Metodologías ágiles

Domestic and non-domestic buildings comprise different types of building and also various building types. As widely explained above, the main factors influencing the building energy demand are, besides outdoor conditions, building structure, building dimensions, building orientation, thermostat temperatures, and the number of people. This chapter studies how the overall energy demand from an aggregated group of buildings, to be used for system-wide analyses, can be modelled. In particular, an aggregation algorithm that takes into account building diversity relevant to all the different thermal load determinants are derived from the relation between each factor and the energy demand. The algorithm is based upon a bottom up modelling approach, through which a large number of load profiles can be aggregated based on statistical data available.

3.1 Domestic heating and hot water load profile

According to the classification adopted in this document, domestic buildings include detached houses, semi-detached houses, terrace houses, and flats. Here, a methodology for load aggregation for residential buildings is presented. In addition, also the energy used for domestic hot water (DHW) production is taken into account and suitably modelled.

3.1.1 Load profile of domestic heating systems

In order to simulate thermal load diversity in the models developed for residential buildings (detached, semi-detached, terrace, and flat households), the building structure, building volume, building dimension ratio, building orientation, temperature set point, and number of people are randomised based on available statistical data.

According to the indications from the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), the comfort temperature for a typical work place is 21.1^oC. We can assume that the same temperature also applies in the UK. The typical heating temperature set point for a bedroom as given in DesignBuilder is 18^oC. The typical temperature set point for a UK dwelling case study given in [12] is 19^oC. Therefore the thermostat settings are assumed here to be between 18 and 22^oC. The heating setbacks are set 6^oC lower than the temperature set point (heating set point), which is a typical trade-off between comfort level and energy efficiency. The heating setpoint and heating setback share assumed for buildings is shown in table 3-1. The heating set point time is mainly set based on the DesignBuilder template (6.00-23.00). Then, diversity for heating set point time is assumed as in table 3-2.

102 Table 3-1: Heating set point and heating setback of houses

Heating set point Heating setback Percentage Assumption (%)

20^oC 14^oC 10

19^oC - 15

18^oC - 50

17^oC - 15

16^oC - 10

Table 3-2: Heating set point time

Heating set point period Percentage Assumption (%)

4.00-21.00 5

4.30-21.30 10

5.00-22.00 10

5.30-22.30 15

6.00-23.00 20

6.30-23.30 15

7.00-24.00 10

7.30-00.30 10

8.00-01.00 5

The floor area of the houses is assumed to be between 50% and 150% of the typical model. The ratio of the length to the width is 1 if the house floor is square. It is assumed that the ratio varies between 0.5 and 1. The number of people for the average 85m² floor area house is assumed to be between 0.01 and 0.03 people/m² which is approximately 1-3 people for the average UK household. However, more people may live in shared flats in London. Different numbers of terrace houses, blocks of flat and different number of storeys in blocks of flats are assumed. The assumed scaling factors of the buildings are shown in table 3-3.

103 Table 3-3: Scaling factors of buildings

Factors Minimum Maximum

Building floor area 50% 150%

Ratio of the length to the width 0.5 1

Occupancy 0.01 people/m² 0.06 people/m²

Number of terrace blocks 4 10

Number of flat blocks 4 12

Number of flat storeys 4 12

Well-designed buildings normally have the door and windows facing south. It is assumed that the house orientation is as shown in table 3-4.

Table 3-4: Orientation of buildings

Orientation to the north (degrees) Percentage Assumption (%)

0-30 25

151-210 50

331-360 25

It is assumed that their construction is of the following types: solid wall, cavity wall, or cavity wall with partL2006 insulation standard. The construction diversity considered for the building stocks is shown in table 3-5.

104 Table 3-5: Construction type of buildings

Model Age Insulation

Roof

The percentages of working people in buildings are from the UK statistical data and can be adjusted based on statistical data for the UK. The patterns of occupancy are the inputs of EnergyPlus to simulate energy demand profiles of randomised building types.

The composition of households in the UK 2002 [12] is given in table 3-6. Occupancy patterns for households are shown in table 3-7. Occupancy patterns for households with one or more residents are shown in table 3-8.

Table 3-6: Occupancy pattern of people

Scenario Type Unoccupied period Percentage

1 Part-time working morning session 1/2 9:00–13:00 3.97 %

2 Full-time working 9:00–18:00 34.94 %

3 Part-time working 2/3 9:00–16:00 3.97 %

4 Not working N/A 53.15 %

5 Part-time working afternoon session 1/2 13:00–18:00 3.97 %

105 Table 3-7: Composition of households in the UK 2002

Number of persons in the household 1 2 3 4 5 6 or

more Proportion of households with the

specified number of people 31% 35% 16% 13% 4% 1%

Table 3-8: Household occupancy patterns

Unoccupied time patterns [hours]

1 resident 2 residents or more

1. 9:00–13:00 1. 9:00–13:00

2. 9:00–18:00 2. 9:00–18:00

3. 9:00–16:00 3. 9:00–16:00

4. Always occupied 4. Always occupied

5. 13:00–18:00 5. 13:00–18:00

6. 13:00–16:00 (for pattern 2. occupied with 5.)

The unoccupied periods in table 3-8 represents the time of the day when the house is empty. For instance, for two residents or more, point 2 in the table Indicates that the house is empty from 9.00 to 18.00.

Heating profiles for detached-house, semi-detached house, terrace and flat with different occupancy patterns in table 3-8 are simulated using London weather data 2002. The EnergyPlus simulations are run on 15 April, 19 August, 15 October and 2 December for spring, summer, autumn and winter respectively. For illustrative purpose, the heating demand in winter of new, modern and old detached-houses in the study with different occupancy patterns given in table 3-8 are shown in figures 3-1.

106 Figure 3-1a: Winter heating demand profiles of a new detached-house with different occupancy

patterns

Figure 3-1a shows that the peak demand of the new detached-house in the morning is approximately 8.5 kWth. The peak demand in the evening is approximately 7.5 kWth for the unoccupied period 9.00-18.00.

Figure 3-1b: Winter heating demand profiles of a modern detached-house with different occupancy patterns

00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00

Demand (kW)

00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00

Demand (kW)