Model Input - Data Files

Time series data, as well as information about buildings and districts, are provided to the District Energy Model (DEM) through data files. Most of these files are stored in Feather format (Apache Software Foundation, 2025).

This section describes the required files, their contents, and the expected data formats. Although all files must be present for the simulation to run, their entries can be set to zero if a dataset is not relevant to a specific case (for example, the wind power file if wind generation is excluded from the scenario).

All input files must be located within the data directory following the predefined directory structure (see below).

Note

For Switzerland, a complete dataset package is available on Zenodo. After downloading and unzipping the archive, place its contents in the data directory of your project. The required directory structure is already provided.

District_Energy_Model/
├── config/
│   ├── ...
│   └── ...
├── data/
│   ├── community_data/
│   │   └── ...
│   ├── electricity_demand/
│   │   └── ...
│   ├── electricity_mix_national/
│   │   └── electricity_mix.feather
│   ├── heat_demand/
│   │   └── DHW_Profile.feather
│   ├── master_data/
│   │   ├── HDD_and_HDH_profiles/
│   │   │   ├── HDD_Municipality_2023.feather
│   │   │   ├── HDD_Municipality_2030.feather
│   │   │   ├── HDD_Municipality_2040.feather
│   │   │   ├── HDD_Municipality_2050.feather
│   │   │   └── ...
│   │   └── simulation_data/
│   │       ├── df_master_sim.feather
│   │       ├── meta_file_2.feather
│   │       ├── simulation_profiles_file.feather
│   │       └── ...
│   ├── tech_wind_power/
│   │   ├── profiles/
│   │   │   └── ...
│   │   └── p_installed_kW_wind_power.feather
│   └── weather_data/
│       └── com_files/
│           └── ...
├── doc/
│   ├── ...
│   └── ...
├── src/
│   ├── ...
│   └── ...
├── LICENSE.txt
└── README.md

Master file

This file contains information about each individual building, with one row per building. District-level information is derived from this file through aggregation. The file may include data for multiple districts; during a simulation, only the buildings belonging to the specified district are selected.

Each building is identified by a unique identification number (column 0: EGID) and assigned to a municipality represented by a numerical code (column 4: GGDENR). Custom districts can also be analyzed by specifying the buildings included in the district via their EGID values.

For Switzerland, data in columns 0 to 15 (except for columns 1 and 5) is sourced from the Federal Register of Buildings and Dwellings (RBD) (Federal Statistical Office, 2025), and the corresponding column naming conventions have been adopted accordingly (see RBD Catalogue of Attributes).

File name

df_master_sim

Format

.feather

Directory

./data/master_data/simulation_data/

Index

Numeric (integer), 0 to X, where X is

the number buildings contained in the

file.

Number of rows

According to number of buildings.

Number of columns

49

Number

Column

Data type

Description

Source for Swiss dataset

0

EGID

int

Unique identifier assigned to each

building. For Switzerland, these are

allready assigned to each building (see

www.regbl.admin.ch/catalog). For

buildings in other regions or not

existing, a new EGID identifier can be

assigned, but should be different from

those already existing.

Federal Statistical Office, 2025

1

GDEKT

string

Canton, in which the building is

located. For regions outside of

Switzerland, this is not relevant or can

be assigned according to similar

regional entities such as e.g.

provinces. For Switzerland, the short

form is used (e.g., ZH, FR, … ).

Swisstopo, 2024

2

GKAT

float

Building category, adopted according to

Federal Statistical Office (2025). The

categroy code is a numeric integer

consisting of 4 digits. The codes for

each category can be found on

www.regbl.admin.ch/catalog. For example,

category “1020” refers to “Building for

residential use only”. Among others,

this categorisation is used to

distinguis between different types of

energy demand.

Federal Statistical Office, 2025

3

GKLAS

float

Building class, adopted according to

Federal Statistical Office (2025). The

class code is a numeric integer

consisting of 4 digits. The codes for

each class can be found on

www.regbl.admin.ch/catalog. For example,

building class “1211” refers to

“Hotels”, while class “1220” refers to

Office buildings. Among others, this

classification is used to distinguis

between different types of energy

demand.

Federal Statistical Office, 2025

4

GGDENR

int

Unique identifier assigned to each

district. For Switzerland, it is the

number of the commune according to the

Official Register of Swiss Communes in

Switzerland. For other regions or

districts with customised boundaries

other than the official Swiss communes,

new numbers can be assigned (>7000).

They must be unique and not coincide

with existing numbers.

Federal Statistical Office, 2025

5

GGDENAME

string

Name of the district. For municipalities

in Switzerland, it is taken from the

Official directory fo building addresses

(Swisstopo, 2024).

Swisstopo, 2024

6

GKODE

float

E coordinate of the building (for

Switzerland in LV95 standard). Not

relevant for regions other than

Switzerland.

Federal Statistical Office, 2025

7

GKODN

float

N coordinate of the building (for

Switzerland in LV95 standard). Not

relevant for regions other than

Switzerland.

