thermal modelling of a building with an integrated ventilated pv façade

Thermal modelling of a building with an integratedventilated PV facade

Li Meia,*, David Infielda, Ursula Eickerb,1, Volker Fuxb

aCentre for Renewable Energy Systems Technology (CREST), Department of Electronic and Electrical Engineering,

Loughborough University, Loughborough, Leicestershire LE11 3TU, UKbDepartment of Building Physics, Hochschule fur Technik, Schellingstr. 24, 70174 Stuttgart, Germany

Received 15 November 2001; accepted 25 September 2002

Abstract

This paper presents a dynamic thermal model based on TRNSYS, for a building with an integrated ventilated PV facade/solar air collector

system. The building model developed has been validated against experimental data from a 6.5 m high PV facade on the Mataro Library near

Barcelona. Preheating of the ventilation air within the facade is through incident solar radiation heating of the PV elements and subsequent

heat transmission to the air within the ventilation gap. The warmed air can be used for building heating in winter. Modelled and measured air

temperatures are found to be in good agreement. The heating and cooling loads for the building with and without such a ventilated facade have

been calculated and the impact of climatic variations on the performance such buildings has also been investigated. It was found that the

cooling loads are marginally higher with the PV facade for all locations considered, whereas the impact of the facade on the heating load

depends critically on location.

# 2002 Elsevier Science B.V. All rights reserved.

Keywords: Thermal modelling; Ventilated facade; PV; Building performance

1. Introduction

Integrating photovoltaic panels into a building facade

represents a significant step forward in the application of

this relatively new technology. Such a facade serves not only

as a renewable source of electricity, but also as a source of

heat for building heating and cooling. The authors have

recently completed an EU project which built on the experi-

ence gained in an earlier project concerned with the venti-

lated photovoltaic facade of the Mataro public library, near

Barcelona [1]. This recent project has taken the issue of

building integration an important step further, in that dedi-

cated solar air heaters have been incorporated into the upper

part of the facade in order to provide air heated to a

temperature sufficient for direct space heating purposes.

In order to achieve good heat transfer within the facade

and solar collectors and also to reduce the operating tem-

perature of the PV modules, forced convection was found

necessary since stack effect/buoyancy driven flow rates were

too limited.

Various authors have modelled the ventilated PV facade

by evaluation of energy inputs and outputs through radiation,

convection, conduction and power generated, [2] and [3].

These studies of the thermal energy balance are however

restricted to steady state conditions. In earlier work by the

authors, a dynamic general finite element thermal model for

ventilated PV facades was developed [4]. Based on this and

the TRNSYS program, a complete thermal building model

incorporating a ventilated PV facade and solar air collectors

has been assembled. The building model comprised of three

major components: the PV facade (PV panel, air gap and

inner double glazing); the solar air collectors; and a

TRNSYS single zone building model together with appro-

priate controller models. This paper outlines the main

features of the complete model. An investigation of the

heating and cooling energy required for the building has

been undertaken using the model. To assess the thermal

impact of the ventilated PV facade, heating and cooling

loads for the building with and without facade have been

calculated. In addition, the model has been used to assess the

performance of such buildings at different European loca-

tions, exhibiting contrasting climatic conditions.

Energy and Buildings 35 (2003) 605–617

* Corresponding author. Tel.: þ44-1509-228145;

fax: þ44-1509-610031.

E-mail addresses: [email protected] (L. Mei), [email protected]

(U. Eicker).1 Tel.: þ49-711-121-2831; fax: þ49-711-121-2666.

0378-7788/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved.

PII: S 0 3 7 8 - 7 7 8 8 ( 0 2 ) 0 0 1 6 8 - 8

2. Thermal building model

The geometry of the Mataro library building is a rectan-

gular block which can be considered as having two levels. In

the modelling, only the upper level is taken into account

treated as a single zone, and the lower level is represented

through a constant temperature partition. This is appropriate

because the PV facade is attached only to the south wall of

the upper level with the lower level adjoining the soil. The

south side of the building is formed by the PV panels, the

solar air collectors and a conventional brick wall. The PV

panels contain blue polycrystalline silicon solar cells encap-

sulated in a clear glass–glass laminate in such a way to give

an overall transparency of 15%. The non-south facing

opaque walls are constructed of cellular concrete with

external steel covering. Windows of different size are fitted

on the north, west and east elevations. Fig. 1 gives a view of

the building showing the south and east elevations.

2.1. PV facade model

The PV facade structure consists of the PV panels and a

double glazed window, with a 14 cm air gap between.

