energy_demand.dwelling_stock package¶
Submodules¶
energy_demand.dwelling_stock.dw_stock module¶
Virtual Dwelling Generator  Generates a virtual dwelling stock

class
energy_demand.dwelling_stock.dw_stock.
Dwelling
(curr_yr, coordinates, floorarea, enduses, driver_assumptions, population=None, age=None, dwtype=None, sector=None, gva=None)[source]¶ Bases:
object
Dwelling or aggregated group of dwellings
 Parameters
curr_yr (int) – Current year of simulation
coordinates (float) – coordinates
dwtype (int) – Dwelling type id. Description can be found in daytype_lu
house_id (int) – Unique ID of dwelling or dwelling group
age (int) – Age of dwelling in years (year the building was built)
pop (float) – Dwelling population
floorarea (float) – Floor area of dwelling
hlc (float) – Heat loss coefficient
hdd (float) – Heating degree days
Note
Depending on service or residential model, not all attributes are filled (then they are inistialised as None or zero)
For every dwelling, the scenario drivers are calculated for each enduse

class
energy_demand.dwelling_stock.dw_stock.
DwellingStock
(dwellings, enduses)[source]¶ Bases:
object
Class of the building stock in a region

energy_demand.dwelling_stock.dw_stock.
generate_dw_existing
(driver_assumptions, enduses, reg_coord, region, curr_yr, dw_lu, floorarea_p, floorarea_by, dwtype_age_distr_by, floorarea_pp, gva_dw_data)[source]¶ Generates dwellings according to age, floor area and distribution assumption
 Parameters
assumptions (dict) – Assumptions
enduses (list) – Enduses
region (dict) – Region name
curr_yr (int) – Base year
dw_lu (dict) – Dwelling type lookup
floorarea_p (dict) – Fraction of floor area per dwelling type
floorarea_by (dict) – Floor area of base year
dwtype_age_distr_by (dict) – Age distribution of dwelling
floorarea_pp (dict) – Floor area per person
tot_floorarea_cy (float) – Floor are in current year
pop_by (dict) – Population in base year
 Returns
dw_stock_by – Dwelling stocks in a list
 Return type

energy_demand.dwelling_stock.dw_stock.
generate_dw_new
(driver_assumptions, reg_coord, enduses, dwtypes, region, curr_yr, floorarea_p_by, floorarea_pp_cy, dw_stock_new_dw, new_floorarea_cy, gva_dw_data)[source]¶ Generate dwelling objects for all new dwellings
All new dwellings are appended to the existing building stock of the region
 Parameters
 Returns
dw_stock_new_dw – List with appended dwellings
 Return type
Notes
The floor area id divided proprtionally depending on dwelling type Then the population is distributed builindg is creatd

energy_demand.dwelling_stock.dw_stock.
get_dwtype_distr
(dwtype_distr_by, dwtype_distr_fy, base_yr, sim_period)[source]¶ Calculates the annual distribution of dwelling types based on assumption of base and end year distribution
 Parameters
 Returns
dwtype_distr – Contains all dwelling type distribution for every year
 Return type
Note
A linear change over time is assumed
Example
out = {year: {‘dwtype’: 0.3}}

energy_demand.dwelling_stock.dw_stock.
get_dwtype_floor_area
(dwtype_floorarea_by, dwtype_floorarea_future, base_yr, sim_period)[source]¶ Calculates the floor area per dwelling type for every year
 Parameters
 Returns
dwtype_floor_area – Contains the floor area change per dwelling type
 Return type
Note
A linear change over time is assumed
Example
out = {year: {‘dwtype’: 0.3}}

energy_demand.dwelling_stock.dw_stock.
get_floorare_pp
(floorarea, reg_pop_by, base_yr, sim_period, assump_diff_floorarea_pp)[source]¶ Calculate future floor area per person depending on assumptions on final change and base year data
 Parameters
:param : base year :type : int :param sim_period: Simulation period :type sim_period: list :param assump_diff_floorarea_pp: Assumption of change in floor area up to end of simulation :type assump_diff_floorarea_pp: float
 Returns
floor_area_pp – Contains all values for floor area per person for every year
 Return type
Note
Linear change of floor area per person is assumed over time

energy_demand.dwelling_stock.dw_stock.
get_floorarea_dwtype_p
(dw_lookup, dw_floorarea, dwtype_distr)[source]¶ Calculates the percentage of the total floor area belonging to each dwelling type. Depending on average floor area per dwelling type and the dwelling type distribution, the percentages are calculated for ever simulation year
 Parameters
 Returns
dw_floorarea_p – Contains the percentage of the total floor area for each dwtype for every simulation year (must be 1.0 in tot)
 Return type
Notes
This calculation is necessary as the share of dwelling types may differ depending the year

energy_demand.dwelling_stock.dw_stock.
get_hlc
(dw_type, age)[source]¶ Calculates the linearly derived heat loss coeeficients depending on age and dwelling type
 Parameters
 Returns
hls
 Return type
Heat loss coefficient [W/m2 * K]
Notes
Source: Linear trends derived from Table 3.17 ECUK Tables https://www.gov.uk/government/collections/energyconsumptionintheuk

energy_demand.dwelling_stock.dw_stock.
get_tot_pop
(dwellings)[source]¶ Get total population of all dwellings

energy_demand.dwelling_stock.dw_stock.
rs_dw_stock
(region, assumptions, scenario_data, sim_yrs, dwelling_types, enduses, reg_coord, driver_assumptions, curr_yr, base_yr, virtual_building_stock_criteria)[source]¶ Creates a virtual building stock for every year and region
 Parameters
 Returns
dwelling_stock (dict) – Building stock wei
reg_dw_stock_by (Base year building stock) – reg_building_stock_yr : Building stock for every simulation year
Notes
The assumption about internal temperature change is used as for each dwelling the hdd are calculated based on wheater data and assumption on t_base
Doesn’t take floor area as an input but calculates floor area based on floor area pp parameter. However, floor area could be read in by:
1.) Inserting tot_floorarea_cy = data[‘rs_floorarea’][curr_yr]
 2.) Replacing ‘dwtype_floor_area’, ‘dwtype_distr’ and ‘data_floorarea_pp’
with more specific information from real building stock model

energy_demand.dwelling_stock.dw_stock.
ss_dw_stock
(region, enduses, sectors, scenario_data, reg_coord, assumptions, curr_yr, base_yr, virtual_building_stock_criteria)[source]¶ Create dwelling stock for service sector
 Parameters
 Returns
dwelling_stock – List with objects
 Return type
Note
Iterate years and change floor area depending on assumption on linear change up to ey