MSC IN SUSTAINABLE E NGINEERING

MSC IN SUSTAINABLE E NGINEERING: RENEWABL E ENERGY SYSTEMS & T HE ENVIRONMENT
FIRST COURSEWORK
ME930: Energy Modelling and Monitoring

Fernando Agudín Muñoz
29/10/201 8
Table of contents
1. Introduction ………………………….. ………………………….. ………………………….. ………… 2
2. Description of the model ………………………….. ………………………….. …………………… 2
3. Numerical experiments performed ………………………….. ………………………….. ……… 3
4. Results and discussion ………………………….. ………………………….. …………………….. 3
5. Conclusions ………………………….. ………………………….. ………………………….. ……….. 8
6. References ………………………….. ………………………….. ………………………….. ………… 9

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1. Introduction
The energy consumed by a building depends upon many factors. Between them we can
find: weather conditions (dry bulb T) where the building is located, materials that
compound the building, lightning, HVAC systems and occupancy are the most important
ones. The variety of factors makes that the prediction of the consumption not easy to be
carried out. Universities and companies are struggling with this issue. To predict it, both
universities and companies usually develop their own simulation programmes to make
assumptions and to understand better the problem they face. The most typical building
subject of study are residential, engineering and office ones (Zhao and Magoulès, 2012) .
Focus on the buildings sector, its final energy consumption represents over one -third of
the total final energy (International Energy Agency, 2013) , with the consequent CO2
emissions that are incrementing the effects of C lim ate Change . It is stated the in Paris
Climate Change Agreement (Otto, 2016) that if we continue with this pace in terms of
fossil fuel consumption, emissions derived from the buildings sector could represent, by
2050, twice as they do now. Therefore, it becomes urgent to renovat e existing buildi ngs
deeply in order to improve their energy efficiency.

2. Description of the model
2 . 1 G e n e r a l D e s c r i p t i o n
The building subject of simulation made on ESP -r is in Chicago . It consists of two rooms ,
which names are reception and office , covered by a roof . It represents a typical medical
practice. We mainly focus on the reception zone when undergoing the comfort research.
The façade where the reception window is located is oriented southern (tow ards the
equator) . Reception has a surface area of 48 m2 (obtained by multiplying the difference
on x -y cartesian coordinates provided by ESP -r) and its window 7,5 m 2 (obtained by
Figure 1: Medical Practice Building

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multiplying the difference on x -z coordinates) . Figure 1 provides the design of the
building.

2. 2 T h e r m o p h y s i c a l c h a n g e s
The following change s are made to run comfort simulations : activation of the cooling
system (the initial design does not include it), halve the size of the reception window , set
a HVAC system and finally change the absorptivity and emissivity of the southern wall .
Comfort parameters are analyzed then in comparison to the initial design provided by
the database . Moreover, one more simulation i s done to calculate how much energy can
ten PVs expo rt to the grid and how much is lost by the inverter.

3. Numerical experiments performed
The simulations undertaken to analyze the thermal comfort on the medical practice are
the following:
1. One winter simulation covering a week of February for each thermophys ical
change (and for the initial design too ). This simulation also considers a heating
system activated to provide warmth to the offices. The heating load, PMV and
PPC comfort parameters and the energy delivered are calculated through this
simulation.
2. One summer simulation covering an entire week of July for each thermophysical
change . This simulation also considers the cooling system disactivated for the
initial design. The cooling load, PMV and PPC comfort parameters and the
energy delivered are calculate d through this simulation.
3. Another yearly simulation is carried out in what 10 PVs panels are incorporated
on to the south facing part of the roof , to get the year generation of them and the
losses in the inverter. Note: this simulation has been done in a colleague laptop
as my windows version could not match the materials needed to the roof.
4. Results and discussion
All graphs shown in this section have b een created with the ESPr resul ts analysis tool.
Th is document shows those that the author has considered as most important.