Federal Statistical Office, 2025

8

GBAUJ

float

Year of construction of the building

according to Federal Statistical Office,

  1. See www.regbl.admin.ch/catalog.

Federal Statistical Office, 2025

9

GBAUP

float

Period of construction according to

Federal Statistical Office, 2025. See

www.regbl.admin.ch/catalog.

Federal Statistical Office, 2025

10

GAREA

float

Surface area of building (floor area) in

square meters according to Federal

Statistical Office, 2025. See

www.regbl.admin.ch/catalog.

Federal Statistical Office, 2025

11

GASTW

float

Number of floors and basements,

including ground floor. According to

Federal Statistical Office, 2025. See

www.regbl.admin.ch/catalog.

Federal Statistical Office, 2025

12

GENH1

float

Energy source / heat source 1 described

as numeric code of 4 digits according to

Federal Statistical Office, 2025. See

www.regbl.admin.ch/catalog. For example,

code “7520” refers to “Gas”.

Federal Statistical Office, 2025

13

GENH2

float

Energy source / heat source 2 (if

applicable). Described as numeric code

of 4 digits in the same way as

GENH1.

Federal Statistical Office, 2025

14

GENW1

float

Energy / heat source for hot water 1

described as numeric code of 4 digits

accordint to Federal Statistical Office,

  1. See www.regbl.admin.ch/catalog.

For example, code “7520” refers to

“Gas”.

Federal Statistical Office, 2025

15

GENW2

float

Energy / heat source for hot water 2 (if

applicable). Described as numeric code

of 4 digits in the same way as

GENW1.

Federal Statistical Office, 2025

16

Coord_lat

float

Latitude coordinate of the building in

decimal format (e.g., 47.269056)

Converted from GKODN.

17

Coord_long

float

Longitude coordinate the building in

decimal format (e.g., 8.449859)

Converted from GKODE.

18

PV_Pot

float

Annual rooftop solar photovoltaic

generation potential of the building (in

kWh).

Swiss Federal Office of Energy, 2023

19

PV_Pot_reco

float

Recommended annual rooftop solar

photovoltaic generation potential based

on roof suitability. Subset of

PV_Pot.

Subset calculated from PV_tot.

20

FPV_Pot

float

Annual fassade solar photovoltaic

generation potential of the building (in

kWh).

Swiss Federal Office of Energy, 2023

21

FPV_Pot_reco

float

Recommended annual fassade solar

photovoltaic generation potential based

on fassade suitability. Subset of

FPV_Pot.

Subset calculated from FPV_tot.

22

BeginningOfOperation

string

Commissioning date of the installed

solar photovoltaic system.

Swiss Federal Office of Energy, 2022a

23

InitialPower

float

Initial commissioning capacity of the

installed solar photovoltaic system in

kW. For solar PV systems without

expansion, the initial commissioning

capacity corresponds to the total

capacity.

Swiss Federal Office of Energy, 2022a

24

TotalPower

float

Total installed solar PV capacity

(including any possible expansions) in

kW.

Swiss Federal Office of Energy, 2022a

25

PlantCategory

string

OPTIONAL. Solar PV plant type according

to Swiss Federal Office of Energy

(2022). (Options: “plantcat_8” =

attached; “plantcat_9” = integrated).

Swiss Federal Office of Energy, 2022a

26

TotalEnergy

float

Total annual generated energy in kWh

from solar PV installation.

Calculated based on TotalPower using an

assumed value of full load hours (e.g.,

1000 kWh/kWp).

27

altitude

int

Elevation above sea level of the

building.

Obtained through Open-Elevation API

(www.open-elevation.com)

28

Temperature_mean

float

Mean annual ambient temperature at

building location.

Calculated as mean from hourly

temperature profile.

29

renovation_base

float

Only required for demand_side scenario

with renovation. Year of renovation for

this building (in the future) for

renovation scenario “base” (e.g., 2045).

Calculated using renovation rates

scenario based on Streicher at al.

(2021). See Renovation and heat generator replacement

30

renovation_low

float

Only required for demand_side scenario

with renovation. Year of renovation for

this building (in the future) for

renovation scenario “low” (e.g., 2045).

Calculated using renovation rates

scenario based on Streicher at al.

(2021). See Renovation and heat generator replacement

31

renovation_high

float

Only required for demand_side scenario

with renovation. Year of renovation for

this building (in the future) for

renovation scenario “high” (e.g., 2045).

Calculated using renovation rates

scenario based on Streicher at al.

(2021). See Renovation and heat generator replacement

32

heat_energy_demand_estimate_kWh_combined

float

Annual space heating demand in kWh.

Computed according to Schneeberger et

al. (2025). See also

Space Heating

33

dhw_estimation_kWh_combined

float

Annual domestic hot water (DHW) demand

in kWh.

