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code that needs to be reviewed to see what is causing errors #3

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code that needs to be reviewed to see what is causing errors #3

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fb04506
code that needs to be reviewed to see what is causing errors
rachel-g-long Oct 26, 2023
cacaa04
changing 'gen' instances to 'generator'
rachel-g-long Nov 13, 2023
01d42f1
Merge branch 'main' of https://github.com/pnnl/MCOR into GPIQ-2775
rachel-g-long Nov 13, 2023
7af5ecf
updated existing_generator params
rachel-g-long Nov 15, 2023
99aa755
Merge branch 'main' into GPIQ-2775
rachel-g-long Nov 20, 2023
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5 changes: 3 additions & 2 deletions data/parameter_validation.csv
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Original file line number Diff line number Diff line change
Expand Up @@ -22,9 +22,10 @@ electricity_rate,"int,float",0,1,,,,,
end_year,int,1998,2021,,,,,
existing,bool,,,,,,,
existing_components,dict,,,,,check_existing_components,,"Existing components can only include PV, Battery, Generator, or FuelTank objects, and have keys 'pv', 'batt', 'gen', or 'fuel_tank'."
existing_generator,bool,,,,,check_existing_generator,,
filter_constraints,list,,,,,check_filter_constraints,,"The filter_constraints list must contain dictionaries with the format: {parameter, type, value} where parameter can be any of the following: capital_cost_usd, pv_area_ft2, annual_benefits_usd, simple_payback_yr, fuel_used_gal mean, fuel_used_gal most-conservative, pv_capacity, or pv_percent mean and type can be [max, min] and value is the maximum or minimum allowable value."
fuel_curve_degree,int,1,3,,,,,
fuel_curve_model,dict,,,,,check_fuel_curve_model,,"The generator fuel curve model must be of the form {'1/4 Load (gal/hr)': val, '1/2 Load (gal/hr)': val, '3/4 Load (gal/hr)': val,
fuel_curve_model,dict,,,,,check_fuel_curve_model,,"The generator fuel curve model must be of the form {'1/4 Load (gal/hr)': val, '1/2 Load (gal/hr)': val, '3/4 Load (gal/hr)': val,
'Full Load (gal/hr)': val}"
fuel_used_gal,"int,float",0,,,,,,
gen_percent,"int,float",,,,,,,
Expand Down Expand Up @@ -142,4 +143,4 @@ om_cost,"int,float",0,500,,,,,
demand_rate_list,"int,float,list",,,,,check_demand_rate_list,,Demand charges must be in the form of a number or a list with 12 elements.
demand_rate,"int,float",0,50,,,,,
solar_source,str,,,"nsrdb,himawari",,check_solar_source,"start_year,end_year",The NSRDB dataset only contains data from 1998-2021. The Himawari dataset only contains data from 2016-2020.
scenario_criteria,str,,,"pv,gen",,,,
scenario_criteria,str,,,"pv,generator",,,,
15 changes: 13 additions & 2 deletions main_files/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,6 +86,7 @@ def run_mcor(input_dict):
net_metering_rate=net_metering_inputs["net_metering_rate"],
demand_rate=demand_rate_inputs["demand_rate"],
existing_components=existing_components_inputs["existing_components"],
existing_generator='existing_generator' in input_dict['existing_components_inputs'],
output_tmy=True,
validate=True,
net_metering_limits=net_metering_inputs["net_metering_limits"],
Expand All @@ -101,7 +102,9 @@ def run_mcor(input_dict):
optim.get_load_profiles()

# Run all simulations
optim.run_sims_par()
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You should change this back.

# optim.run_sims_par()
#run without multi-threading
optim.run_sims()

# Filter and rank results
optim.parse_results()
Expand Down Expand Up @@ -202,7 +205,15 @@ def run_mcor(input_dict):
# input_dict["existing_components_inputs"]["pv"] = PV(existing=True, pv_capacity=100, tilt=tilt, azimuth=azimuth,
# module_capacity=0.360, module_area=3, spacing_buffer=2,
# pv_tracking='fixed', pv_racking='ground')
# input_dict["existing_components_inputs"]["existing_components"] = {'pv': pv}
# input_dict["existing_components_inputs"]["existing_components"] = {"pv": ["pv"]}

input_dict["existing_components_inputs"]["existing_generator"] = Generator(existing=True, rated_power=500, num_units=1,
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I think we'll want to specify all of the parameters that are passed into the Generator object in the input_dict and then create the Generator object separately, probably in microgrid_optimizer.define_grid(). The code that will be creating the input_dict in gridpiq will not have access to the Generator class, only the run_mcor function.

