def __init__(self,
dfm,
run_uuid,
min_kw,
max_kw,
existing_kw,
fuel_slope_gal_per_kwh,
fuel_intercept_gal_per_hr,
fuel_avail_gal,
min_turn_down_pct,
outage_start_hour=None,
outage_end_hour=None,
time_steps_per_hour=1,
fuel_avail_before_outage_pct=1,
emissions_factor_lb_CO2_per_gal=None,
**kwargs):
super(Generator, self).__init__(min_kw=min_kw, max_kw=max_kw, **kwargs)
"""
super class init for generator is not unique anymore as we are now allowing users to define min/max sizes;
and include diesel generator's size as optimization decision variable.
Note that default burn rate, slope, and min/max sizes are handled in ValidateNestedInput.
"""
self.fuel_slope = fuel_slope_gal_per_kwh
self.fuel_intercept = fuel_intercept_gal_per_hr
self.fuel_avail = fuel_avail_gal
self.min_turn_down = min_turn_down_pct
self.reopt_class = 'GENERATOR'
self.outage_start_hour = outage_start_hour
self.outage_end_hour = outage_end_hour
self.time_steps_per_hour = time_steps_per_hour
self.generator_only_runs_during_grid_outage = kwargs[
'generator_only_runs_during_grid_outage']
self.fuel_avail_before_outage_pct = fuel_avail_before_outage_pct
self.generator_sells_energy_back_to_grid = kwargs[
'generator_sells_energy_back_to_grid']
self.diesel_fuel_cost_us_dollars_per_gallon = kwargs[
'diesel_fuel_cost_us_dollars_per_gallon']
self.derate = 0.0
self.loads_served = ['retail', 'storage']
self.incentives = Incentives(**kwargs)
if max_kw < min_kw:
min_kw = max_kw
self.min_kw = min_kw
self.max_kw = max_kw
self.existing_kw = existing_kw
self.emissions_factor_lb_CO2_per_gal = emissions_factor_lb_CO2_per_gal
# no net-metering for gen so it can only sell in "wholesale" bin (and not "export" bin)
if self.generator_sells_energy_back_to_grid:
self.loads_served.append('wholesale')
dfm.add_generator(self)
def __init__(self,
dfm,
degradation_pct,
time_steps_per_hour=1,
acres_per_kw=6e-3,
kw_per_square_foot=0.01,
existing_kw=0.0,
tilt=0.537,
azimuth=180,
**kwargs):
super(PV, self).__init__(**kwargs)
self.degradation_pct = degradation_pct
self.nmil_regime = 'BelowNM'
self.reopt_class = 'PV'
self.acres_per_kw = acres_per_kw
self.kw_per_square_foot = kw_per_square_foot
self.time_steps_per_hour = time_steps_per_hour
self.incentives = Incentives(**kwargs)
self.tilt = tilt
self.azimuth = azimuth
self.pvwatts_prod_factor = None
self.existing_kw = existing_kw
# if user hasn't entered the tilt (default value is 0.537), tilt value gets assigned based on array_type
if self.tilt == 0.537:
if kwargs.get(
'array_type'
) == 0: # 0 are Ground Mount Fixed (Open Rack) arrays, we assume an optimal tilt
"""
start assuming the site is in the northern hemisphere, set the tilt to the latitude and leave the
default azimuth of 180 (unless otherwise specified)
"""
self.tilt = kwargs.get('latitude')
if kwargs.get('latitude') < 0:
"""
if the site is in the southern hemisphere, now set the tilt to the positive latitude value and
change the azimuth to 0. Also update kwargs going forward so they get saved to the database later
show up in final results
"""
self.tilt = -1 * self.tilt
self.azimuth = 0
else: # All other tilts come from lookup table included in the array_type_to_tilt_angle dictionary above
self.tilt = PV.array_type_to_tilt_angle[kwargs.get(
'array_type')]
self.pvwatts = PVWatts(time_steps_per_hour=self.time_steps_per_hour,
azimuth=self.azimuth,
tilt=self.tilt,
**self.kwargs)
dfm.add_pv(self)