Exterior air is entrained at the base of the facade and injected

via the air collector at the top into the building ventilation

system. Fig. 2 shows the PV facade structure and the thermal

transfer scheme. G represents the solar irradiation striking

the PV panel; Tp and Tg are the temperatures of ventilated

gap inside surfaces; hc,p and hc,g the respective convective

Nomenclature

Ac effective air collector area (m2)

Ap total PV panel area (m2)

Aw total windows area (m2)

bt, ct and

dt

transfer function coefficients

Cp specific heat capacity of air (J/kg K)

FR overall collector heat removal efficiency

factor

GrH Grashof number

GT incident radiation on the collector surface

(W/m2)

Gw incident radiation on the building surface

(W/m2)

hc,g convective heat transfer coefficient of

ventilated gap—glass window side

(W/m2 K)

hc,i heat transfer coefficient on the window

double glazing room side (W/m2 K)

hc,o heat transfer coefficient on the PV panel

exterior (W/m2 K)

hc,p convective heat transfer coefficient of venti

lated gap—PV panel side (W/m2 K)

kair thermal conductive coefficient of air

(W/m K)

kg thermal conductive coefficient of glazing

(W/m K)

ki thermal conductive coefficient of different

materials in Eq. (1) (W/m K)

kp thermal conductive coefficient of PV panel

(W/m K)

L long wave heat exchange gain (W/m2)

m ventilated air flow rate (kg/s)

Nu Nusselt number

qi internal heat source generated per unit

volume of the medium in Eq. (1) (W/m3)

Qinf l infiltration gain (W)

Qu total useful energy gain of air collector (W)

Qvent ventilation gain (W)

Qwd diffuse radiation entering windows (W)

Qwbf beam radiation through windows striking

floor (W)

Qwbs beam radiation through windows striking

other surfaces (W)

Qz heat gain through the wall and roof to the

building inside space (W/m2)

Re Reynolds number

S short wave radiation gain (W/m2)

Ta ambient air temperature (8C)

Teq equivalent room inside temperature, defined

by Eq. (15)

Tfacade facade room side surface temperature (8C)

Tg inner surface temperature of ventilated

gap—glass window side (8C)

Ti temperatures of the different construction

layers (8C)

Ti,c air collector inlet temperature (8C)

Tm air temperature in the gap (8C)

Tm,mean mean air temperature in the gap (8C)

To,c air collector outlet temperature (8C)

Tp inner surface temperature of ventilated

gap—PV panel side (8C)

Tsa solar air temperature (8C)

UL overall heat loss coefficient of collector

(W/m2 K)

Uw heat transfer coefficient of windows

(W/m2 K)

Greek letters

ai thermal diffusivity (m2/s)

eg surface emmisivity of double glazing

ep surface emmisivity of PV panel

Z air collector efficiency

n air velocity (m/s)

s Stefan–Boltzmann constant ¼ 5:67 � 10�8

W/m2 K4

ta effective transmittance–absorptance

product

u kinematic viscosity of air (m2/s)

606 L. Mei et al. / Energy and Buildings 35 (2003) 605–617

heat transfer coefficients for their inside surfaces; Tðx ¼ 0Þand Tðx ¼ LÞ the temperatures of PV panel outside surface

and the double glazing room side; hc,o and hc,i the convective

heat transfer coefficients for the PV panel outside surface

and the room inside surface; and x and y are the co-ordinates

associated with facade thickness and height.

Earlier studies made use of a simplified steady state

analysis [5], whereas here, a fully dynamic thermal model

for the ventilated PV facade, based on a numerical solution,

is presented.

From Fig. 2, it can be seen that the dynamical form of one-

dimension heat conduction in the x-direction for PV facade

can be expressed by Fourier’s equation:

@T2i

@x2þ qi

ki

¼ 1

ai

@Ti

@t(1)

where the Ti represent the temperatures of the different

construction layers, and are functions of time t and the layer

position x; ai ¼ ki=rcp is thermal diffusivities, ki is the thermal

conductivties of various materials; and qi represent the internal

heat sources generated per unit volume of the various materi-

als, corresponding to the part of solar radiation absorbed and

converted into thermal energy at the PV panel and the double

glazing. In this study, the transmittance–absorptance product

for PV panel has been taken to be constant at 0.8 to account for

the 15% transparency of the PV laminates mentioned above

and reflectance from the PV modules. At the same time, the

semi-transparency of the PV panel allows 15% of the short-

wave radiation to pass directly through the PV panel and the

double glazed window (i.e. ignoring absorption by the glass).

