
initial_soc=initial_soc,
capacity=battery_capacity_kWh,
max_abs_battery_power_kW=max_abs_battery_power_kW,
loss_per_hour=0.0,
strategy=self,
min_allowed_soc=min_allowed_soc)
self.cap_price_strategy = cap_price_strategy
self.balancing_energy_ratio = BalancingRatio(*balancing_energy_ratio)
def _area_reconfigure_prices(self, validate=True, **kwargs):
if validate:
validate_pv_device_price(**kwargs)
if 'initial_selling_rate' in kwargs and kwargs[
'initial_selling_rate'] is not None:
self.offer_update.initial_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['initial_selling_rate'])
if 'final_selling_rate' in kwargs and kwargs[
'final_selling_rate'] is not None:
self.offer_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['final_selling_rate'])
self._validate_rates()
self.offer_update.update_offer(self)
def _read_predefined_profile_for_pv(self) -> Dict[DateTime, float]:
"""
Reads profile data from the predefined power profiles. Reads config and constructor
parameters and selects the appropriate predefined profile.
:return: key value pairs of time to energy in kWh
"""
if self._power_profile_index is None or self._power_profile_index == 4:
if self.owner.config.pv_user_profile is not None:
return self.owner.config.pv_user_profile
else:
self._power_profile_index = self.owner.config.cloud_coverage
if self._power_profile_index == 0: # 0:sunny
profile_path = pathlib.Path(d3a_path +
'/resources/Solar_Curve_W_sunny.csv')
elif self._power_profile_index == 1: # 1:partial
profile_path = pathlib.Path(d3a_path +
'/resources/Solar_Curve_W_partial.csv')
elif self._power_profile_index == 2: # 2:cloudy
profile_path = pathlib.Path(d3a_path +
'/resources/Solar_Curve_W_cloudy.csv')
else:
raise ValueError("Energy_profile has to be in [0,1,2]")
# Populate energy production forecast data
return read_arbitrary_profile(InputProfileTypes.POWER,
str(profile_path))
def _read_predefined_profile_for_pv(self) -> Dict[DateTime, float]:
"""
Reads profile data from the power profile. Handles csv files and dicts.
:return: key value pairs of time to energy in kWh
"""
return read_arbitrary_profile(InputProfileTypes.POWER,
self._power_profile_W)
def test_correct_time_expansion_read_arbitrary_profile():
market_maker_rate = 30
GlobalConfig.sim_duration = duration(hours=3)
mmr = read_arbitrary_profile(InputProfileTypes.IDENTITY, market_maker_rate)
assert (list(mmr.keys())[-1] - today(tz=TIME_ZONE)).days == 0
GlobalConfig.sim_duration = duration(hours=36)
mmr = read_arbitrary_profile(InputProfileTypes.IDENTITY, market_maker_rate)
assert (list(mmr.keys())[-1] - today(tz=TIME_ZONE)).days == 1
GlobalConfig.sim_duration = duration(hours=48)
mmr = read_arbitrary_profile(InputProfileTypes.IDENTITY, market_maker_rate)
assert (list(mmr.keys())[-1] - today(tz=TIME_ZONE)).days == 2
GlobalConfig.sim_duration = duration(hours=49)
mmr = read_arbitrary_profile(InputProfileTypes.IDENTITY, market_maker_rate)
# read_arbitrary_profile expands until 01:00 after the last day in sim_duration
# because of the future markets
assert (sorted(list(mmr.keys()))[-1] == today(tz=TIME_ZONE).add(hours=49))
def __init__(self, avg_power_W, hrs_per_day=None, hrs_of_day=None, daily_budget=None,
min_energy_rate: Union[float, dict, str] =
ConstSettings.LoadSettings.MIN_ENERGY_RATE,
max_energy_rate: Union[float, dict, str] =
ConstSettings.LoadSettings.MAX_ENERGY_RATE,
balancing_energy_ratio: tuple =
(ConstSettings.BalancingSettings.OFFER_DEMAND_RATIO,
ConstSettings.BalancingSettings.OFFER_SUPPLY_RATIO)):
BaseStrategy.__init__(self)
self.min_energy_rate = read_arbitrary_profile(InputProfileTypes.IDENTITY,
min_energy_rate)
self.max_energy_rate = read_arbitrary_profile(InputProfileTypes.IDENTITY,
max_energy_rate)
BidUpdateFrequencyMixin.__init__(self,
initial_rate_profile=self.min_energy_rate,
final_rate_profile=self.max_energy_rate)
self.state = LoadState()
self.avg_power_W = avg_power_W
# consolidated_cycle is KWh energy consumed for the entire year
self.daily_energy_required = None
# Budget for a single day in eur
self.daily_budget = daily_budget * 100 if daily_budget is not None else None
# Energy consumed during the day ideally should not exceed daily_energy_required
self.energy_per_slot_Wh = None
self.energy_requirement_Wh = {} # type: Dict[Time, float]
self.hrs_per_day = {} # type: Dict[int, int]
if hrs_of_day is None:
hrs_of_day = list(range(24))
# be a parameter on the constructor or if we want to deal in percentages
if hrs_per_day is None:
hrs_per_day = len(hrs_of_day)
if hrs_of_day is None:
hrs_of_day = list(range(24))
self.hrs_of_day = hrs_of_day
self._initial_hrs_per_day = hrs_per_day
self.balancing_energy_ratio = BalancingRatio(*balancing_energy_ratio)
if not all([0 <= h <= 23 for h in hrs_of_day]):
raise ValueError("Hrs_of_day list should contain integers between 0 and 23.")