We should also do the same for any existing PV or Battery objects.

fuel_curve_model={'1/4 Load (gal/hr)': 11, '1/2 Load (gal/hr)': 18.5,
'3/4 Load (gal/hr)': 26.4, 'Full Load (gal/hr)': 35.7},
capital_cost=191000, ideal_minimum_load=0.3,
loading_level_to_add_unit=0.9,
loading_level_to_remove_unit=0.3, validate=True)
input_dict["existing_components_inputs"]["existing_components"] = {'generator': input_dict["existing_components_inputs"]["existing_generator"]}

# Specific PV and battery sizes dictionary
input_dict["specific_pv_battery_sizes_inputs"] = {}
Expand Down
68 changes: 39 additions & 29 deletions microgrid_optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -279,6 +279,7 @@ def __init__(self, power_profiles, temp_profiles, night_profiles,
net_metering_limits=None,
generator_buffer=1.1,
gen_power_percent=(), existing_components={},
existing_generator=False,
off_grid_load_profile=None,
output_tmy=False, validate=True):

Expand All @@ -301,6 +302,7 @@ def __init__(self, power_profiles, temp_profiles, night_profiles,
self.generator_buffer = generator_buffer
self.gen_power_percent = gen_power_percent
self.existing_components = existing_components
self.existing_generator = existing_generator
self.off_grid_load_profile = off_grid_load_profile
self.output_tmy = output_tmy
self.load_profiles = []
Expand All @@ -321,6 +323,7 @@ def __init__(self, power_profiles, temp_profiles, night_profiles,
'battery_params': battery_params,
'duration': duration,
'gen_power_percent': gen_power_percent,
'existing_generator': existing_generator,
'dispatch_strategy': dispatch_strategy,
'batt_sizing_method': batt_sizing_method,
'system_costs': system_costs}
Expand Down Expand Up @@ -391,7 +394,7 @@ def size_PV_for_netzero(self):
# Calculate round-trip efficiency based on battery and inverter
# efficiency
system_rte = self.battery_params['one_way_battery_efficiency'] ** 2 \
* self.battery_params['one_way_inverter_efficiency'] ** 2
* self.battery_params['one_way_inverter_efficiency'] ** 2

# Calculate the amount of pv energy lost through
# charging/discharging batteries at the net zero capacity
Expand Down Expand Up @@ -464,7 +467,7 @@ def size_batt_for_no_pv_export(self, pv_sizes, load_profile):
excess_pv['pv_base'] = self.tmy_solar.values
for size in pv_sizes:
excess_pv[int(size)] = excess_pv['pv_base'] * size
excess_pv['{}_exported'.format(int(size))] = excess_pv[int(size)]\
excess_pv['{}_exported'.format(int(size))] = excess_pv[int(size)] \
- excess_pv['load']
excess_pv[excess_pv < 0] = 0

Expand Down Expand Up @@ -860,9 +863,14 @@ def aggregate_by_system(self, system, validate=True):
log_error(message)
raise Exception(message)

# Size and dispatch generator
simulation.size_single_generator(
self.system_costs['generator_costs'], validate=False)
if not self.existing_generator:
# Size and dispatch generator
simulation.size_single_generator(
self.system_costs['generator_costs'], validate=False)
else:
simulation.calc_existing_generator_dispatch(
self.system_costs['generator_costs'], validate=False
)

# Add the results to the lists
results_summary['pv_percent'] += \
Expand Down Expand Up @@ -923,13 +931,14 @@ def aggregate_by_system(self, system, validate=True):
results_summary['load_duration']['max_%_kW_not_met_max'] = \
max_kW_not_met.fillna(0).max(axis=1)

# Find the simulation with the largest generator and add that
# generator object to the system
max_gen_sim_num = \
np.where(results_summary['generator_power_kW']
== max(results_summary['generator_power_kW']))[0][0]
max_gen_sim = system.get_simulation(max_gen_sim_num)
system.add_component(max_gen_sim.generator_obj, validate=False)
if not self.existing_generator:
# Find the simulation with the largest generator and add that
# generator object to the system
max_gen_sim_num = \
np.where(results_summary['generator_power_kW']
== max(results_summary['generator_power_kW']))[0][0]
max_gen_sim = system.get_simulation(max_gen_sim_num)
system.add_component(max_gen_sim.generator_obj, validate=False)

return results_summary, system

Expand Down Expand Up @@ -988,7 +997,7 @@ def parse_results(self):
system.set_outputs(results_summary, validate=False)