The boundary/initial conditions for Eq. (1) are determined

by the exterior and interior temperatures and the heat

flux:

�kp@T

@xjx¼0 ¼ hc;o½To � Tðx ¼ 0; tÞ (2)

and

�kg@T

@xjx¼L ¼ hc;i½Tðx ¼ L; tÞ � Ti (3)

with Tðx; t ¼ 0Þ ¼ 20 8C taken as initial value.

Here, kp and kg are the thermal conductivities of the PV

panel and the glazing, respectively, and hc,o and hc,i are the

surface heat transfer coefficients on the PV panel exterior

and double glazing, respectively. In the computations, hc,o

and hc,i are considered to be constant at 15 and 5 W/m2 K,

respectively. The constant value of hc,o represents a fixed low

wind speed and this reflects the lack of available local wind

speed data for model validation purposes.

A Crank–Nicolson method [6] was used to solve the

Eqs. (1)–(3). This method compared with the other finite

difference solutions has the advantage of being uncondi-

tionally stable and tolerating variable time-steps. This

numerical model can be integrated easily into other dynamic

simulation programs, such as TRNSYS.

The energy balance between the facade and the ventila-

tion air can be expressed by

hc;pðTp � TmÞ þ hc;gðTg � TmÞ ¼ mCp

dTm

dy(4)

Fig. 1. Geometry of the Mataro library building.

Fig. 2. PV facade structure and thermal transfer scheme.

L. Mei et al. / Energy and Buildings 35 (2003) 605–617 607

where m is the air flow rate and Cp the specific heat capacity

of air. Surface temperatures of the PV panel and glass

window within the air gap can be determined by the layer

temperatures given by Eqs. (1)–(3). By solving Eq. (4), the

air temperature in the gap Tm can be expressed as a function

of the gap height y:

TmðyÞ ¼ exp �ðhc;p þ hc;gÞymCp

� �Tin

þ 1�exp �ðhc;p þ hc;gÞymCp

� �� hc;pTp þ hc;gTg

hc;p þ hc;g

� �:

(5)

The mean air temperature can be obtained by integrating Tm

from y ¼ 0 to H:

Tm;mean ¼ 1

H

Z H

0

TmðyÞdy ¼ 1 � exp �ðhc;p þ hc;gÞHmCp

� ��

� Tin � ðhc;pTp þ hc;gTgÞ=ðhc;p þ hc;gÞðhc;p þ hc;gÞH=mCp

� �

þ hc;pTp þ hc;gTg

hc;p þ hc;g(6)

where Tin is the inlet temperature for the ventilated chamber

which is approximately equal to the ambient air temperature,

and for simplicity is taken to be exactly so in this study.

It can be seen from Eq. (6) that the air temperature in the

ventilated chamber only depends on the two surface tem-

peratures, Tp and Tg, when the air mass flow rate, the inlet

temperature Tin and the convective coefficients are known.

Inserting Tm,mean as a layer temperature between Tp and Tg,

the finite deference solution can be applied to whole PV

facade for thermal transmission through the air gap.

The convective heat transfer coefficients within the gap,

hc,p and hc,g, are far from straightforward to estimate. This is

because, in reality, the heat transfer processes involve a

combination of forced and natural convection, laminar and

turbulent flow and, certainly in the entrance region, simul-

taneously developing flow (in which the hydrodynamic and

thermal flow profiles are both evolving). For such lower air

flow velocities (<0.5 m/s), it is essential to model an appro-

priate mixture of flow conditions. As is common, the non-

dimensional Nusselt number has been used to estimate the

heat convection coefficient hc. A useful expression of the

Nusselt number, for mixed flow condition is [7]:

�Nu ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi�Nu2

lam þ �Nu2turb

q(7)

with

�Nulam ¼ 0:644ffiffiffiffiffiffiRe

p ffiffiffiffiffiPr

3p

;

�Nuturb ¼ 0:037Re0:8Pr

1 þ 2:444Re�0:1ðPr2=3 � 1Þwhere

Re ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiRe2

force þ Re2H;free

q(8)

and

Reforce ¼nH

u; ReH;free ¼

ffiffiffiffiffiffiffiffiGrH

2:5

r

where Re is the Reynolds number, Pr the Prandtl number and

GrH the Grashof number, n the air velocity, and u the

kinematic viscosity of air (m2/s). Using the properties of

air at the mean air temperature, the convection heat transfer

coefficient can be obtained directly from the Nusselt number

in the normal way:

hc ¼�Nu � kair

D(9)

where kair is the thermal conductivity of air and D the plate

spacing.

