def _energy_mix_to_emissions_rate(energy_mix: Dict) -> EmissionsPerKwh:
"""
Convert a mix of energy sources into emissions per kWh
https://github.com/responsibleproblemsolving/energy-usage#calculating-co2-emissions
:param energy_mix: A dictionary that breaks down the energy produced into sources, with a total value.
Format will vary, but must have keys for "coal", "petroleum" and "naturalGas" and "total"
:return: an EmissionsPerKwh object representing the average emissions rate
"""
# source: https://github.com/responsibleproblemsolving/energy-usage#conversion-to-co2
emissions_by_source: Dict[str, EmissionsPerKwh] = {
"coal": EmissionsPerKwh.from_kgs_per_kwh(0.995725971),
"petroleum": EmissionsPerKwh.from_kgs_per_kwh(0.8166885263),
"naturalGas": EmissionsPerKwh.from_kgs_per_kwh(0.7438415916),
}
emissions_percentage: Dict[str, float] = {}
for energy_type in energy_mix.keys():
if energy_type not in ["total", "isoCode", "countryName"]:
emissions_percentage[energy_type] = (energy_mix[energy_type] /
energy_mix["total"])
# Weighted sum of emissions by % of contributions
# `emissions_percentage`: coal: 0.5, petroleum: 0.25, naturalGas: 0.25
# `emission_value`: coal: 0.995725971, petroleum: 0.8166885263, naturalGas: 0.7438415916
# `emissions_per_kwh`: (0.5 * 0.995725971) + (0.25 * 0.8166885263) * (0.25 * 0.7438415916)
# >> 0.5358309 kg/kwh
emissions_per_kwh = EmissionsPerKwh.from_kgs_per_kwh(
sum([
emissions_percentage[source] *
value.kgs_per_kwh # % (0.x) # kgs / kwh
for source, value in emissions_by_source.items()
]))
return emissions_per_kwh
def get_region_emissions(self, energy: Energy, geo: GeoMetadata) -> float:
"""
Computes emissions for a region on private infra.
Given an quantity of power consumed, use regional data
on emissions per unit power consumed or the mix of energy sources.
https://github.com/responsibleproblemsolving/energy-usage#calculating-co2-emissions
:param energy: Mean power consumption of the process (kWh)
:param geo: Country and region metadata.
:return: CO2 emissions in kg
"""
try:
country_emissions_data = self._data_source.get_country_emissions_data(
geo.country_iso_code.lower()
)
if geo.region not in country_emissions_data:
# TODO: Deal with missing data, default to something
raise ValueError(
f"Region: {geo.region} not found for Country with ISO CODE : {geo.country_iso_code}"
)
emissions_per_kwh: EmissionsPerKwh = EmissionsPerKwh.from_lbs_per_mwh(
country_emissions_data[geo.region]["emissions"]
)
except DataSourceException: # This country has regional data at the energy mix level, not the emissions level
country_energy_mix_data = self._data_source.get_country_energy_mix_data(
geo.country_iso_code.lower()
)
region_energy_mix_data = country_energy_mix_data[geo.region]
emissions_per_kwh: EmissionsPerKwh = self._energy_mix_to_emissions_rate(
region_energy_mix_data
)
return emissions_per_kwh.kgs_per_kwh * energy.kwh # kgs
def get_country_emissions(self, energy: Energy, geo: GeoMetadata) -> float:
"""
Computes emissions for a country on private infra,
given emissions per unit power consumed at a country level
https://github.com/responsibleproblemsolving/energy-usage#calculating-co2-emissions
:param energy: Mean power consumption of the process (kWh)
:param geo: Country and region metadata
:return: CO2 emissions in kg
"""
# source: https://github.com/responsibleproblemsolving/energy-usage#conversion-to-co2
emissions_by_source: Dict[str, EmissionsPerKwh] = {
"coal": EmissionsPerKwh.from_kgs_per_kwh(0.995725971),
"petroleum": EmissionsPerKwh.from_kgs_per_kwh(0.8166885263),
"naturalGas": EmissionsPerKwh.from_kgs_per_kwh(0.7438415916),
}
energy_mix = self._data_source.get_global_energy_mix_data()
if geo.country_iso_code not in energy_mix:
# TODO: Deal with missing data, default to something
raise Exception()
country_energy_mix: Dict = energy_mix[geo.country_iso_code]