if len(hrs_of_day) < hrs_per_day:
raise ValueError("Length of list 'hrs_of_day' must be greater equal 'hrs_per_day'")
def event_activate(self):
super().event_activate()
load_profile_raw_kg = read_arbitrary_profile(
InputProfileTypes.IDENTITY, self.discharge_profile)
for key, value in load_profile_raw_kg.items():
self.load_profile_kWh[key] = value * self.conversion_factor_kWh_kg
def _event_activate_energy(self, daily_load_profile):
"""
Reads the power profile data and calculates the required energy
for each slot.
"""
load_profile = read_arbitrary_profile(InputProfileTypes.POWER,
daily_load_profile)
self._update_energy_requirement(load_profile)
def test_correct_interpolation_power_profile():
slot_length = 20
GlobalConfig.slot_length = duration(minutes=slot_length)
profile_path = pathlib.Path(d3a_path + '/resources/Solar_Curve_W_sunny.csv')
profile = read_arbitrary_profile(InputProfileTypes.POWER, str(profile_path))
times = list(profile)
for ii in range(len(times)-1):
assert abs((times[ii]-times[ii+1]).in_seconds()) == slot_length * 60
def hour_profile_of_market_maker_rate(context, scenario):
import importlib
from d3a.models.read_user_profile import InputProfileTypes
setup_file_module = importlib.import_module(
"d3a.setup.{}".format(scenario))
context._market_maker_rate = \
read_arbitrary_profile(InputProfileTypes.IDENTITY, setup_file_module.market_maker_rate)
assert context._market_maker_rate is not None
def event_activate(self):
"""
Runs on activate event. Reads the power profile data and calculates the required energy
for each slot.
:return: None
"""
self.bid_update.update_on_activate()
self.load_profile = read_arbitrary_profile(InputProfileTypes.POWER,
self.daily_load_profile)
self._update_energy_requirement()
def area_reconfigure_event(self, validate=True, **kwargs):
assert all(k in self.parameters for k in kwargs.keys())
if validate:
validate_pv_device(**kwargs)
for name, value in kwargs.items():
setattr(self, name, value)
if 'initial_selling_rate' in kwargs and kwargs[
'initial_selling_rate'] is not None:
self.offer_update.initial_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['initial_selling_rate'])
if 'final_selling_rate' in kwargs and kwargs[
'final_selling_rate'] is not None:
self.offer_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, kwargs['final_selling_rate'])
self._validate_rates()
self.produced_energy_forecast_kWh()
self.offer_update.update_offer(self)
def read_market_maker_rate(self, market_maker_rate):
"""
Reads market_maker_rate from arbitrary input types
"""
market_maker_rate_parsed = ast.literal_eval(str(market_maker_rate))
self.market_maker_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, market_maker_rate_parsed)
self.market_maker_rate = {
k: float(v)
for k, v in self.market_maker_rate.items()
}
def check_pv_csv_profile(context):
house1 = list(
filter(lambda x: x.name == "House 1",
context.simulation.area.children))[0]
pv = list(filter(lambda x: x.name == "H1 PV", house1.children))[0]
from d3a.setup.strategy_tests.user_profile_pv_csv import user_profile_path
profile_data = read_arbitrary_profile(InputProfileTypes.POWER,
user_profile_path)
for timepoint, energy in pv.strategy.energy_production_forecast_kWh.items(
):
if timepoint in profile_data.keys():
assert energy == profile_data[timepoint]
else:
assert energy == 0
def event_activate(self):
"""
Runs on activate event. Reads the power profile data and calculates the required energy
for each slot.