By applying Eqs. (7)–(9) independently for the two vertical

surfaces, namely, the PV panel and the double glazing, the

coefficients hc,p and hc,g can be calculated. These are found to

provide a good agreement between the measured and calcu-

lated air chamber temperatures, and justify the idealisation of

two independent surfaces irrespective of the relatively small

distance (140 mm) between them.

The long wave radiant heat exchange between the sur-

faces inside the PV gap is straightforwardly modelled by

Qp=g ¼ Ap

sðT2p þ T2

g ÞðTp þ TgÞð1=epÞ þ ð1=egÞ � 1

ðTp � TgÞ (10)

where ep and eg are the surface emmisivities of the PV panel

and double glazing (0.88), respectively, and s the Stefan–

Boltzmann constant. Eq. (10) presents a standard linearised

internal heat exchange relation and will be used throughout

to approximate the radiative heat exchange for the facade. In

the numerical solution of the PV facade model, the calcu-

lated radiative heat flow is added (i.e. as treated heat gain) to

the colder surface, and is subtracted (as heat loss) from the

warmer surface. The complete calculation (i.e. solution of

Eqs. (1)–(6)) is repeated with the already calculated heat

gains/losses, and the resulting layer temperatures re-deter-

mined as before. This iterative process is repeated until

sufficient convergence is achieved.

Considering the different thermal properties of materials,

the PV facade is considered as three distinct sections: the PV

panel; the double glazing; and the air gap between. The PV

panel itself contains three distinct layers: glass/PV/glass.

The double glazing also in principal contains three layers but

these are not differentiated in this model. The thermal

properties for the various layers are listed in Table 1.

The numerical method described here is for one-dimen-

sional heat transfer, although the model allows the facade

to be divided into up to 50 segments in order to better

calculate the gap air temperature profile. All this assumes a

uniform temperature within each segments of each layer in

the vertical direction, and uniform solar radiation on the

exterior surface. For each segment the layer temperature


(including the gap surface temperatures) and the gap outlet

temperature is calculated. The gap outlet temperature from

one segment becomes the inlet temperature for the next

segment placed above and so on.

2.2. Solar air collector model

The standard thermal model for solar air collectors, as

incorporated within the top section of the facade, is given by

the Hottel–Whillier, Bliss equation [8]:

Z ¼ Qu

GTAc¼ FRðtaÞ �

FRULðTi;c � TaÞGT

(11)

and

To;c ¼Qu

Cp _mþ Ti;c (12)

where Z is the collector efficiency, Qu the useful energy gain,

GT the total incident radiation on the collector surface, Ac the

effective collector surface area, FR the overall collector heat

removal efficiency factor, and UL the overall heat loss

coefficient of the collector. Ta, Ti,c and To,c are the tempera-

tures of the ambient air, the air collector inlet and the

collector outlet, respectively. It should be noted that the

inlet air temperature of the solar air collector, Ti,c is the outlet

air temperature of the ventilated facade since these are

connected in series. The back of the solar air collector is

assumed to be perfectly insulated from the interior of the

room.

Collector test results are normally presented as a linear

relation between Z and ðTi;c � TaÞ=GT with a intercept a

(FR(ta)) and slope of b (FRUL). With the values of a and b

known, this linear efficiency model can be used to straight-

forwardly calculate the useful energy gain and the collector

outlet temperature.

The values of a and b for different air velocities, were

obtained from experimental data provided by the manufac-

turer; these are listed in Table 2.

2.3. The completed building model

It can be seen from Fig. 1 that, aside from the limited

lower brick section, the south facing elevation of the build-

ing is taken up with the ventilated PV facade and solar air

collectors. The remaining surfaces of the building, the walls

orientated to the north, west and east, the ceiling and floor

are taken into account within the single zone representation

of the building.

