def grow_drop_data(self, years, frequency, load_growth):
""" Adds data by growing the given data OR drops any extra data that
might have slipped in. Update variable that hold timeseries data
after adding growth data. These method should be called after
add_growth_data and before the optimization is run.
Args:
years (List): list of years for which analysis will occur on
frequency (str): period frequency of the timeseries data
load_growth (float): percent/ decimal value of the growth rate of
loads in this simulation
"""
super().grow_drop_data(years, frequency, load_growth)
if self.u_ts_constraints:
self.regu_max = Lib.fill_extra_data(self.regu_max, years, 0,
frequency)
self.regu_max = Lib.drop_extra_data(self.regu_max, years)
self.regu_min = Lib.fill_extra_data(self.regu_min, years, 0,
frequency)
self.regu_min = Lib.drop_extra_data(self.regu_min, years)
if self.d_ts_constraints:
self.regd_max = Lib.fill_extra_data(self.regd_max, years, 0,
frequency)
self.regd_max = Lib.drop_extra_data(self.regd_max, years)
self.regd_min = Lib.fill_extra_data(self.regd_min, years, 0,
frequency)
self.regd_min = Lib.drop_extra_data(self.regd_min, years)
def grow_drop_data(self, years, frequency, load_growth):
""" Adds data by growing the given data OR drops any extra data that might have slipped in.
Update variable that hold timeseries data after adding growth data. These method should be called after
add_growth_data and before the optimization is run.
Args:
years (List): list of years for which analysis will occur on
frequency (str): period frequency of the timeseries data
load_growth (float): percent/ decimal value of the growth rate of loads in this simulation
"""
# timeseries data
self.system_load = Lib.fill_extra_data(self.system_load, years,
load_growth, frequency)
self.system_load = Lib.drop_extra_data(self.system_load, years)
if 'active hours' in self.idmode:
self.active = Lib.fill_extra_data(self.active, years, 0, frequency)
self.active = Lib.drop_extra_data(self.active, years)
self.active = self.active == 1
# monthly data
self.capacity_rate = Lib.fill_extra_data(self.capacity_rate, years, 0,
'M')
self.capacity_rate = Lib.drop_extra_data(self.capacity_rate, years)
def grow_drop_data(self, years, frequency, load_growth):
if self.site_thermal_load_exists:
self.site_steam_load = Lib.fill_extra_data(self.site_steam_load,
years, load_growth,
frequency)
self.site_steam_load = Lib.drop_extra_data(self.site_steam_load,
years)
self.site_hotwater_load = Lib.fill_extra_data(
self.site_hotwater_load, years, load_growth, frequency)
self.site_hotwater_load = Lib.drop_extra_data(
self.site_hotwater_load, years)
def grow_drop_data(self, years, frequency, load_growth):
if self.site_hotwater_load is not None:
self.site_hotwater_load = Lib.fill_extra_data(
self.site_hotwater_load, years, load_growth, frequency)
self.site_hotwater_load = Lib.drop_extra_data(
self.site_hotwater_load, years)
if self.site_steam_load is not None:
self.site_steam_load = Lib.fill_extra_data(self.site_steam_load,
years, load_growth,
frequency)
self.site_steam_load = Lib.drop_extra_data(self.site_steam_load,
years)
def grow_drop_data(self, years, frequency, load_growth):
""" Adds data by growing the given data OR drops any extra data that might have slipped in.
Update variable that hold timeseries data after adding growth data. These method should be called after
add_growth_data and before the optimization is run.
Args:
years (List): list of years for which analysis will occur on
frequency (str): period frequency of the timeseries data
load_growth (float): percent/ decimal value of the growth rate of loads in this simulation
"""
self.energy_req = Lib.fill_extra_data(self.energy_req, years, 0,
frequency)
self.energy_req = Lib.drop_extra_data(self.energy_req, years)
self.monthly_energy = Lib.fill_extra_data(self.monthly_energy, years,
0, 'M')
self.monthly_energy = Lib.drop_extra_data(self.monthly_energy, years)
self.price = Lib.fill_extra_data(self.price, years, 0, 'M')
self.price = Lib.drop_extra_data(self.price, years)
def grow_drop_data(self, years, frequency, load_growth):
""" Update variable that hold timeseries data after adding growth data. These method should be called after
add_growth_data and before the optimization is run.
Args:
years (List): list of years for which analysis will occur on
frequency (str): period frequency of the timeseries data
load_growth (float): percent/ decimal value of the growth rate of loads in this simulation
"""
# timeseries data
self.system_load = Lib.fill_extra_data(self.system_load, years,
load_growth, frequency)
self.system_load = Lib.drop_extra_data(self.system_load, years)
self.months = Lib.fill_extra_data(self.months, years, 0, frequency)
self.months = Lib.drop_extra_data(self.months, years)
self.cap_commitment = Lib.fill_extra_data(self.cap_commitment, years,
0, frequency)
self.cap_commitment = Lib.drop_extra_data(self.cap_commitment, years)
# monthly data
self.cap_monthly = Lib.fill_extra_data(self.cap_monthly, years, 0, 'M')
self.cap_monthly = Lib.drop_extra_data(self.cap_monthly, years)
self.cap_price = Lib.fill_extra_data(self.cap_price, years, 0, 'M')
self.cap_price = Lib.drop_extra_data(self.cap_price, years)
self.ene_price = Lib.fill_extra_data(self.ene_price, years, 0, 'M')
self.ene_price = Lib.drop_extra_data(self.ene_price, years)
def grow_drop_data(self, years, frequency, load_growth):
if self.site_cooling_load is not None:
self.site_cooling_load = Lib.fill_extra_data(
self.site_cooling_load, years, load_growth, frequency)
self.site_cooling_load = Lib.drop_extra_data(
self.site_cooling_load, years)