:return: None
"""
# If use_market_maker_rate is true, overwrite final_buying_rate to market maker rate
if self.use_market_maker_rate:
self.area_reconfigure_event(final_buying_rate=GlobalConfig.market_maker_rate)
self._validate_rates()
self.bid_update.update_on_activate()
self.load_profile = read_arbitrary_profile(
InputProfileTypes.POWER,
self.daily_load_profile)
self._update_energy_requirement()
def check_pv_profile_csv(context):
house1 = list(
filter(lambda x: x.name == "House 1",
context.simulation.area.children))[0]
pv = list(filter(lambda x: x.name == "H1 PV", house1.children))[0]
input_profile = read_arbitrary_profile(InputProfileTypes.POWER,
context._device_profile)
produced_energy = {
from_format(f'{TODAY_STR}T{k.hour:02}:{k.minute:02}',
DATE_TIME_FORMAT): v
for k, v in pv.strategy.energy_production_forecast_kWh.items()
}
for timepoint, energy in produced_energy.items():
if timepoint in input_profile:
assert energy == input_profile[timepoint]
else:
assert False
def check_pv_profile(context):
house1 = list(
filter(lambda x: x.name == "House 1",
context.simulation.area.children))[0]
pv = list(filter(lambda x: x.name == "H1 PV", house1.children))[0]
if pv.strategy._power_profile_index == 0:
path = os.path.join(d3a_path, "resources/Solar_Curve_W_sunny.csv")
if pv.strategy._power_profile_index == 1:
path = os.path.join(d3a_path, "resources/Solar_Curve_W_partial.csv")
if pv.strategy._power_profile_index == 2:
path = os.path.join(d3a_path, "resources/Solar_Curve_W_cloudy.csv")
profile_data = read_arbitrary_profile(InputProfileTypes.POWER, str(path))
for timepoint, energy in pv.strategy.energy_production_forecast_kWh.items(
):
if timepoint in profile_data.keys():
assert energy == profile_data[timepoint]
else:
assert energy == 0
def area_reconfigure_event(self,
avg_power_W=None,
hrs_per_day=None,
hrs_of_day=None,
final_buying_rate=None):
if hrs_per_day is not None or hrs_of_day is not None:
self.assign_hours_of_per_day(hrs_of_day, hrs_per_day)
self.hrs_per_day = {
day: self._initial_hrs_per_day
for day in range(self.area.config.sim_duration.days + 1)
}
if avg_power_W is not None:
self.avg_power_W = avg_power_W
self.assign_energy_requirement(avg_power_W)
if final_buying_rate is not None:
self.bid_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
def __init__(self,
duration: duration,
slot_length: duration,
tick_length: duration,
market_count: int,
cloud_coverage: int,
market_maker_rate,
iaa_fee: int,
pv_user_profile=None):
self.duration = duration
self.slot_length = slot_length
self.tick_length = tick_length
self.market_count = market_count
self.ticks_per_slot = self.slot_length / self.tick_length
if self.ticks_per_slot != int(self.ticks_per_slot):
raise D3AException(
"Non integer ticks per slot ({}) are not supported. "
"Adjust simulation parameters.".format(self.ticks_per_slot))
self.ticks_per_slot = int(self.ticks_per_slot)
if self.ticks_per_slot < 10:
raise D3AException(
"Too few ticks per slot ({}). Adjust simulation parameters".