In contrast to the facade model, the transient heat response

of the other surfaces of the building is represented using the

transfer function method [9]. This has been done in order to

keep the overall model manageable, and because the mod-

elling challenge of this work relates specifically to the

facade and not the conventional parts of the structure. In

this transfer function approach, which is supported by

TRNSYS, a conduction transfer function is used to describe

the heat fluxes at the inside of walls and the roof as a function

of previous values of the heat fluxes and previous values of

inside and outside temperatures. Application of the transfer

function approach to the heat gain/loss through the building

construction layers allows the heat flux to be expressed as

[9,10]:

Qz ¼Xt¼0

ðbtTsa;t � ctTeq;tÞ �Xt¼1

dtQz;t (13)

where t represents the time step (1 h steps are often sufficient

for building analysis and have been used here). The value of

t ¼ 0 represents the current time, t ¼ 1 represents previous

hour, and so on. Qz is the heat gain through walls and roof to

the building inside space via the corresponding transfer

function coefficients, and bt, ct and dt, the conduction

transfer function coefficients pre-calculated for representa-

tive wall and roof assemblies. These coefficients depend

only on the building construction layers and their thermo-

physical properties. For example, the west wall of the

Mataro building consists of three layers. These are a

0.007 m steel cover, a 0.14 m air space and a 0.25 m cellular

concrete wall. For this construction the transfer function

Table 1

The thermal properties of the PV facade

Left side wall Air gap Right side wall

Layer 1 Layer 2 Layer 3Layer 4

Layer 5 Layer 6 Layer 7

Material Glazed PV Glazed Air Glazed Air Glazed

Conductivity (W/m K) 0.8 0.8 0.8 0.8 0.021 0.8

Density (kg/m3) 2500 2500 2500 2500 1 2500

Capacity (J/K) 1000 1000 1000 1000 1000 1000

Width (m) 0.004 0.0045 0.004 0.14 0.004 0.012 0.004

Table 2

The collector test data

Velocity (m/s) Value a (W/m2 K) Value b (W/m2 K)

2.8 0.65 �11.6

2.2 0.64 �12.2

1.7 0.61 �13.1

1.1 0.51 �12.7

0.55 0.46 �11.7


coefficients bt, ct and dt are estimated following [10] and

given by Table 3.

From Eq. (13), it can be seen that the conduction transfer

function represented by bt is driven by the solar air tem-

perature, Tsa. In TRNSYS this is calculated according to the

solar radiation and convective heat transfer occurring on the

exposed external surfaces [10]:

Tsa ¼ Ta þGw

hc;o(14)

where hc,o is the building outside convection heat transfer

coefficient which itself is a function of wind speed:

hc;o ¼ 5:7 þ 3:8 � wind speed, Ta is the ambient air tem-

perature, and Gw the total incident solar radiation absorbed

by walls or roof. As the surfaces are at the different

orientations they will receive differing amounts of solar

radiation, Tsa is therefore different for the each individual

surface of the building.

Teq of Eq. (15) is an equivalent room inside temperature

defined by

Teq ¼ Ti þS þ L

hc;i(15)

where Ti is the actual internal space air temperature. This

equivalent room inside temperature is coupled to the short-

wave radiation heat gain, S, absorbed by the internal surfaces

and the longwave heat exchange, L, between the internal

surfaces.

Direct shortwave radiation heat gain, S, due to solar

radiation penetrating windows is calculated from the inci-

dent beam and diffuse radiation components available from

climate data for the site. The proportion of incoming radia-

tion distributed onto the surfaces of wall, ceiling and floor is

calculated according to the total exchange factor as given for

example by [10]. To take the case of the floor for example,

the net shortwave radiation received is given by:

Sf ¼ Ffwð1 � rfÞQwd

Af

þ ð1 � rfÞQwbf

Af

þX

rsQwbsFfsð1 � rfÞAs

Af

(16)

where the subscripts f, w and s are for the floor, window and

other surfaces, respectively, r the surface reflectance, A the

surface area, F the exchange factor, Qwd the diffuse radiation

entering windows, and Qwbf and Qwbs are the fractional beam

radiation through the window striking floor and other sur-

faces, respectively. The first term of Eq. (16) represents the

diffuse radiation to the floor from the window, the second is

the beam radiation to the floor from the window, and the third

is the diffusely reflected beam radiation from other surfaces

absorbed by floor. If required, radiation from people, lighting

and equipment can also be added to the term S.

The longwave radiation heat exchange, L, between the

surfaces inside the zone is modelled using the linearised

radiative heat transfer coefficient, hr,s, which is a function of�T

3. For the purpose of estimating this coefficient, �T has been

assumed to be 20 8C. The small error introduced by this

assumption is not critical.

The thermal conduction through the window from ambi-

ent is given by

Qw ¼ AwUwðTa � TeqÞ (17)

where Uw is the reciprocal of the sum of the resistances of

the window, outside air and inside air surface, Aw the total

area of windows. Teq is the estimated equivalent zone

temperature.