# Turn results into a dataframe
system_row = pd.DataFrame.from_dict(results_summary).transpose().\
system_row = pd.DataFrame.from_dict(results_summary).transpose(). \
stack()
system_row.index = [' '.join(col).strip()
for col in system_row.index.values]
Expand Down Expand Up @@ -1194,12 +1203,12 @@ def plot_best_system(self, scenario_criteria='pv', scenario_num=None, validate=T
if scenario_criteria == 'pv':
# Find the outage periods with the max and min PV
criteria_dict = {key: val.sum() for key, val
in enumerate(self.power_profiles)}
in enumerate(self.power_profiles)}
scenario_label = 'Solar Irradiance Scenario'
else:
# Find the outage periods with the max and min generator runtime
criteria_dict = {key: val for key, val
in enumerate(system.outputs['fuel_used_gal'])}
in enumerate(system.outputs['fuel_used_gal'])}
scenario_label = 'Fuel Consumption Scenario'
max_scenario = max(criteria_dict, key=criteria_dict.get)
min_scenario = min(criteria_dict, key=criteria_dict.get)
Expand Down Expand Up @@ -1297,7 +1306,7 @@ def plot_system_dispatch(self, num_systems=None, plot_per_fig=3,
for plot_num, (system_name, _) in enumerate(
self.results_grid.iloc[
fig_num * plot_per_fig:fig_num * plot_per_fig + num_plots].
iterrows()):
iterrows()):
# Plot the maximum PV outage dispatch
ax = fig.add_subplot(num_plots, 2, plot_num * 2 + 1)
self.get_system(system_name).plot_dispatch(max_pv, ax=ax)
Expand Down Expand Up @@ -1396,13 +1405,13 @@ def format_inputs(self, spg):
if 'generator' in self.existing_components:
inputs['Existing Equipment'].loc['Generator'] = \
'{} units of {}kW'.format(
self.existing_components['generator'].num_units,
self.existing_components['generator'].rated_power)
self.existing_components['generator'].num_units,
self.existing_components['generator'].rated_power)
if 'battery' in self.existing_components:
inputs['Existing Equipment'].loc['Battery'] = \
'{}kW, {}kWh'.format(
self.existing_components['battery'].power,
self.existing_components['battery'].batt_capacity)
self.existing_components['battery'].power,
self.existing_components['battery'].batt_capacity)
if 'fuel_tank' in self.existing_components:
inputs['Existing Equipment'].loc['FuelTank'] = \
'{}gal'.format(self.existing_components['fuel_tank'].tank_size)
Expand All @@ -1429,7 +1438,7 @@ def format_inputs(self, spg):

assumptions['Generator'] = pd.DataFrame.from_dict(
{'sizing buffer': '{:.0f}%'.format(
self.generator_buffer*100-100)}, orient='index')
self.generator_buffer * 100 - 100)}, orient='index')

return inputs, assumptions

Expand Down Expand Up @@ -1515,6 +1524,7 @@ def save_results_to_file(self, spg, filename='simulation_results'):
for _ in self.gen_power_percent:
units += ['kW', 'gallons', 'gallons', '$', '', '', '', 'kWh',
'kWh', 'kW', 'kW']

format_results.loc['units'] = units

format_results.columns = [col.replace('_', ' ').capitalize()
Expand Down Expand Up @@ -1671,20 +1681,20 @@ def plot_compare_metrics(self, x_var='simple_payback_yr',

# Check that vars exist in results grid
if x_var not in self.results_grid.columns or y_var not in self.results_grid.columns:
return('ERROR: {} or {} are not valid output metrics, please '
'choose one of the following options: {}'.format(
x_var, y_var, ', '.join(self.results_grid.columns.values)))
return ('ERROR: {} or {} are not valid output metrics, please '
'choose one of the following options: {}'.format(
x_var, y_var, ', '.join(self.results_grid.columns.values)))

# Make pv and batt sizes categorical, so exact sizes are shown
# in the legend
results_mod = self.results_grid.copy()
results_mod['pv_capacity'] = results_mod['pv_capacity'].apply(
lambda x: str(int(x))+'kW')
pv_order = [str(elem2)+'kW' for elem2 in np.flipud(
lambda x: str(int(x)) + 'kW')
pv_order = [str(elem2) + 'kW' for elem2 in np.flipud(
np.sort([int(elem[:-2]) for elem in results_mod['pv_capacity'].unique()]))]
results_mod['battery_power'] = results_mod['battery_power'].apply(
lambda x: str(int(x))+'kW')
batt_order = [str(elem2)+'kW' for elem2 in np.flipud(
lambda x: str(int(x)) + 'kW')
batt_order = [str(elem2) + 'kW' for elem2 in np.flipud(
np.sort([int(elem[:-2]) for elem in results_mod['battery_power'].unique()]))]