format(self.ticks_per_slot))
self.total_ticks = self.duration // self.slot_length * self.ticks_per_slot
# TODO: Once the d3a uses a common API to the d3a-web, this should be removed
# since this limitation already exists on d3a-web
if 0 <= cloud_coverage <= 2:
self.cloud_coverage = cloud_coverage
else:
raise D3AException(
"Invalid cloud coverage value ({}).".format(cloud_coverage))
self.pv_user_profile = None \
if pv_user_profile is None \
else read_arbitrary_profile(InputProfileTypes.POWER,
ast.literal_eval(pv_user_profile),
self.slot_length)
self.read_market_maker_rate(market_maker_rate)
if iaa_fee is None:
self.iaa_fee = ConstSettings.IAASettings.FEE_PERCENTAGE
else:
self.iaa_fee = iaa_fee
def _update_rate_parameters(self, initial_selling_rate, final_selling_rate,
initial_buying_rate, final_buying_rate,
energy_rate_change_per_update):
if initial_selling_rate is not None:
self.offer_update.initial_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, initial_selling_rate)
if final_selling_rate is not None:
self.offer_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_selling_rate)
if initial_buying_rate is not None:
self.bid_update.initial_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, initial_buying_rate)
if final_buying_rate is not None:
self.bid_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
if energy_rate_change_per_update is not None:
self.offer_update.energy_rate_change_per_update = \
read_arbitrary_profile(InputProfileTypes.IDENTITY,
energy_rate_change_per_update)
self.bid_update.energy_rate_change_per_update = \
read_arbitrary_profile(InputProfileTypes.IDENTITY,
energy_rate_change_per_update)
def _read_solar_profile(profile_path):
return read_arbitrary_profile(InputProfileTypes.POWER, str(profile_path))
def _validate_constructor_arguments(initial_soc=None,
min_allowed_soc=None,
battery_capacity_kWh=None,
max_abs_battery_power_kW=None,
initial_selling_rate=None,
final_selling_rate=None,
initial_buying_rate=None,
final_buying_rate=None,
energy_rate_change_per_update=None):
if battery_capacity_kWh is not None and battery_capacity_kWh < 0:
raise ValueError("Battery capacity should be a positive integer")
if max_abs_battery_power_kW is not None and max_abs_battery_power_kW < 0:
raise ValueError(
"Battery Power rating must be a positive integer.")
if initial_soc is not None and 0 < initial_soc > 100:
raise ValueError("initial SOC must be in between 0-100 %")
if min_allowed_soc is not None and 0 < min_allowed_soc > 100:
raise ValueError("initial SOC must be in between 0-100 %")
if initial_soc is not None and min_allowed_soc is not None and \
initial_soc < min_allowed_soc:
raise ValueError(
"Initial charge must be more than the minimum allowed soc.")
if initial_selling_rate is not None and initial_selling_rate < 0:
raise ValueError("Initial selling rate must be greater equal 0.")
if final_selling_rate is not None:
if type(final_selling_rate) is float and final_selling_rate < 0:
raise ValueError("Final selling rate must be greater equal 0.")
elif type(final_selling_rate) is dict and \
any(rate < 0 for _, rate in final_selling_rate.items()):
raise ValueError("Final selling rate must be greater equal 0.")
if initial_selling_rate is not None and final_selling_rate is not None:
initial_selling_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, initial_selling_rate)
final_selling_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_selling_rate)
if any(initial_selling_rate[hour] < final_selling_rate[hour]
for hour, _ in initial_selling_rate.items()):
raise ValueError(
"Initial selling rate must be greater than final selling rate."
)
if initial_buying_rate is not None and initial_buying_rate < 0:
raise ValueError("Initial buying rate must be greater equal 0.")
if final_buying_rate is not None:
final_buying_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
if any(rate < 0 for _, rate in final_buying_rate.items()):
raise ValueError("Final buying rate must be greater equal 0.")
if initial_buying_rate is not None and final_buying_rate is not None:
initial_buying_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, initial_buying_rate)
final_buying_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
if any(initial_buying_rate[hour] > final_buying_rate[hour]
for hour, _ in initial_buying_rate.items()):
raise ValueError(
"Initial buying rate must be less than final buying rate.")
if final_selling_rate is not None and final_buying_rate is not None:
final_selling_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_selling_rate)
final_buying_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
if any(final_buying_rate[hour] >= final_selling_rate[hour]
for hour, _ in final_selling_rate.items()):
raise ValueError(
"final_buying_rate should be higher than final_selling_rate."
)
if energy_rate_change_per_update is not None and energy_rate_change_per_update < 0:
raise ValueError(
"energy_rate_change_per_update should be a non-negative value."
)
def _area_reconfigure_prices(self, final_buying_rate):
if final_buying_rate is not None:
self.bid_update.final_rate = read_arbitrary_profile(
InputProfileTypes.IDENTITY, final_buying_rate)
self._validate_rates()
def event_activate(self):
super().event_activate()
self.max_available_power_kW = \
read_arbitrary_profile(InputProfileTypes.IDENTITY, self.max_available_power_kW)
def read_pv_user_profile(self, pv_user_profile=None):
self.pv_user_profile = None \
if pv_user_profile is None \
else read_arbitrary_profile(InputProfileTypes.POWER,
ast.literal_eval(pv_user_profile))
def event_activate(self):
self.energy_rate = self.area.config.market_maker_rate if self.energy_rate is None \
else read_arbitrary_profile(InputProfileTypes.IDENTITY, self.energy_rate)