The ventilation gains/losses to the zone are assumed to be

due to the building design ventilation rate of 9000 m3/h,

hence,

Qvent ¼ Cp _mventðTa � TiÞ (18)

where Qvent is the ventilation gain, _mvent the ventilation air

flow rate, Cp the specific heat of air.

The infiltration gain is given by

Qinf ¼ Cp _minf lðTa � TiÞ (19)

where Qinf l is the infiltration gain; the infiltration air flow

rate is given by

_minf l ¼ raVð0:1 þ 0:023jTa � Tij þ 0:07WÞ (20)

where V (12509 m3) is the building volume, and W the

external wind speed loading the building. This expression

for the infiltration flow rate is taken from the ASHRAE

Handbook of Fundamentals [9].

3. Model simulation and comparison withmeasured data

3.1. Integration of the PV facade model with TRNSYS

building model

As discussed previously, the dynamic PV facade thermal

model is solved using a finite difference method. Heat

transfer modelling for the other surfaces of the building

are based on the transfer function method as implemented in

Table 3

Transfer function coefficients for the west wall

t b c d

West wall

0 0.0000 5.60 1.00

1 0.0000 �13.93 �2.18

2 0.0015 12.51 1.68

3 0.0074 �5.01 �0.56

4 0.0076 0.91 0.08

5 0.0021 �0.07 �0.01

6 0.0002 0.00 0.00

7 0.0000 0.00 0.00


the TRNSYS building simulation environment. In order to

combine the PV facade model with the building model, a

dynamic link library file (DLL) has been created containing

the new special type code (written in Delphi). This DLL file

is compiled in the TRNSYS simulation project and linked to

Fortran code which passes the input and output variables

associated with the facade model. All the thermal properties

of the PV facade are stored in a pre-processing input file

which can be edited by users and read by the TRNSYS

program.

To illustrate how the interface to this new special type

operates, the heat transfer to the interior from the facade is

examined. The heat flux from the room side surface of the

PV facade to the building internal space is considered as an

additional heat gain/loss to the single zone building model.

This heat gain/loss is calculated by

Qin ¼ hc � Ap � ðTfacade � TeqÞ

where Tfacade is the layer temperature of room side surface of

the facade, Teq the equivalent zone temperature calculated by

the single zone model, Ap the facade area, hc the convective

heat transfer coefficient, assumed to be 5 W/m2 K. In the

simulation, Teq is taken as the value calculated by the single

zone building model at the previous timestep.

3.2. Model validation for sample periods

Outputs from the complete thermal building model have

been compared with measured data from Mataro Library.

Three sets of measured temperatures during unoccupied

periods were used for comparison to the simulated results.

These were selected because during these times the HVAC

plant was not operating and there is thus no additional

thermal energy supplied to or extracted from the zone. In

these circumstances, the building performance is determined

only by the incident solar radiation and ambient environ-

ment (ambient temperature and wind speed).

The measured data from Mataro, including total horizon-

tal global radiation, outside air temperature and wind speed

are used as the time dependent input data for the building

model simulation. Other measured data, such as the building

inside air temperature, the outlet temperatures of the PV

facade gap and the air collectors are used to validate the

model.

Fig. 3. Room temperature comparison (summer).

Fig. 4. Room temperature comparison (summer).


The horizontal radiation measured is used to generate the

total incident and beam incident radiation on the vertical

surfaces of the building in different orientations. This cal-

culation has been undertaken using the TRNSYS imple-

mentation of the Reindl solar processor and the Isotropic sky

models [10].

Measured data has been used to initialise the model.

However, the initial value of zone temperature was set to

a constant of 20 8C through the simulation in order to

calculate the longwave radiation heat exchange coefficient,

hr,s ð�T ¼ 20 �CÞ.

Figs. 3–5 show the measured room temperature together

with the simulated temperature for the three periods in

question. It can be seen that the simulated temperature

fluctuations are very close to the measured data. However,

the model response is slightly slower than the building’s.

This reflects the approximate value taken for the effective

internal thermal capacity used in the room temperature

calculation. The peak room temperature in summer is about

30 8C without air conditioning of the building. In winter the

room temperature can rise to 25 8C without heating. It is

clear that for the Mataro library building, with its large

Fig. 5. Room temperature comparison (winter).

Fig. 6. PV facade outlet temperature comparison (summer).

Fig. 7. Air collector outlet temperature comparison (summer).


glazed south facing facade, the cooling load exceeds the

heating load.

