service_sector

CTS_demand_scale(aggregation_level)[source]

Description: caling the demand curves to the annual demand of the respective aggregation level

Parameters:aggregation_level (str) – aggregation_level : str if further processing is to be done in zensus cell level ‘other’ else ‘dsitrict’
Returns:
  • CTS_per_district (pandas.DataFrame) –
    if aggregation =’district’
    Profiles scaled up to annual demand
    else
    0
  • CTS_per_grid (pandas.DataFrame) –
    if aggregation =’district’
    Profiles scaled up to annual demandd
    else
    0
  • CTS_per_zensus (pandas.DataFrame) –
    if aggregation =’district’
    0
    else
    Profiles scaled up to annual demand
cts_demand_per_aggregation_level(aggregation_level, scenario)[source]

Description: Create dataframe assigining the CTS demand curve to individual zensus cell based on their respective NUTS3 CTS curve

Parameters:aggregation_level (str) – if further processing is to be done in zensus cell level ‘other’ else ‘dsitrict’
Returns:
  • CTS_per_district (pandas.DataFrame) –
    if aggregation =’district’
    NUTS3 CTS profiles assigned to individual zensu cells and aggregated per district heat area id
    else
    empty dataframe
  • CTS_per_grid (pandas.DataFrame) –
    if aggregation =’district’
    NUTS3 CTS profiles assigned to individual zensu cells and aggregated per mv grid subst id
    else
    empty dataframe
  • CTS_per_zensus (pandas.DataFrame) –
    if aggregation =’district’
    empty dataframe
    else
    NUTS3 CTS profiles assigned to individual zensu population id