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refactor: more intermediate output columns and input validation #105

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Mar 4, 2020
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refactor: more intermediate output columns and input validation #105

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920cacb
refactor: more intermediate output columns and input validation
dmuldrew Mar 3, 2020
baea5c3
chore: pep8 tweaks
dmuldrew Mar 3, 2020
8e9be7d
fix: error typo
dmuldrew Mar 3, 2020
e68c0bb
fix: pep8 space fix
dmuldrew Mar 4, 2020
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146 changes: 118 additions & 28 deletions powersimdata/scaling/clean_capacity_scaling/auto_capacity_scaling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,18 +21,32 @@ def set_next_sim_hours(next_sim_hours):

def targets_from_data_frame(self, data_frame):
for row in data_frame.itertuples():
self.add_target(TargetManager(row.region_name,
row.ce_target_fraction,
row.ce_category,
row.total_demand,
row.external_ce_historical_amount,
row.solar_percentage))

if row.solar_percentage == 'None':
solar_percentage = None
else:
solar_percentage = row.solar_percentage
target = TargetManager(row.region_name,
row.ce_target_fraction,
row.ce_category,
row.total_demand,
row.external_ce_historical_amount,
solar_percentage)
if row.allowed_resources == '':
allowed_resources = ['solar', 'wind']
else:
split_resources = row.allowed_resources.split(',')
allowed_resources = [x.strip() for x in split_resources]
target.set_allowed_resources(allowed_resources)
self.add_target(target)

def add_target(self, target_manager_obj):
"""
Add target to strategy object
:param target_manager_obj: target object to be added
"""
assert (isinstance(target_manager_obj, TargetManager)), \
"Input must be of TargetManager type"
self.targets[target_manager_obj.region_name] = target_manager_obj

@staticmethod
Expand Down Expand Up @@ -70,22 +84,47 @@ def data_frame_of_next_capacities(self):
"""
target_capacities = []
for tar in self.targets:
solar_added_capacity, wind_added_capacity = \
self.targets[tar].calculate_added_capacity()
# solar_added_capacity, wind_added_capacity =
# self.targets[tar].calculate_added_capacity_gen_constant()
if self.targets[tar].ce_target_fraction == 0:
solar_added_capacity, wind_added_capacity = (0, 0)
else:
solar_added_capacity, wind_added_capacity =\
self.targets[tar].calculate_added_capacity()
target_capacity = [
self.targets[tar].region_name,
self.targets[tar].resources['solar'].calculate_next_capacity(
solar_added_capacity),
self.targets[tar].resources['wind'].calculate_next_capacity(
wind_added_capacity)]
self.targets[tar].ce_target_fraction,
self.targets[tar].ce_target,
self.targets[tar].calculate_prev_ce_generation(),
self.targets[tar].calculate_ce_shortfall(),
solar_added_capacity,
wind_added_capacity,
self.targets[tar].resources['solar'].prev_capacity,
self.targets[tar].resources['wind'].prev_capacity,
self.targets[tar].resources[
'solar'].calculate_expected_cap_factor(),
self.targets[tar].resources[
'wind'].calculate_expected_cap_factor(),
self.targets[tar].resources[
'solar'].calculate_next_capacity(solar_added_capacity),
self.targets[tar].resources[
'wind'].calculate_next_capacity(wind_added_capacity)]
target_capacities.append(target_capacity)
target_capacities_df = pd.DataFrame(
target_capacities,
columns=['region_name',
'next_solar_capacity',
'next_wind_capacity'])

target_capacities_df = pd.DataFrame(target_capacities,
columns=[
'region_name',
'ce_target_fraction',
'ce_target',
'previous_ce_generation',
'clean_energy_shortfall',
'solar_added_capacity',
'wind_added_capacity',
'solar_prev_capacity',
'wind_prev_capacity',
'solar_expected_cap_factor',
'wind_expected_cap_factor',
'next_solar_capacity',
'next_wind_capacity'])
target_capacities_df = target_capacities_df.set_index('region_name')
return target_capacities_df