The PV facade air gap outlet temperature and the air

collector outlet temperature for both simulation and mea-

surement are presented in the Figs. 6–11 for the different

measurement periods. The calculated PV gap outlet air

temperature compares well with the measured data. It

reaches up about 50 8C in summer, and about 35 8C on a

typical winter day. The simulated air collector outlet tem-

perature agrees reasonably the measured data, which can

reach up to 60 8C in summer and 50 8C in winter, although

during winter the measured air collector temperature

remains slightly higher than the simulated values for

extended periods.

Fig. 8. PV facade outlet temperature comparison (late summer).

Fig. 9. Air collector outlet temperature comparison (late summer).

Fig. 10. PV facade outlet temperature comparison (winter).


4. Predicting the cooling load and heating loadusing the building model

4.1. The temperature control

The cooling and heating loads of the building depend of

course on the required interior temperature levels. In energy

rate control strategy for building heating/cooling loads

calculation was developed within TRNSYS. The maximum

and minimum room temperature limits are user-set con-

stants. For the purpose of estimating the heating/cooling

energy required for real buildings, the temperature setpoints

for occupied and unoccupied periods should be allowed to

differ. TRNSYS does not facilitate a straightforward imple-

mentation of this.

In order to represent the building energy management

approach used at Mataro, a simple energy control strategy

was developed. In this approach, a general HVAC plant

control model is connected to the Mataro building model for

calculating the heating/cooling energy required to maintain

the inside space temperature at the required setpoints. The

control strategy is illustrated in Fig. 12; it is a normal

feedback control loop in which the controller output U is

the required energy for heating or cooling purposes (equiva-

lent to the building heating and cooling loads). Heating loads

are treated as positive, whilst cooling loads take negative

values.

The temperature setpoints for the heating and cooling

seasons are selected as the actual building plant control

parameters used at Mataro:

� heating season: occupied time 20 8C, unoccupied time

17 8C;

� cooling season: occupied and unoccupied time 26 8C;

� weekend days are unoccupied time.

4.2. The air gap ventilator control

Since a ventilated PV facade can supply preheated air to

the building interior, improvements to the building control

system may be required in order to make effective use of the

warm air produced by the facade. Forced ventilation of air

through the facade can be controlled according to strategies

which reflect the varying conditions occurring during the

heating and cooling seasons. The ON/OFF control modelled

here can be summarised as:

� Winter condition (occupied time): if the facade tempera-

ture is 5 8C higher than the exterior air temperature and

the room temperature is lower than the setpoint, the

ventilator is operated and the pre-heated ventilation air

is directed to the air conditioning unit.

� Winter condition (unoccupied time): if the facade tem-

perature is 5 8C higher than the room temperature and the

room temperature is lower than the setpoint, the ventilator

is operated and the pre-heated ventilation air is directed to

the air conditioning unit.

� Summer condition: if facade temperature is higher than

38 8C, the ventilator is operated and the ventilated air is

vented directly to the exterior for facade cooling purposes.

Since continuous measurements from the Mataro library

spanning a whole year are not available, weather data

generated using the proprietary code, METEONORM

[11] has been used in the heating and cooling loads estima-

tion. Time dependent hourly data sets including global

horizontal radiation, ambient temperature and wind velocity

have been created for three locations: Barcelona; Stuttgart;

and Loughborough, in order to assess the performance of the

PV ventilated facade concept for differing EU climates.

Fig. 11. Air collector outlet temperature comparison (winter).

Fig. 12. The scheme for heating/cooling load prediction.


4.3. The prediction results

Figs. 13 and 14 provide a snap-shot of room temperature

and the corresponding ambient temperature variations for

Barcelona during January and August, respectively. In

Fig. 13 (heating season), the last 2 days cover the weekend,

and the room temperature setpoint is 17 8C. It is clear that

during these 2 days the room temperature is higher than the

setpoint due to the higher ambient temperature. Thus, no

heating energy is required for these days. For remaining days

the library is in use and the room temperature is kept at the

setpoint (20 8C) by the heating system.

In Fig. 14 (cooling season), the supplied cooling power

must keep the room temperature at 26 8C. Of course, if the

room temperature is lower than the setpoint, cooling power

is not required. Thus, there is no cooling power supplied at

night during this period.

Simulations for Stuttgart and Loughborough have also

been carried out also based on METEONORM weather data.

The room temperature is maintained at the setpoint if it

lower than 17 8C/20 8C in winter or higher than 26 8C in

summer, using heating and cooling as required.

