List of variables and explanations

The original can be found on the Zenodo repository at the following address:

https://dx.doi.org/10.5281/zenodo.4139299

Input Files

File name: "Sim_Param_Distribution.mat"

"areaP" (37x3)

Definition: Annual floor area per person from 2013 to 2049 (m2/pers.y-1). The first column is the average, and the two second column is the deviation in both directions.

"population" (37x3)

Definition: Annual population from 2013 to 2049. The first column is the average, and the two second column is the deviation in both directions.

"RENO_matrix" (5x1)

Definition: "RENO_matrix" contains information on the evolution of renovation rate. Rates for 2013, 2030 and 2050 are defined

• RENO_matrix(1) = 1 if renovation rate changes, 0 if not
• RENO_matrix(2) = renovation rate for 2030
• RENO_matrix(3) = renovation rate for 2049

"time20(30/50)" (2x744)

Definition: array used for definition the hours and the weekdays for a specific month.

• Row 1 Hour of the day (0:23)
• Row 2 Binary value for weekend/holiday (=1) or weekday (=0)

"PARAMETER_matrix" (18x1)

PARAMETER_matrix contains variables affecting the renovation, demolition and construction of buildings

1. PARAMETER_matrix(1) = number of years calculated
2. PARAMETER_matrix(2) = 1 if renovation is enabled, 0 if renovation is not enabled
3. PARAMETER_matrix(3) = mean value of normal distribution for modelling RB renovation (years)
4. PARAMETER_matrix(4) = annual renovation rate for NRB (%)
5. PARAMETER_matrix(5) = grace period for renovation and demolition (years)
6. PARAMETER_matrix(6) = energy efficiency improvement after renovation (%)
7. PARAMETER_matrix(7-9) = parameters of the Weibull distribution for modelling RB demolition
8. PARAMETER_matrix(10) = annual demolition rate for NRB (%)
9. PARAMETER_matrix(11) = parameter for correlation between RB volume and floor area
10. PARAMETER_matrix(12-14)= share of the volume of detached, row and apartment buildings among new RB (%)
11. PARAMETER_matrix(15) = allowed error for calculation of the volume of new buildings (%)
12. PARAMETER_matrix(16) = energy efficiency improvement for new buildings built before 2020
13. PARAMETER_matrix(17) = energy efficiency improvement for new buildings built after 2020
14. PARAMETER_matrix(18) = annual volume of new NRB compared with new RB (%)

Output Files

Building Stock Model

Data related to the building stock model, available in the file "Sim_Param_Distribution.mat"

"SIM_vol" (37x22x100)

Definition: Contains annual information on the volume of building stock, duplicated 100 times for sensitivity analysis of the simulation (randomness of the sample of building stock variation).

1. Column 1 is the year
2. Column 2 is the annual volume of the building stock
3. Column 3 is the annual volume of RB
4. Columns 4-6 are the annual volume of detached, row and apartment buildings
5. Column 7 is the annual volume of NRB
6. Column 8 is the annual volume of renovated RB
7. Columns 9-11 are the annual volume of renovated detached, row and apartment buildings
8. Column 12 is the annual volume of renovated NRB
9. Column 13 is the annual volume of demolished RB
10. Columns 14-16 are the annual volume of demolished detached, row and apartment buildings
11. Column 17 is the annual volume of demolished NRB
12. Column 18 is the annual volume of new RB
13. Columns 19-21 are the annual volume of new detached, row and apartment buildings
14. Column 22 is the annual volume of new NRB

"SIM_rates" (38x6x100)

Defintion: Contains annual and mean renovation, demolition and new building rates for RB and NRB

1. Columns 1-3 contain renovation, demolition and new building rates for RB
2. Columns 4-6 contain renovation, demolition and new building rates for NRB

"SIM_NRBs" (37x5x100)

Defintion: Contains annual information on the number of NRB and the number of demolished, renovated and new NRB

1. First column is the year
2. Second column is the number of NRB at the start of the year
3. Columns 3-5 are the annual number of renovated, demolished and new NRB

"SIM_RBs" (37x17x100)

Defintion: Contains annual information on the number of RB and the number of demolished, renovated and new RB

1. First column is the year
2. Second column is the number of RB at the start of the year
3. Columns 3-5 are the number of detached, row and apartment buildings at the start of the year
4. Columns 6-8 are the annual number of renovated, demolished and new RB
5. Columns 9-11 are the annual number of renovated, demolished and new detached houses
6. Columns 12-14 are the annual number of renovated, demolished and new row houses
7. Columns 15-17 are the annual number of renovated, demolished and new apartment buildings

Power, Energy, and Temperature outputs

The following section apply for each of the following files:

• Simulation_0_year.mat
• Simulation_1_year.mat
• Simulation_2_year.mat
• Simulation_3_year.mat

The characteristics of each simulation is as follow:

• Simulation 0:
  • Target for 2030 = 1%;
  • Target for 2050 = 1%
• Simulation 1:
  • Target for 2030 = 1%
  • Target for 2050 = 3%
• Simulation 2:
  • Target for 2030 = 1.5%
  • Target for 2050 = 3%
• Simulation 3:
  • Target for 2030 = 2%
  • Target for 2050 = 3%

1. Power/energy data

Each output file follow the same structure. For each year, is is possible to retrieve 3 types of variable from the power output: the hourly power demand, the total power for the entire simulation, and the maximum peak power for the entire simulation. The following is how the variable are constructed:

Power designation:

1. 'P': Hourly heat demand for the entire simulation[MW/h]
   • (6x5088x100): first dimension is the building type, second dimension is the hour of the simulation, third dimension is each randomness simulation
2. 'Pmax': Maximum heat demand of the entire simulation period [MW]
   • (6x100): first dimension is the hour of the simulation, second dimension is each randomness simulation
3. 'Ptot': Total heat demand for the entire simulation period [GWh]
   • (6x100): first dimension is the hour of the simulation, second dimension is each randomness simulation

Each of the variable have 6 rows, that represents a different building segment in the building stock:

1. Row 1 is for all the buildings.
2. Row 2 is for RBs.
3. Row 3 is for detached houses.
4. Row 4 is for row houses.
5. Row 5 is for apartment buildings.
6. Row 6 is for NRBs.

The year 2013 can be read as the following:

• "Power"2013_"Scenario name"_year
  • e.g. P2013_Cold2010_year, Pmax2013_TMY2004_2018_year

Note: "Scenario name" is the fullname of the scenario as described in the associated paper.

For the years 2030 and 2050, 2 more variables characterised the dataset: 1. the database used (RCM or GCM), and the RCP scenario used.

Climate dataset available "database":

1. GCM (Global Climate Models): Paituli
2. RCM (Regional Climate Models): ECEM

RCP (Representative Concentrated Pathways) used in the model "RCP scenario":

1. RCP2.6 --> RCP26
2. RCP4.5 --> RCP45
3. RCP8.5 --> RCP85

the following routine is used:

• SIM_"Power""year"_"Scenario name"_"Database"_"RCP scenario"
  • e.g. SIM_Pmax2030_Cold2010_ECEM_RCP85
  • SIM_P2050_Cold2010_Paituli_RCP45

2. Temperature data

The outdoor temperature variation used in the simulation are also available and can be retrieved using one of the following:

• outtemp_"Scenario name"_year
  • e.g. outtemp_TMY2004_2018_year