See Domestic Hot Water (DHW)

34

cluster_number

int

currently not used

n/a

35

kWh_household_sfh

float

If the building is a single family house

(SFH): annual electricity demand in kWh.

Otherwise 0.

See

Residential Buildings

36

kWh_household_mfh

float

If the building is a multi family house

(MFH): annual electricity demand in kWh.

Otherwise 0.

See

Residential Buildings

37

Heating_System

string

Heat flow in DEM nomenclature

(Nomenclature and Abbreviations) for specified

heating system. E.g., v_h_hp for

heat pump (hp) heat flow.

See: Nomenclature and Abbreviations

38

Hot_Water_System

string

Heat flow in DEM nomenclature

(Nomenclature and Abbreviations) for specified hot

water system. E.g., v_hw_hp for heat

pump (hp) hot water flow.

See: Nomenclature and Abbreviations

39

Electricity_Industry

float

Annual electricity demand for industry

(if applicable) in kWh.

See Industry and Services

40

Electricity_Service

float

Annual electricity demand for services

(if applicable) in kWh.

See Industry and Services

41

s_wd_bm

float

Share of total woody biomass potential

in kWh allocated to individual building.

Value of total woody biomass potential

obtained from Data provided by the Swiss

Federal Institute for Forest, Snow and

Landscape Research (WSL). Values are

originally provided by municipality.

Here, the share per building is

calculated based on share of building

surface area (GAREA) in relation to

the whole municipality. The value for

woody biomass with bark and 0% water

content is used.

42

s_wet_bm

float

Share of total wet biomass potential in

kWh allocated to individual building.

Data provided by the Swiss Federal

Institute for Forest, Snow and Landscape

Research (WSL) based on Burg et al.

  1. and Thees et al. (2017). Here,

the share per building is calculated

based on share of building surface area

(GAREA) in relation to the whole

municipality.

43

LocalHydroPotential_Laufkraftwerk

float

Share of local annual run-of-river hydro

power potential in kWh allocated to

individual building.

See Hydro Power

44

LocalHydroPotential_Speicherkraftwerk

float

Share of local annual storage hydro

power potential in kWh allocated to

individual building.

See Hydro Power

45

LocalHydroPotential_Pumpspeicherkraftwerk

float

Share of local annual pumped storage

hydro power potential in kWh allocated

to individual building.

See Hydro Power

46

avg_dh_connection_distance

float

Average distance to nearby buildings on

a near-optimal triangulation of the

building points on the plane.

47

dh_distance_cat

int

Distance category obtained by combining

avg_dh_connection_distance with the thermal demand of

the buildings.

48

heat_energy_demand_renov_estimate_kWh

float

Post-total renovation heat energy demand

estimation

Meta file

This file contains information about each district, with one row per district. Some of the data can be derived as an aggregate from the Master File.

The district identification number (column 1: GGDENR) must match the corresponding municipality code of the buildings listed in the Master File.

File name

meta_file_2

Format

.feather

Directory

./data/master_data/simulation_data/

Index

Numeric (integer), 0 to X, where X is

the number districts contained in the

file.

Number of rows

According to number of districts.

Number of columns

53

Number

Column

Data type

Description

Source for Swiss dataset

0

Municipality

string

Name of the district or municipality

according to GGDENAME in

Master file. For municipalities

in Switzerland, it is taken from the

Official directory fo building addresses

(Swisstopo, 2024).

Grouped value from Master file

1

GGDENR

int

According to GGDENR in

Master file.

Grouped value from Master file

2

Canton

string

Same as GDEKT in

Master file. Canton, in which the

district is located. For regions outside

of Switzerland, this is not relevant or

can be assigned according to similar

regional entities such as e.g.

provinces. For Switzerland, the short

form is used (e.g., ZH, FR, … ).

From Master file.

3

Coord_lat_median

float

Latitude coordinate of the district.

Given in decimal format (e.g.,

47.269056).

Calculated as median from Coord_lat

values given in Master file.

4

Coord_long_median

float

Longitude coordinate of the district.

Given in decimal format (e.g., 8.449859)

Calculated as median from Coord_long

values given in Master file.

5

altitude_median

float

Elevation above sea level of the

district.

Calculated as median from altitude

values given in Master file.

6

Filename

string

Name of the file that will be

automatically generated as a subset from

Master file. It must not contain

spaces. It is usually based on the

Municipality name. For example, if the

Municipality name is “Affoltern am Albis”,

Filename is “Affoltern_am_Albis”.

Based on values in Municipality

7

LocalHydroPotential

float

Local total annual hydro power potential

in kWh.

See Hydro Power

8

LocalHydroPotential_Laufkraftwerk

float

Local annual run-of-river hydro power

potential in kWh.

See Hydro Power

9

LocalHydroPotential_Speicherkraftwerk

float

Local annual storage hydro power

potential in kWh.

See Hydro Power

10

LocalHydroPotential_Pumpspeicherkraftwerk

float

Local annual pumped storage hydro power

potential in kWh.