Expand Down Expand Up @@ -241,8 +280,6 @@ def calculate_capacity_scaling(self):
solar_prev_capacity = self.calculate_total_capacity('solar')
wind_prev_capacity = self.calculate_total_capacity('wind')
solar_added, wind_added = self.calculate_total_added_capacity()
# solar_added, wind_added =
# self.calculate_total_added_capacity_gen_constant()

solar_scaling = (solar_added / solar_prev_capacity) + 1
wind_scaling = (wind_added / wind_prev_capacity) + 1
Expand All @@ -259,15 +296,32 @@ def data_frame_of_next_capacities(self):
for tar in self.targets:
target_capacity = [
self.targets[tar].region_name,
self.targets[tar].resources['solar'].prev_capacity *
self.targets[tar].ce_target_fraction,
self.targets[tar].ce_target,
self.targets[tar].calculate_prev_ce_generation(),
self.targets[tar].calculate_ce_shortfall(),
solar_scaling,
self.targets[tar].resources['wind'].prev_capacity *
wind_scaling]
wind_scaling,
self.targets[tar].resources['solar'].prev_capacity,
self.targets[tar].resources['wind'].prev_capacity,
self.targets[tar].resources[
'solar'].prev_capacity * solar_scaling,
self.targets[tar].resources[
'wind'].prev_capacity * wind_scaling]
target_capacities.append(target_capacity)
target_capacities_df = pd.DataFrame(target_capacities,
columns=['region_name',
'ce_target_fraction',
'ce_target',
'previous_ce_generation',
'clean_energy_shortfall',
'solar_scaling',
'wind_scaling',
'solar_prev_capacity',
'wind_prev_capacity',
'next_solar_capacity',
'next_wind_capacity'])
target_capacities_df = target_capacities_df.set_index('region_name')
return target_capacities_df


Expand All @@ -284,6 +338,21 @@ def __init__(self, region_name, ce_target_fraction, ce_category,
clean energy, etc.
:param total_demand: total demand for region
"""
assert (type(region_name) == str), "region_name must be a string"
assert (type(ce_category) == str), "ce_category must be a string"
assert (total_demand >= 0), "total_demand must be greater than zero"
assert (0 <= ce_target_fraction <= 1), "ce_target_fraction must be " \
"between 0 and 1"
assert (external_ce_historical_amount >= 0), "external_ce_historical" \
"_amount must be greater"\
" than zero"
assert (type(solar_percentage) == float or
type(solar_percentage) == int or
solar_percentage is None), "solar_percentage must be" \
" a number or None"
if type(solar_percentage) == float:
assert (0 <= solar_percentage <= 1), "solar_percentage must be " \
"between 0 and 1"
self.region_name = region_name
self.ce_category = ce_category

Expand Down Expand Up @@ -375,6 +444,8 @@ def add_resource(self, resource):
Adds resource to TargetManager
:param resource: resource to be added
"""
assert (isinstance(resource, Resource)), "Input must be of Resource " \
"type"
self.resources[resource.name] = resource

def get_resource(self, resource_name):
Expand Down Expand Up @@ -452,13 +523,18 @@ def save_target_as_pickle(self):
json_file.close()

def __str__(self):
return json.dumps(json.loads(jsonpickle.encode(self)), indent=4,
sort_keys=True)
return json.dumps(json.loads(
jsonpickle.encode(self, unpicklable=False)),
indent=4,
sort_keys=True)


class Resource:
def __init__(self, name, prev_scenario_num):
# todo: input validation
assert (type(name) == str), "name must be a string"
assert (type(prev_scenario_num) == int), "prev_scenario_num must be " \
"an integer"
self.name = name
self.prev_scenario_num = prev_scenario_num
self.no_congestion_cap_factor = None
Expand All @@ -477,6 +553,12 @@ def set_capacity(self, no_congestion_cap_factor, prev_capacity,
:param prev_capacity: capacity from scenario run
:param prev_cap_factor: capacity factor from scenario run
"""
assert (0 <= no_congestion_cap_factor <= 1), \
"no_congestion_cap_factor must be between 0 and 1"
assert (0 <= prev_cap_factor <= 1),\
"prev_cap_factor must be between 0 and 1"
assert (prev_capacity >= 0), "prev_capacity must be greater than zero"