By integrating the heating and cooling power from the

simulations, the annual heating and cooling loads have been

estimated for the library building design located in Barce-

lona, Stuttgart and Loughborough. Note that no changes

were made to the building control specification. This was to

enable a comparison of operational performance in these

different climates. In reality marginally different levels of

insulation and plant design would apply. Fig. 15 shows the

annual heating/cooling loads calculated using the Mataro

simulation model for the three locations. The results reflect

the climatic conditions: as might be expected, the highest

heating loads are experienced in Stuttgart, whereas Barce-

lona with the hottest climate gives the highest cooling loads.

4.4. Comparison of heating and cooling loads for

the PV facade and a conventional structure

The building with neither PV facade nor solar air collec-

tors has been modelled to assess, by comparison, the facade

effects on the heating and cooling energy. The PV facade

(including the inner double glazing) and air collectors, of the

south side of the library are replaced by a conventional brick

construction with glazed window and entrance door. The

combined area of the window and door was chosen to match

to the 15% transparency of the PV facade.

Fig. 13. Estimated room temperature (winter).

Fig. 14. Estimated room temperature (summer).

Fig. 15. Annual heating/cooling loads.


In Figs. 16 and 17, the heating and cooling loads for the

building with and without facade are compared. It can be

seen, contrary to expectation, that the ventilated PV facade

does not result in a larger heating contribution to the

conventional building for the colder climate areas of Stutt-

gart and Loughborough. This is because the PV facade

exhibits a larger heat loss coefficient than the conventional

brick wall. The higher heat loss from PV facade is not fully

compensated for by the pre-heating of useful ventilated air.

Reflecting the high solar gain, the cooling load is the

largest for the PV facade in Barcelona, where an annual

value of 51546 kWh is indicated by the simulation. For

Loughborough, the cooling loads with and without the

facade are both small and can be safely ignored.

4.5. The analysis for the ventilation heat gain

Simulation of the Mataro building with its PV facade and

solar air collectors also facilitates prediction of the ventila-

tion heat gain to be expected at three different locations.

Because of the differing climatic conditions, the proportion

of the total required heat load met from the heated ventila-

tion air varies significantly. It can be seen from Table 4 that

12% of the heating load can be supplied from the facade in

Barcelona, whereas only 2% of the ventilation heat load can

be supplied in Stuttgart or Loughborough. The average of

the outside temperature and incident solar radiation for

winter season are also illustrated in Table 4.

5. Conclusions

In this paper, a thermal building model that includes sub-

models of the ventilated PV facade and the additional solar

air collectors has been described. The model has been

validated against measured performance data when the

HVAC plant was not being operated. The modelled con-

tributions from the solar gain, and the heat loss for the

building as a whole, were captured with acceptable accuracy.

This model will be applied to refine the design of such

building, and the controls, as part of a planned future study.

Fig. 16. Cooling loads comparison.

Fig. 17. Heating loads comparison.

Table 4

Ventilation heat gains for three locations

Location Stuttgart Lboro Barcelona

Average outside temperature (8C) 3.35 5.27 11.1

Average incident radiation (kJ/h m2) 363 308 466

Average air collector temperature (8C) 8.93 10.05 16.5

Ventilation heat gain (kWh) 3779 3161 9339

Proportion of vent gain to heat load (%) 2.05 1.83 12.37


Based on the developed building model, the heating

and cooling loads for the building, in different European

locations, have been estimated. From both measurement

and simulation, it can be seen that the PV facade outlet

air temperature reaches around 50 8C in summer and 40 8Cin winter. Twelve percent of heating energy can be saved

using the pre-heated ventilation of the air for the building

location in Barcelona in winter season. For Stuttgart

and Loughborough, only 2% heating energy can be saved,

although of course the design was not made within

these locations in mind. Indeed it is clear that for such

northern latitude, a far higher proportion of solar air

collector area would be appropriate. The work establishes

that accurate modelling of buildings incorporating venti-

lated PV facades can be achieved within the TRNSYS

environment, but an appropriate special type, as described

here, to represent the novel features of the facade itself

must be used.

Acknowledgements

The authors are grateful for the financial support from

the European commission, through contract JOR3-CT97-

0185.

References

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[6] J.A. Clarke, Energy Simulation in Building Design, Hilger, Bristol,

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[9] ASHRAE, Handbook of Fundamentals, New York, 1993.

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[11] METEONORM-Global Meteorological Database for Solar Energy

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thermal modelling of a building with an integrated ventilated pv façade

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