See Hydro Power

11

v_h_eh

float

Required annual heat supply (i.e., heat

demand) in kWh from electric heaters

(eh) in base scenario (i.e., current

status) for the selected district. Can

be calculated from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_eh within the selected

municipality.

12

v_h_hp

float

Required annual heat supply (i.e., heat

demand) in kWh from heat pumps (hp) in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_hp within the selected

municipality.

13

v_h_dh

float

Required annual heat supply (i.e., heat

demand) in kWh from district heating

(dh) in base scenario (i.e., current

status) for the selected district. Can

be calculated from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_dh within the selected

municipality.

14

v_h_gb

float

Required annual heat supply (i.e., heat

demand) in kWh from gas boilers (gb) in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_gb within the selected

municipality.

15

v_h_ob

float

Required annual heat supply (i.e., heat

demand) in kWh from oil boilers (ob) in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_ob within the selected

municipality.

16

v_h_wb

float

Required annual heat supply (i.e., heat

demand) in kWh from wood boilers (wb) in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_wb within the selected

municipality.

17

v_h_solar

float

Required annual heat supply (i.e., heat

demand) in kWh from solar thermal in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_solar within the selected

municipality.

18

v_h_other

float

Required annual heat supply (i.e., heat

demand) in kWh from other technologies

(i.e., unknown) in base scenario (i.e.,

current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of heat_energy_demand_estimate_kWh_combined for all

buildings with Heating_System type

v_h_other within the selected

municipality.

19

Total_Heating

float

Total required annual heat supply (i.e.,

heat demand) in kWh as the sum from all

technologies in base scenario (i.e.,

current status) for the selected

district.

Calculated as the sum of the values from

individual technologies (columns 11-18)

20

v_hw_eh

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

electric heaters (eh) in base scenario

(i.e., current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_eh within the selected

municipality.

21

v_hw_hp

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

heat pumps (hp) in base scenario (i.e.,

current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_hp within the selected

municipality.

22

v_hw_dh

float

Required annual domestic hot watert

supply (i.e., heat demand) in kWh from

district heating (dh) in base scenario

(i.e., current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of `dhw_estimation_kWh_

combined`` for all buildings with ``Hot_Water_System@@EXPR

_1@@v_h_dh`` within the selected

municipality.

23

v_hw_gb

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

gas boilers (gb) in base scenario (i.e.,

current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_gb within the selected

municipality.

24

v_hw_ob

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

oil boilers (ob) in base scenario (i.e.,

current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_ob within the selected

municipality.

25

v_hw_wb

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

wood boilers (wb) in base scenario

(i.e., current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_wb within the selected

municipality.

26

v_hw_solar

float

Required annual domestic hot watert

supply (i.e., heat demand) in kWh from

solar thermal in base scenario (i.e.,

current status) for the selected

district. Can be calculated from values

contained in Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_solar within the selected

municipality.

27

v_hw_other

float

Required annual domestic hot water

supply (i.e., heat demand) in kWh from

other technologies (i.e., unknown) in

base scenario (i.e., current status) for

the selected district. Can be calculated

from values contained in

Master file.

Calculated from Master file:

Aggregated value of dhw_estimation_kWh_combined for all

buildings with Hot_Water_System type

v_h_other within the selected

municipality.

28

Total_Hot_Water

float

Total required annual domestic hot water

supply (i.e., heat demand) in kWh as the

sum from all technologies in base

scenario (i.e., current status) for the

selected district.

Calculated as the sum of the values from

individual technologies (columns 20-27)

29

PV_Pot

float

Annual rooftop solar photovoltaic

generation potential of the building (in

kWh).

PV_Pot values in Master file

aggregated across municipality.

30

TotalEnergy

float

Total annual generated energy in kWh

from solar PV installation.

TotalEnergy values in Master file

aggregated across municipality.

31

kWh_household_sfh

float

Total annual electricity demand in kWh

for single family houses (SFH) in the

district.

kWh_household_sfh values in Master file

aggregated across municipality.

32

kWh_household_mfh

float

Total annual electricity demand in kWh

for multi family houses (MFH) in the

district.

kWh_household_mfh values in Master file

aggregated across municipality.

33

Electricity_Industry

float

Annual electricity demand for industry

(if applicable) in kWh for the selected

district.

Electricity_Industry values in Master file

aggregated across municipality.

34

Electricity_Service

float

Annual electricity demand for services

(if applicable) in kWh for the selected

district.

Electricity_Service values in Master file

aggregated across municipality.

35

s_wd_bm

float

Total woody biomass potential in kWh for

the selected district.

Value of total woody biomass potential

obtained from Data provided by the Swiss

Federal Institute for Forest, Snow and

Landscape Research (WSL). Values are

originally provided by municipality. The

value for woody biomass with bark and 0%

water content is used.

36

s_wet_bm

float

Total wet biomass potential in kWh for

the selected district.

Data provided by the Swiss Federal

Institute for Forest, Snow and Landscape

Research (WSL) based on Burg et al.