# Create plot
Expand Down Expand Up @@ -1767,7 +1777,7 @@ def get_electricity_rate(location, validate=True):

# Return the electricity rate for that state in $/kWh
return rates.set_index('Name').loc[
state, 'Average retail price (cents/kWh)'] / 100
state, 'Average retail price (cents/kWh)'] / 100

except Exception as e:
# If there is an error, return the median electricity rate
Expand Down
77 changes: 11 additions & 66 deletions microgrid_simulator.py
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Expand Up @@ -395,9 +395,7 @@ def size_single_generator(self, generator_options, validate=True):
self.dispatch_df[['load_not_met']], self.duration, validate=False)
self.load_duration_df = calculate_load_duration(grouped_load, validate=False)

def calc_existing_generator_dispatch(self, generator_options,
add_additional_generator=True,
validate=True):
def calc_existing_generator_dispatch(self, generator_options, validate=True):
"""
If there is an existing generator, determine how it meets the load and consumes fuel.

Expand All @@ -412,12 +410,12 @@ def calc_existing_generator_dispatch(self, generator_options,

# Validate input parameters
if validate:
args_dict = {'generator_options': generator_options,
'add_additional_generator': add_additional_generator}
args_dict = {'generator_costs': generator_options}
validate_all_parameters(args_dict)

# Get info from existing generator
gen = self.system.components['generator']

self.generator_power_kW = gen.rated_power

# Create a temporary dataframe to hold load not met cropped at the existing generator
Expand All @@ -435,68 +433,14 @@ def calc_existing_generator_dispatch(self, generator_options,
self.dispatch_df.loc[self.dispatch_df['load_not_met_by_generator'] < 0,
'load_not_met_by_generator'] = 0

# If the load cannot be fully met by the existing generator
if self.dispatch_df['load_not_met_by_generator'].sum() > 0:

# If another generator can be added
if add_additional_generator:

# Total rated power (including multiple units together) based on max unmet
# power
max_power = self.dispatch_df['load_not_met_by_generator'].max()

# Find the smallest generator with sufficent rated power, assumes generators
# are sorted from smallest to largest
addl_gen = None
num_gen = 1
while addl_gen is None:
# Find an appropriately sized generator
best_gen = generator_options[generator_options.index
* num_gen >= max_power
* self.generator_buffer]

# If no single generator is large enough, increase the number of
# generators
if not len(best_gen):
num_gen += 1
else:
# Create generator object
best_gen = best_gen.iloc[0]
self.generator_power_kW += best_gen.name*num_gen
addl_gen = Generator(
existing=False, rated_power=best_gen.name,
num_units=num_gen,
fuel_curve_model=best_gen[
['1/4 Load (gal/hr)', '1/2 Load (gal/hr)',
'3/4 Load (gal/hr)', 'Full Load (gal/hr)']].to_dict(),
capital_cost=best_gen['Cost (USD)'],
validate=False)
self.generator_obj = addl_gen

# Calculate the load duration curve and fuel consumption for the additional
# generator
grouped_load, addl_fuel_used = \
addl_gen.calculate_fuel_consumption(
self.dispatch_df[['load_not_met_by_generator']],
self.duration, validate=False)
self.load_duration_df = calculate_load_duration(grouped_load,
validate=False)
self.fuel_used_gal = existing_gen_fuel_used + addl_fuel_used

# If another generator cannot be dispatched
else:
self.load_duration_df = pd.DataFrame(
0, index=temp_load_duration_curve.index,
columns=temp_load_duration_curve.columns)
self.fuel_used_gal = existing_gen_fuel_used


# If the existing generator can meet load, use empty load duration curve and existing
# fuel used
else:
self.load_duration_df = pd.DataFrame(
0, index=temp_load_duration_curve.index,
columns=temp_load_duration_curve.columns)
self.fuel_used_gal = existing_gen_fuel_used

self.load_duration_df = pd.DataFrame(
0, index=temp_load_duration_curve.index,
columns=temp_load_duration_curve.columns)
self.fuel_used_gal = existing_gen_fuel_used

def get_load_breakdown(self):
return self.load_breakdown
Expand Down Expand Up @@ -639,7 +583,8 @@ def calculate_load_duration(grouped_load, validate=True):
# Run the simulation
sim.scale_power_profile()
sim.calc_dispatch()
sim.size_single_generator(generator_options, validate=False)
# sim.size_single_generator(generator_options, validate=False)
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One of these two lines needs to but uncommented for it to run, right?

# sim.calc_existing_generator_dispatch(generator_options, validate=False)

# Plot dispatch
sim.dispatch_df[['load', 'pv_power', 'delta_battery_power', 'load_not_met']].plot()
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