a closer look at energy demands: quantification and characterisation

A Closer Look at Energy Demands: Quantification and Characterisation

Why is demand data important?

• having information on likely energy demands is a key requirement of a low energy building deisgn

• we can assess if design criteria have been met

• allows us to target demand reduction measures

• … or we can size low carbon energy supply equipment

Aggregate Energy Demand

• the simplest way to describe the energy consumption of a building is to provide an aggregate value

• is consumption over a time period (a year)

• lumps all energy demands together (heat/electrical)

• often expressed in kWh/m2 … or as a non-dimensional rating (e.g. SAP)

• …useful as a performance metric – not that useful for design

Disaggregating by Load Type

• dissaggregation gives us more detail• e.g. looking at what the energy was used for• useful for targeting demand reduction measures • … or to select energy supply technologies

Disaggregating by Load Type

Temporal Characteristics

• load data can be disaggregated in different ways: - by type- spatially (by location)- temporally (by time)

Heating system Price of fuel Energy use Cost CO2 emission p/kWh p/day kWh £ kg ASHP 12.11 16.47 2,261 334 1,230 Direct electric 12.11 16.47 5,487 725 2,985 Gas condensing boiler

3.41 14.47 7,515 309 1,383

0

50

100

150

200

250

300

350

400

450

kWh

Monthly Electrical Consumption

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Temporal Characteristics

Calculating Energy Demands• we’ll look at how we can quantify

and characterise each of the major energy loads in turn

Calculating Heating/Cooling Demands• we are spoiled for choice when it

comes to determining space heating or cooling demands

• simplified methods: - Standard Assessment Procedure SAP *- degree-day method** (daily or monthly

heating/cooling demands)- basic UA calculation

• more comprehensive methods:- building simulation (hourly minutely heating or

cooling energy demand)

* produces a rating not a value, **does not adequately account for internal and solar gains

Climate Data• the starting point for a heat

load calculation is climate data

• this could be as simple as an average annual external air temperature

• or as detailed as hourly readings of temperature, solar radiation, wind speed and wind direction

Calculating Heating/Cooling Demands

• SAP is used more for compliance checking (with building regulations) than as a design tool

• gives an energy rating score (1-100) using a ‘tick-list’ based on the building design

• degree day/U-value methods are energy balance based

• DD assumes that is ext. air temp > 15.5oC there will be no heating load

• the assumption is that when the ext air temp reaches this point internal heat gains in the building will keep the temperature ~ 18.5oC

• does not adequately account for equipment gains … or solar gains (increasingly important in well-insulated dwellings)

• doesn’t account for thermal dynamics caused by building fabric


• for each day (or longer period) calculate the accumulated degree days

• calculate the associated energy demand

• (kWh)


2

5.15 minmax TTDD

31000

1

24

NVUAK

DDKQ

• a basic UA calculation can be uses to produce annual daily or hourly demand data

• the calculation could be performed once for T equal to an annual average to give an annual energy consumption

• … or 8760 times with hourly external temperature readings and temperature set points to give hourly space heating demands


TTT

TNV

UAQ

i

2431000

1

• … again, does not adequately account for equipment gains or solar gains

• doesn’t account for thermal dynamics caused by building fabric


Qf - fabric

Qi - infiltration

Qs - solar

Q g -

gain

s

Qh - heat

• the most robust approach is to use a simulation tool to calculate heat load

- building is typically decomposed into hundreds of volumes

- an energy balance is set up for each ‘volume’ which includes fabric energy storage

- internal heat gains, solar gains calculated using climate, geometric and schedule information

- solution of all of the individual energy balance equations gives the heat flows and temperatures throughout a building typically at hourly or sub hourly time intervals

- computer and software required and usually does more than calculate heat demand data


• typical output is as follows:


Calculating Heat Gains

• to effectively calculate heating/cooling loads we need to calculate the other energy inputs (solar and internal heat gains)

– solar gain is typically calculated within building simulation tools as part of the heat gain calculation or can be pre-calculated using climate data, geometric data and glazing data

– internal heat gains (people and equipment) are typically prescribed and are a “boundary condition” for the heating/cooling load calculation


• the basis for these is typically a prescribed schedule detailing: when people are ‘active’ and when equipment is functioning

• typically occupancy ‘profiles’ are developed• these are then used with heat gain data to calculate time series

heat gains, that are used as boundary conditions for modelling time-series performance

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

time of day

nu

mb

er

of a

ctiv

e o

ccu

pa

nts


• data is available for people and equipment (for example):

315210GymnasiumAthletics

14080FactoryLight bench work

8080RestaurantSedentary work

7075BankWalking standing

5575Department store, retail store

Standing, light work; walking

5575Offices, hotels, apartments

Moderate office work


Seated very light work

Latent Heat Gain

(Watts)

Sensible Heat Gain

(Watts)Typical buildingConditions

315210GymnasiumAthletics

14080FactoryLight bench work

8080RestaurantSedentary work

7075BankWalking standing

5575Department store, retail store

Standing, light work; walking


Moderate office work


Seated very light work

Latent Heat Gain

(Watts)

Sensible Heat Gain

(Watts)Typical buildingConditions

Appliance (W)Chest freezer 190

Fridge freezer 190

Refrigerator 110

Upright freezer 155

Answer machine 0

Cassette / CD Player 15

Clock 0

Cordless telephone 0

Hi-Fi 100

Iron 1000

Vacuum 2000

Fax 37

Personal computer 141

Printer 335

TV 1 124

TV 2 124

TV 3 124

VCR / DVD 34

TV Receiver box 27

Hob 2400

Oven 2125

Microwave 1250

Kettle 2000

Small cooking (group) 1000

Dish washer 1131

Tumble dryer 2500

Washing machine 406

Washer dryer 792

DESWH 3000

E-INST 3000

Electric shower 9000

Storage heaters 10200

Other electric space heating 2000

• using occupancy/equipment profiles and heat gain data enables a time-series heat gain profile to be developed


Calculating Electrical Demand• the electrical demand profile can be derived from the heat gain profile for

electrical consuming equipment or vice versa• can assume that 100% of the electrical demand is eventually degraded to heat• a few exceptions e.g. lighting with in built extract • also it is possible to simulate the operation of daylight controlled lighting using a

simulation tool (e.g. ESP-r) or some lighting design tools (e.g. DIALUX)• there are also free tools to generate electrical profiles

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6000

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

Dwelling load profile (W)

Calculating Electrical Demand

Munute vs Hourly Data

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1000

2000

3000

4000

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6000

1 56 111 166 221 276 331 386 441 496 551 606 661 716 771 826 881 936 991 1046 1101 1156 1211 1266 1321 1376 1431

Minutes

Dem

and

(W

)

Minutely Hourly Averaged

• the characteristics of electrical demand can be significantly affected by time-averaging

• generally the higher the time resolution the more realistic the electrical demand profile

Calculating Hot Water Demand• as with occupant and equipment gains, hot water demands are

typically calculated using a pre-defined draw-schedule• this indicates the total draw being taken from a storage tank or

needs to be supplied from a device

Calculating Hot Water Demand• again these are highly intermittent and significantly affected by

averaging• the resulting time-series heat demand (W) can be calculated if

the hot water supply temperature and the feed water inlet temperature are known or assumed

)( TTcmQ s

Calculating Resulting Emissions• calculation of emissions associated with energy use require the

desegregation (by type) of energy demands• …and carbon emissions rates (cx) for the different fuel types• the carbon emissions are determined by multiplying the energy

consumption over the period analysed by the appropriate rate:

ECEgasHWHc cEEcEEM

a closer look at energy demands: quantification and characterisation

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