emissions_percentage: Dict[str, float] = {}
for energy_type in country_energy_mix.keys():
if energy_type not in ["total", "isoCode", "countryName"]:
emissions_percentage[energy_type] = (
country_energy_mix[energy_type] /
country_energy_mix["total"])
# Weighted sum of emissions by % of contributions
# `emissions_percentage`: coal: 0.5, petroleum: 0.25, naturalGas: 0.25
# `emission_value`: coal: 0.995725971, petroleum: 0.8166885263, naturalGas: 0.7438415916
# `emissions_per_kwh`: (0.5 * 0.995725971) + (0.25 * 0.8166885263) * (0.25 * 0.7438415916)
# >> 0.5358309 kg/kwh
emissions_per_kwh = EmissionsPerKwh.from_kgs_per_kwh(
sum([
emissions_percentage[source] *
value.kgs_per_kwh # % (0.x) # kgs / kwh
for source, value in emissions_by_source.items()
]))
return emissions_per_kwh.kgs_per_kwh * energy.kwh # kgs
def get_cloud_emissions(self, energy: Energy,
cloud: CloudMetadata) -> float:
"""
Computes emissions for cloud infra
:param energy: Mean power consumption of the process (kWh)
:param cloud: Region of compute
:return: CO2 emissions in kg
"""
df: pd.DataFrame = self._data_source.get_cloud_emissions_data()
emissions_per_kwh: EmissionsPerKwh = EmissionsPerKwh.from_g_per_kwh(
df.loc[(df["provider"] == cloud.provider)
& (df["region"] == cloud.region)]["impact"].item())
return emissions_per_kwh.kgs_per_kwh * energy.kwh # kgs
def get_emissions(energy: Energy, geo: GeoMetadata, timeout=60):
if geo.latitude:
params = {"lat": geo.latitude, "lon": geo.longitude}
else:
params = {"countryCode": geo.country_2letter_iso_code}
resp = requests.get(
URL,
params=params,
headers={"auth-token": CO2_SIGNAL_API_TOKEN},
timeout=timeout,
)
if resp.status_code != 200:
raise CO2SignalAPIError(resp.json()["error"])
carbon_intensity_g_per_kWh = resp.json()["data"]["carbonIntensity"]
emissions_per_kwh: EmissionsPerKwh = EmissionsPerKwh.from_g_per_kwh(
carbon_intensity_g_per_kWh
)
return emissions_per_kwh.kgs_per_kwh * energy.kwh
def get_cloud_emissions_barchart_data(
self,
net_energy_consumed: float,
on_cloud: str,
cloud_provider: str,
cloud_region: str,
) -> Tuple[str, pd.DataFrame]:
if on_cloud == "N":
return (
"",
pd.DataFrame(data={
"region": [],
"emissions": [],
"countryName": []
}),
)
cloud_emissions = self._data_source.get_cloud_emissions_data()
cloud_emissions = cloud_emissions[[
"provider", "providerName", "region", "impact", "countryName"
]]
from codecarbon.core.units import EmissionsPerKwh
cloud_emissions["emissions"] = cloud_emissions.apply(
lambda row: EmissionsPerKwh.from_g_per_kwh(row.impact).kgs_per_kwh
* net_energy_consumed,
axis=1,
)
cloud_emissions_project_region = cloud_emissions[cloud_emissions.region
== cloud_region]
cloud_emissions = cloud_emissions[
(cloud_emissions.provider == cloud_provider)
& (cloud_emissions.region != cloud_region)].sort_values(
by="emissions")
return (
cloud_emissions_project_region.iloc[0, :].providerName,
pd.concat([cloud_emissions_project_region, cloud_emissions]),
)
def get_region_emissions(self, energy: Energy, geo: GeoMetadata) -> float:
"""
Computes emissions for a country on private infra,
given emissions per unit power consumed at a regional level
https://github.com/responsibleproblemsolving/energy-usage#calculating-co2-emissions
:param energy: Mean power consumption of the process (kWh)
:param geo: Country and region metadata.
:return: CO2 emissions in kg
"""
country_emissions_data = self._data_source.get_country_emissions_data(
geo.country_iso_code.lower())
if geo.region not in country_emissions_data:
# TODO: Deal with missing data, default to something
raise Exception(
f"Region: {geo.region} not found for Country with ISO CODE : {geo.country_iso_code}"
)
emissions_per_kwh: EmissionsPerKwh = EmissionsPerKwh.from_lbs_per_mwh(
country_emissions_data[geo.region]["emissions"])
return emissions_per_kwh.kgs_per_kwh * energy.kwh