  1. and Thees et al. (2017).

37

PV_Filename

int

Identification number of the hourly

solar photovoltaic profile applicable to

the district based on profiles provided

in Simulation profiles columns

33-43. E.g., “9” for PV_Profile_9.

Profile which was simulated closest to

the selected municipality is used. See

also Solar PV.

38

dh_cap_class_1

float

Thermal power need of the buildings in

district energy expansion class 1, pre

renovation

39

dh_cap_class_2

float

Thermal power need of the buildings in

district energy expansion class 2, pre

renovation

40

dh_cap_class_3

float

Thermal power need of the buildings in

district energy expansion class 3, pre

renovation

41

dh_cap_renov_class_1

float

Thermal power need of the buildings in

district energy expansion class 1, post

renovation

42

dh_cap_renov_class_2

float

Thermal power need of the buildings in

district energy expansion class 2, post

renovation

43

dh_cap_renov_class_3

float

Thermal power need of the buildings in

district energy expansion class 3, post

renovation

44

dh_avg_dist_class_1

float

Average distance to neighbouring egids

of buildings in district energy

expansion class 1

45

dh_avg_dist_class_2

float

Average distance to neighbouring egids

of buildings in district energy

expansion class 2

46

dh_avg_dist_class_3

float

Average distance to neighbouring egids

of buildings in district energy

expansion class 3

47

m_per_kWh_class_1_renov

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 1, post renovation

48

m_per_kWh_class_2_renov

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 2, post renovation

49

m_per_kWh_class_3_renov

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 3, post renovation

50

m_per_kWh_class_1

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 1, pre renovation

51

m_per_kWh_class_2

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 2, pre renovation

52

m_per_kWh_class_3

float

Meters of distance to neighbouring

buildings per kWh heat demand for

buildings in district energy expansion

class 3, pre renovation

Simulation profiles

This file contains hourly profiles for an entire year (i.e., 8760 hours) representing various generation and demand metrics at national and regional levels.

File name

simulation_profiles_file

Format

.feather

Directory

./data/master_data/simulation_data/

Index

Numeric (integer), 0 to 8759, hour of

the year

Number of rows

8760

Number of columns

51

Number

Column

Data type

Description

Source for Swiss dataset

0

Woody_Biomass_Profile

float

Normalised hourly profile of woody

biomass availability. This accounts for

the fact that not the entire resource is

available at once due to limitations

such as harvesting, transport, storage,

etc…

Constant hourly profile across the whole

year.

1

Wet_Biomass_Profile

float

Normalised hourly profile of wet biomass

availability. This accounts for the fact

that not the entire resource is

available at once due to limitations

such as harvesting, transport, storage,

etc…

Constant hourly profile across the whole

year.

2

Electricity_Profile_MFH

float

Normalised hourly electricity load

profile for multi family houses (MFH).

Rinaldi et al. (2022)

3

Electricity_Profile_SFH

float

Normalised hourly electricity load

profile for single family houses (SFH).

Rinaldi et al. (2022)

4

Electricity_Profile_Industry_AG

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Aargau (AG).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

5

Electricity_Profile_Industry_FR

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Freiburg

(FR).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

6

Electricity_Profile_Industry_GL

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Glarus (GL).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

7

Electricity_Profile_Industry_GR

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Graubünden

(GR).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

8

Electricity_Profile_Industry_LU

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Luzern (LU).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

9

Electricity_Profile_Industry_NE

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Neuenburg

(NE).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

10

Electricity_Profile_Industry_SO

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Solothurn

(SO).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

11

Electricity_Profile_Industry_SG

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of St. Gallen

(SG).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

12

Electricity_Profile_Industry_TI

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Tessin (TI).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

13

Electricity_Profile_Industry_TG

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Thurgau (TG).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

14

Electricity_Profile_Industry_VS

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Wallis (VS).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

15

Electricity_Profile_Industry_AI

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Appenzell

Innerrhoden (AI).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

16

Electricity_Profile_Industry_AR

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Appenzell

Ausserrhoden (AR).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

17

Electricity_Profile_Industry_BL

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of

Basel-Landschaft (BL).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

18

Electricity_Profile_Industry_BS

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Basel-Stadt

(BS).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

19

Electricity_Profile_Industry_BE

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Bern (BE).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

20

Electricity_Profile_Industry_JU

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Jura (JU).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

21

Electricity_Profile_Industry_SZ

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Schwyz (SZ).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

22

Electricity_Profile_Industry_ZG

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Zug (ZG).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

23

Electricity_Profile_Industry_OW

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Obwalden

(OW).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

24

Electricity_Profile_Industry_NW

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Nidwalden

(NW).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

25

Electricity_Profile_Industry_UR

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Uri (UR).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

26

Electricity_Profile_Industry_GE

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Genf (GE).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

27

Electricity_Profile_Industry_VD

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Waadt (VD).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

28

Electricity_Profile_Industry_SH

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Schaffhausen

(SH).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

29

Electricity_Profile_Industry_ZH

float

Only relevant for region Switzerland.