self.no_congestion_cap_factor = no_congestion_cap_factor
self.prev_capacity = prev_capacity
self.prev_cap_factor = prev_cap_factor
Expand All @@ -487,6 +569,8 @@ def set_generation(self, prev_generation):
Set generation from scenario run
:param prev_generation: generation from scenario run
"""
assert (prev_generation >= 0), "prev_generation must be greater than "\
"zero"
self.prev_generation = prev_generation

# todo: calculate directly from scenario results
Expand All @@ -496,13 +580,17 @@ def set_curtailment(self, prev_curtailment):
:param prev_curtailment: calculated curtailment from scenario run
:return:
"""
assert (prev_curtailment >= 0), "prev_curtailment must be greater " \
"than zero"
self.prev_curtailment = prev_curtailment

def set_addl_curtailment(self, addl_curtailment):
"""
Set additional curtailment to included in capacity calculations
:param addl_curtailment: additional curtailment
"""
assert (addl_curtailment >= 0), "addl_curtailment must be greater " \
"than zero"
self.addl_curtailment = addl_curtailment

def calculate_expected_cap_factor(self):
Expand All @@ -523,5 +611,7 @@ def calculate_next_capacity(self, added_capacity):
return next_capacity

def __str__(self):
return json.dumps(json.loads(jsonpickle.encode(self)), indent=4,
sort_keys=True)
return json.dumps(json.loads(jsonpickle.encode(self,
unpicklable=False
)),
indent=4, sort_keys=True)
4 changes: 0 additions & 4 deletions powersimdata/scaling/clean_capacity_scaling/tests/test_object_persistence.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -4,10 +4,6 @@
import json


def test_can_pass():
assert 1 == 1


def test_create_json_of_target_object():
# create Pacific
pacific_solar = Resource('solar', 3)
Expand Down
4 changes: 0 additions & 4 deletions powersimdata/scaling/clean_capacity_scaling/tests/test_resource_target_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,10 +4,6 @@
from unittest.mock import patch


def test_can_pass():
assert 1 == 1


def test_expected_cap_factor():
solar = Resource('solar', 3)
solar.set_capacity(0.25, 3700, 0.25)
Expand Down
11 changes: 8 additions & 3 deletions powersimdata/scaling/clean_capacity_scaling/tests/test_target_manager_input.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,10 @@
from powersimdata.scaling.clean_capacity_scaling.auto_capacity_scaling \
import AbstractStrategyManager, TargetManager
import pandas as pd
import pytest


def test_can_pass():
assert 1 == 1


def test_create_targets_from_dataframe():
Expand All @@ -11,7 +14,8 @@ def test_create_targets_from_dataframe():
'ce_target_fraction': [.25, .4],
'total_demand': [200000, 300000],
'external_ce_historical_amount': [0, 0],
'solar_percentage': [.3, .6]}
'solar_percentage': [.3, .6],
'allowed_resources': ['solar', 'wind']}

# future_data = {'total_demand': [200000, 300000],
# 'external_ce_total_gen': [ 0, 0]}
Expand All @@ -38,7 +42,8 @@ def test_populate_strategy_from_dataframe():
'ce_target_fraction': [.25, .4],
'total_demand': [200000, 300000],
'external_ce_historical_amount': [0, 0],
'solar_percentage': [.3, .6]}
'solar_percentage': [.3, .6],
'allowed_resources': ['solar', 'wind']}
planning_dataframe = pd.DataFrame.from_dict(planning_data)

strategy = AbstractStrategyManager()
Expand Down