Auditorías de los Sistemas de Seguridad y Salud

3.3.1 Occupancy Patterns

The behaviour of the occupants (both in terms of their interaction with appliances, lighting and DHW outlets, and the temporal configuration of space heating controls) is a major driver of thermal and electrical demand. Profiles were created which described the occupancy status of each occupant: absent from dwelling; “active” in dwelling; asleep in dwelling. In Sections 3.4 to 3.7, the relevance of each occupancy status to the associated event scripting is discussed at length, including the reliance of certain appliance usage events on active occupancy. By superimposition of all four profiles, a dwelling occupancy profile was created that identified periods of “active occupancy”, “inactive occupancy” and “absence”. These periods were used to dimension the space heating thermal demand periods, as defined in Section 3.9, and are used to constrain micro-generation systems functioning within certain operating

The definition of a household to occupy the building variant was undertaken with three goals in mind; firstly, to represent, in terms of numbers, and preferably composition, a significant portion of UK households; secondly, to suit the building variant and greater-than-average demands wanted from the building variant; and finally, to produce plausible demand profiles. Analysis of the UK General Household Survey 2002/03 [14], as presented in Appendix A, suggested that four-person households account for around 13%1 of UK households, whilst larger households account for less than 6%2 cumulatively. Hence, a household with four members, as defined in Table 3.3, was chosen as a compromise between a large household with associated demand, and the remit to maximise representation of household stock. The decision to specify the household composition of three working adults and one school- attending child was made in light of research undertaken on the UK Time Use Survey 2000 [15] that suggested a range of occupancy, and vacancy, durations from both schoolchildren and adults. The particular household represents almost 18% of four- person households, and could be expected to represent a family with a grown-up offspring who has remained within the family home.

Occupant Description

1 Working Adult Male 2 Working Adult Female

3 Working Adult Male (Offspring) 4 School-attending Child

Table 3.3: Definition of Occupants as used in BIM-G model

Occupancy profiles were created after analysis of the UK Time Use Survey 2000 [15], in conjunction with the UK General Household Survey [14], from which distributions (see Figure 3.8) of occupant vacancy due to employment (or full-time education) were derived. Further analysis of this data showed that the peak of the distribution was much greater during weekdays, than weekend days. Two occupancy patterns were then defined for each, one that represents weekdays, and another for weekend days, where the vacancy durations have been selected from the upper and lower end,

1 _{Appendix A, Table B.3} 2

respectively, of the distribution in Figure 3.8. The assumption of two discrete occupancy patterns and approximate duration of weekday vacancy is supported [16] by similar assumptions within the established BRE Domestic Energy Model (BREDEM).

Figure 3.8: Distribution of Occupant Vacancy Periods, generated from analysis of the UK Time Use Survey 2000 [15]

The duration of sleeping periods were selected using the distribution in Figure 3.9, where longer periods were selected for the child than the adults. As before, the period of dwelling nocturnal inactivity was selected with the assumptions of the BREDEM model [16] in mind. The particulars of each occupant’s occupancy pattern are given in Table 3.4.

Activity Occupant Weekday

Start Time Weekday Stop Time Weekend Start Time Weekend Stop Time Sleeping 1 23:00 07:00 23:00 07:00 2 23:00 07:00 23:00 07:30 3 23:00 07:00 23:00 08:00 4 22:00 07:30 22:30 08:00 Vacant 1 08:15 17:45 10:00 11:30 2 08:30 16:30 13:30 15:30 3 07:30 17:15 18:30 21:30 4 08:30 16:30 13:30 15:30

Figure 3.9: Distribution of Occupant Sleeping Periods, generated from analysis of the UK Time Use Survey 2000 [15]

The occupancy patterns defined in this section are consistent with the analysis undertaken by Agar & Newborough [17] upon a demand dataset, recorded by an energy utility in 1996, with annual thermal and electrical demand data for approximately 30 UK dwellings. This data had a temporal resolution of 1-minute, where the thermal demand recorded was boiler gas consumption, for space heating and DHW. They concluded that daily thermal and electrical demand profiles were functions of occupancy characteristics, and identified 2 basic types of profile, occurring in any home in any season; Type A on a weekday and Type B on a weekend. Despite the association with weekday and weekend, they conclude that relative proportions of Type A and B profiles are a function of the household’s lifestyle. Type A was characterised as unoccupied for several hours per day. Type B was characterised as one or more members in residence for 24 hours.

In their µCHP modelling exercise, Hawkes et al [18] used similar operating patterns, both in terms of vacancy and sleep durations, and in the split between weekday and weekend operating patterns.

3.3.2 Metabolic Gains

Design guide-derived assumptions [19] on task-dependant metabolic heat emission were correlated with ASHRAE [20] design estimates on gender and age specific emissions to produce specific values of metabolic gains for each occupant whilst undertaking a defined type of activity. A range of occupant activities are defined within the UK Time Use Survey [15], including “Watching TV”, “Cooking”, “Laundry”, “Washing and Dressing”, “Ironing” and “House Cleaning”. Whilst these discrete activities were considered when composing a narrative for the occupants, a simplified approach was applied to the consideration of metabolic gains. The increased metabolic rate of “Active” was used whenever an occupant uses, or interacts with, a domestic cleaning appliance (i.e. washing machine, dishwasher or vacuum cleaner), or cooks a meal involving the hob or oven. All other activities are classed as sedentary.

Since the BIM-G model does not simulate humidity levels and moisture transfer, for reasons discussed in Section 2.3.1, and a disparity of up to 64% exists between total and sensible metabolic gains, it was deemed necessary to segregate the sensible and latent fractions of the metabolic gain. To this end, activity specific sensible-latent metabolic gain ratios were derived from ASHRAE design guide data [20], and applied to the calculated metabolic gains.

The metabolic gains to the dwelling, as calculated using the above methodology, are detailed in Table 3.5. The metabolic gain corresponding to the “Active” state was calculated as the average of the range of metabolic gains for housework.

Activity Adult Male Adult Female Child

Sleeping 55.4 47.0 41.5

Sedentary 71.4 60.7 53.6

Active (Housework, Cooking) 96.2 81.8 72.2

Vacant 0.0 0.0 0.0

Table 3.5: Sensible Metabolic Gains (W) by Gender, Age and Activity

Using the occupancy patterns discussed in the previous sub-section, and the values for metabolic gains, a metabolic casual thermal gains profile was produced, as visualised in

Figure 3.10. It is prudent to note that “active occupancy”, as described in the previous sub-section, is distinct from the “active” activity type, as “active occupancy” is a dwelling circumstance where at least one occupant is in the “active” or “sedentary” state. The time periods with active occupancy are tabulated for weekday and weekend occupancy patterns in Appendix B.2.1 and Appendix B.2.2.

Figure 3.10: Metabolic Gain Profiles, for entire household, produced for Weekday & Weekend Occupancy Patterns