Normalised electricity load profile for

industry for the canton of Zürich (ZH).

Modelled based on grid data (Swissgrid

Ltd, 2025). See

Industry and Services.

30

Hydro_Lokal_Laufwasser_Profile

float

Normalised hourly standard profile of

local run-of-river hydro power

generation.

31

Hydro_Lokal_Speicher_Profile

float

Normalised hourly standard profile of

local storage hydro power generation.

32

Hydro_Lokal_Pumpspeicher_Profile

float

Normalised hourly standard profile of

local pumped storage hydro power

generation.

33

PV_Profile_0

float

Normalised hourly profile of solar PV

yield at location 0.

See Solar PV

34

PV_Profile_1

float

Normalised hourly profile of solar PV

yield at location 1.

See Solar PV

35

PV_Profile_2

float

Normalised hourly profile of solar PV

yield at location 2.

See Solar PV

36

PV_Profile_3

float

Normalised hourly profile of solar PV

yield at location 3.

See Solar PV

37

PV_Profile_4

float

Normalised hourly profile of solar PV

yield at location 4.

See Solar PV

38

PV_Profile_5

float

Normalised hourly profile of solar PV

yield at location 5.

See Solar PV

39

PV_Profile_6

float

Normalised hourly profile of solar PV

yield at location 6.

See Solar PV

40

PV_Profile_7

float

Normalised hourly profile of solar PV

yield at location 7.

See Solar PV

41

PV_Profile_8

float

Normalised hourly profile of solar PV

yield at location 8.

See Solar PV

42

PV_Profile_9

float

Normalised hourly profile of solar PV

yield at location 9.

See Solar PV

43

PV_Profile_10

float

Normalised hourly profile of solar PV

yield at location 10.

See Solar PV

44

Hydro_National_Profile

float

Normalised hourly profile of hydro power

generation from national electricity

mix, for large hydro power plants not

considered local.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

45

Nuclear_National_Profile

float

Normalised hourly profile of nuclear

power generation from national

electricity mix. Nuclear power plants

are never considered local in DEM.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

46

Solar_National_Profile

float

Normalised hourly profile of solar PV

power generation from national

electricity mix for large solar PV

plants not considered local.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

47

Wind_National_Profile

float

Normalised hourly profile of wind power

generation from national electricity mix

for large wind power plants not

considered local.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

48

Biomass_National_Profile

float

Normalised hourly profile of power

generation from biomass from national

electricity mix for large power plants

not considered local.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

49

Other_National_Profile

float

Normalised hourly profile of power

generation from other technologies in

the national electricity mix for

technologies not considered local.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

50

Import_National_Profile

float

Normalised hourly profile of energy

imported from other countries.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

Temperatures

These files contains hourly temperature data for an entire year (i.e., 8760 hours) across multiple years (i.e., one column per year). One file must be provided per district, where the temperature values represent spatial averages over the district area.

Past years include historical measurements from monitoring stations, while future years contain projected values based on climate scenarios (see also Climate Adjustment).

File name

[com_nr], e.g. “2762” for municipality

of Allschwil

Format

.feather

Directory

./data/weather_data/

Index

datetime format; hourly entries; e.g.,

2016-01-01 00:00:00 to 2016-12-31

23:00:00

Number of rows

8760

Number of columns

according to number of captured years

Number

Column

Data type

Description

Source for Swiss dataset

0

2016

float

Hourly ambient air temperature data for

the district location for the year 2016.

Temperatures based on the combined

Meteostat (Lamprecht, 2025) and

MeteoSwiss station temperature

measurement series for 2016.

1

2023

float

Hourly ambient air temperature data for

the district location for the year 2023.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2023 (CH2018 Project Team,

2018).

2

2024

float

Hourly ambient air temperature data for

the district location for the year 2024.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2024 (CH2018 Project Team,

2018).

3

2025

float

Hourly ambient air temperature data for

the district location for the year 2025.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2025 (CH2018 Project Team,

2018).

4

2030

float

Hourly ambient air temperature data for

the district location for the year 2030.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2030 (CH2018 Project Team,

2018).

5

2040

float

Hourly ambient air temperature data for

the district location for the year 2040.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2040 (CH2018 Project Team,

2018).

6

2050

float

Hourly ambient air temperature data for

the district location for the year 2050.

Temperatures for 2016, adjusted using

the CH2018 climate scenarios to the

climate of 2050 (CH2018 Project Team,

2018).

DHW profile

This file contains an hourly domestic hot water (DHW) demand profile for an entire year (i.e., 8760 hours). The profile is normalised to 1 and can be scaled according to the annual DHW demand of the district or building.

File name

DHW_Profile

Format

.feather

Directory

./data/heat_demand/

Index

Numeric (integer), 0 to 8759, hour of

the year

Number of rows

8760

Number of columns

1

Number

Column

Data type

Description

Source for Swiss dataset

0

DHW_Profile

float

Normalised hourly load profile for

domestic hot water (DHW) demand.

