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_per_district (pandas.DataFrame) –
-
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
- CTS_per_district (pandas.DataFrame) –