Generated based on standard SIA

385/2:2025 (Schweizerischer Ingenieur-

und Architektenverein, 2025).

Wind power capacity

This file contains the currently installed wind power capacity (in kW) for each municipality.

File name

p_installed_kW_wind_power

Format

.feather

Directory

./data/tech_wind_power/

Index

Numeric (integer), 0 to X, where X is

the number districts contained in the

file.

Number of rows

According to number of districts.

Number of columns

2

Number

Column

Data type

Description

Source for Swiss dataset

0

Municipality

string

Name of district according to GGDENAME

in Master file and Municipality in

meta_file.

Swisstopo, 2024

1

p_kW

float

Currently installed wind power capacity

in kW in the district. This data is used

for computation of the base scenario

(i.e., current status).

Swiss Federal Office of Energy SFOE,

2022a

Wind power profiles

These files contain hourly wind power generation profiles aggregated at the municipal level. For each municipality, two files are provided: one representing profiles optimised for maximum annual generation (named according to muncipality name), and another optimised for maximum winter generation (named according to muncipality name with extension _winter). This is based on the location of the wind turbines within the municipality. The two profile types (annual- and winter-optimised) are disjoint subsets of the total capacity, meaning that turbines counted in ‘winter’ are not counted in ‘annual’ and they add up to the total generation potential.

For Switzerland, the Wind-Topo dataset is used (Dujardin and Lehning, 2022a, 2022b). Each file contains five time series, grouped into bins according to the share of district-level wind turbine capacity installed (e.g. 0–20%, 20–40%, etc.). The binning reflects an ordering of site quality: locations with the highest expected yields are assumed to be developed first, while additional capacity is deployed at progressively less favourable sites. As a result, total electricity generation increases with installed capacity, but the average capacity factor declines. This effect is represented by separate capacity-factor time series for each installation bin.

File name

[district name] / [district name]_winter

Format

.feather

Directory

./data/tech_wind_power/profiles/

Index

Numeric (integer), 0 to 8760, index 0:

wind power capacity in kW; indices

1-8760: hour of the year

Number of rows

8760

Number of columns

5

Number

Column

Data type

Description

Source for Swiss dataset

0

20%

float

Row 0: wind turbine capacity. Rows

1-8760: Hourly capacity factors for

total wind power capacity between 0% and

20% of total potential capacity.

Dujardin and Lehning, 2022a, 2022b

1

40%

float

Row 0: wind turbine capacity. Rows

1-8760: Hourly capacity factors for

total wind power capacity between 20%

and 40% of total potential capacity.

Dujardin and Lehning, 2022a, 2022b

2

60%

float

Row 0: wind turbine capacity. Rows

1-8760: Hourly capacity factors for

total wind power capacity between 40%

and 60% of total potential capacity.

Dujardin and Lehning, 2022a, 2022b

3

80%

float

Row 0: wind turbine capacity. Rows

1-8760: Hourly capacity factors for

total wind power capacity between 60%

and 80% of total potential capacity.

Dujardin and Lehning, 2022a, 2022b

4

100%

float

Row 0: wind turbine capacity. Rows

1-8760: Hourly capacity factors for

total wind power capacity between 80%

and 100% of total potential capacity.

Dujardin and Lehning, 2022a, 2022b

National electricity mix

This file contains hourly profiles of the national electricity mix. The data include the hourly contribution of each generation technology and are used to create normalised profiles of national electricity generation technologies, as well as to calculate the shares of each large generator type (e.g., large hydro) on national scale.

File name

electricity_mix

Format

.feather

Directory

./data/electricity_mix_national/

Index

Numeric (integer), 0 to 8759, hour of

the year

Number of rows

8760

Number of columns

10

Number

Column

Data type

Description

Source for Swiss dataset

0

Hydro Pumpspeicher

float

Hourly supply profile in GWh for pumped

storage hydro power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

1

Hydro Laufwasser

float

Hourly supply profile in GWh for

run-of-river hydro power on national

scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

2

Hydro Speicher

float

Hourly supply profile in GWh for storage

hydro power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

3

Nuclear

float

Hourly supply profile in GWh for nuclear

power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

4

Solar

float

Hourly supply profile in GWh for solar

PV power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

5

Wind

float

Hourly supply profile in GWh for wind

power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

6

Biomass

float

Hourly supply profile in GWh for biomass

power on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

7

Other

float

Hourly supply profile in GWh for other

sources on national scale.

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

8

Load

float

Hourly load profile in GWh on national

scale (i.e. national electricity

demand).

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

9

Import

float

Hourly supply profile in GWh for power

imported from other countries (i.e.,

cross-border import).

Modelled based on data from Swiss

electricity statistics (Swiss Federal

Office of Energy, 2022b)

HDD Profiles

These files contain the number of heating degree days (HDD) per year for each municipality, calculated for base temperatures of 12 °C and 15 °C. Each file corresponds to one simulation year, and each row represents a single municipality.

File name

HDD_Municipality_[year]

Format

.feather

Directory

./data/master_data/HDD_and_HDH_profiles/

Index

Numeric (integer), 0 to X, where X is

the number districts contained in the

file.

Number of rows

According to number of districts.

Number of columns

4

Number

Column

Data type

Description

Source for Swiss dataset

0

Municipality

string

Name of district according to GGDENAME

in Master file and Municipality in

meta_file.

Swisstopo, 2024

1

HDD_12_2023

float

Heating degree days for the district

based on a reference temperature (start

temperature for heating) of 12°C.

Computed based on temperature data of

2023 using the methods of Schneeberger

et al. (2025)

2

HDD_15_2023

float

Heating degree days for the district

based on a reference temperature (start

temperature for heating) of 15°C.

Computed based on temperature data of

2023 using the methods of Schneeberger

et al. (2025)

3

GGDENR

int

According to GGDENR in

Master file and meta_file.

Federal Statistical Office, 2025

EV demand profiles

For Switzerland, the dataset by Herrera and Hug (2025a; 2025b) is used to model hourly EV charging demand and daily flexibility. The dataset provides hourly time series of municipal charging load (CP), corresponding upper (PU) and lower (PD) bounds on charging power, and a time series of daily flexible energy (FE). See also :ref:electricity_demand_ev.

File name

profile_CP_y4 / profile_PD_y4 /

profile_PU_y4

Format

.feather

Directory

./data/electricity_demand/ev_profiles/

Index

Numeric (integer), 0 to 8759, hour of

the year

Number of rows

8760

Number of columns

According to number of districts.

File name

profile_FE_y4

Format

.feather

Directory

./data/electricity_demand/ev_profiles/

Index

Numeric (integer), 0 to 364, day of the

year

Number of rows

365

Number of columns

According to number of districts.

Number

Column

Data type

Description

Source for Swiss dataset

0

name of district 0

float

CP file: hourly charging load in kW.

PD file: hourly lower power bound in kW.

PU file: hourly upper power bound in kW.

FE file: daily flexible energy in kWh.

Herrera and Hug, 2025a, 2025b

1

name of district 1

float

see above

see above

2

name of district 2

float

see above

see above

3

name of district 3

float

see above

see above

…

…

float

see above

see above

N

name of district N

float

see above

see above

References

Apache Software Foundation. (2025). Feather file format (Apache Arrow). https://arrow.apache.org/docs/python/feather.html

Burg, V., Bowman, G., Erni, M., Lemm, R., & Thees, O. (2018). Analyzing the potential of domestic biomass resources for the energy transition in Switzerland. Biomass and bioenergy, 111, 60-69. DOI: 10.1016/j.biombioe.2018.02.007

CH2018 Project Team (2018). CH2018 - Climate Scenarios for Switzerland. National Centre for Climate Services. doi: 10.18751/Climate/Scenarios/CH2018/1.0

Dujardin, J., Lehning, M. (2022a). Wind-Topo_model. EnviDat. DOI: 10.16904/envidat.301

Dujardin, J., & Lehning, M. (2022b). Wind‐Topo: Downscaling near‐surface wind fields to high‐resolution topography in highly complex terrain with deep learning. Quarterly Journal of the Royal Meteorological Society, 148(744), 1368-1388. DOI: 10.1002/qj.4265

Federal Statistical Office (FSO). (2025). Federal register of buildings and dwellings (RBD). https://www.bfs.admin.ch/bfs/en/home/registers/federal-register-buildings-dwellings.html

Federal Office of Topography Swisstopo. (2024). Official directory of building addresses. https://www.swisstopo.admin.ch/en/official-directory-of-building-addresses

Lamprecht, C. S. (2025). Meteostat Python [Software]. https://meteostat.net/en/

Parajeles Herrera, M., & Hug, G. (2025a). Charging Demand and Flexibility Bounds for Large-Scale BEV Fleets - The Case Study of Switzerland [Data set]. Zenodo. DOI: 10.5281/zenodo.16597426

Parajeles Herrera, M & Hug, G. (2025b). Modeling Charging Demand and Quantifying Flexibility Bounds for Large-Scale BEV Fleets. 2025 IEEE Kiel PowerTech, Kiel, Germany, 2025, pp. 1-6. DOI: 10.1109/PowerTech59965.2025.11180551

Rinaldi, A., Ramirez, H., Schroeteler, B., & Meier, M. (2022). The role of energy storage technologies in the context of the Swiss energy transition (SwissStore) [Data set]. Zenodo. DOI: 10.5281/zenodo.6782179

Schneeberger, S., Meister, C., & Schuetz, P. (2025). Estimating the heating energy demand of residential buildings in Switzerland using only public data. Energy and Buildings, 116371. DOI: 10.1016/j.enbuild.2025.116371

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