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Figure 2: Heating load obtained during a w inter week of the initial design

Figure 3: Co oling load obtained du ring a summe r week. Initial desig n does not include co oling
system

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Figure 4: PM V values of the initial design , winter simulation

Figure 5: PMV va lues of the initial design, summer simulation

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Figure 6: PMV va lues, summer simulation. 5000 W of coo ing system with 25ºC of set point

Figure 7: PMV values, summer simulation. Hal f size window and 5000 W of c oo ing system with
25ºC of set point

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Figure 8: PMV values, summer simulation. 1 a c/h infilt ration f rom 9:00 to 18: 00 during weekdays
and 5000 W of cooling system with 25ºC of set point

Figu re 2 and Figure 3 pro vide the heating load and co oling load through a winter and a
summer resp ec tively. On the one han d, heating load follows a sharply t endency which
1kW pics m atch with the working hours . The total heating delivered value is 46 kWh . On
the other hand, it is understandable that if there is no cooling system activated , the
Figure 9: Generation of 10 PVs and Transsmission to the grid, year simulation

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cooling load is ze ro. PMV winter and summer values (Figures 4 ,5) indicates a bad
comfort according t o ASHRA E. W ithout cooling system, PMV reception in summer
achie ves a v alue of 5, ex tremely hot . For this reason, changes are required . First of them
is shown in Figure 6. Applying 5000 W of cooling system with a set point of 25ºC red uce
PMV value in the reception in summer from 5 to an average of 2,5 . However, the
ext remely unpleasant pics still ap pear. The energy delivered for cooling in this case is
140 kWh. Hal ving the window size eliminate s the sharp p eak s of PMV summer values .
Values f luctuate betw een 1 and 3 but any sudden increase or decrease appears. This is
mainly because le ss solar ra diation ent ers during daylight hours. However, the cooling
capacity applied seem s to be not enough to maintain a good degree of comfor t even
though the windo w is reduced. The energy delivered for cooling in this particular study
is 110 kWh. A further stu dy with a lower set point and t hat si ze of the window would
probably get better results. Figure 8 shows the case of ap plying an infiltration rate of 3
AC/h for the r eception during w orking hours f rom Monday to Friday. Again, the PMV
value got for summer in no t acceptable , averaging a v alue of 2,3 approximately for the
reception. Pro bably the best results would ha ve been obtained by mergin g the three
changes just explained. Another study has been c arried out by chan ging the absorptivity
to 0,9 and the emissivity to 0,1 of the reception south wall. It can be deduced that
increasing absorptivity produce more substantial effects than decreasing the emissivity
because a value of 144,5 kWh has been o btained for the energy deliver ed for cooling in
summer . Lately, t en PV panels ha ve been installed on the south facing part of the roof.
The average generation value is ap proximately of 1 kW while the tra nsmission to the grid
is 700 W ; so, 300 W are lost in the inverter .
The refore, advanced improvements are required to improve the comfort of this medical
practice. Going to the literature, (Balaras, 1996) investigates the role of thermal mass for
red ucing cooling demand while (Venkiteswaran, Liman and Alkaff, 2017) studi es the
case s of wall insulation by polystyrene, single low -emissivity window glazing and white
painted roo f for reducing cooling demand and improving thermal c omfort.

5. Conclusions
1. Without cooling system, it is not possible to stay in the reception due to the
extremely ho t situation .
2. A 5000 W cooling capacity with an entering set point of 25ºC improves the
comfo rt but it is still unpleasant . Re ducing the set point temperature would
improve the com fort but it would increase the cooling load.

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3. Smaller windows reduce the cooling requirement in summer.
4. Increas ed absorptivity make s more difficult the heat to escape.
5. Losses in inverter in form of heat are directly related to their qu ality and price. It
is preferable spend more mone y initially in a good inverter than having big losses
each day.
6. References
Balaras, C. A. (1996) ‘The role of thermal mass on the cooling load of buildings. An
overview of computational methods ‘, Energy and Buildings , 24(1), pp. 1 –10. doi:
10.1016/0378 -7788(95)00956 -6.
International Energy Agency (2013) ‘Transition to Sustainable Buildings ‘, Iea.Org , p. 290.
doi: 10.1787/9789264202955 -en.
Otto, M. (2016) ‘What the Paris Climate Agreement means for the Building Sector Critical
to realizing global objectives: Combating Climate Change Sustainable Development
Housing and Urbanization Disaster Risk Reduction ‘, (September). Available at:
http://www.swisscontact.org/fileadmin/user_upload/COUNTRIES/Peru/Documents/Con
tent/Building_Sector_Paris_Agreement_ -_IGBC.pdf.
Venkiteswaran, V. K., Liman, J. and Alkaff, S. A. ( 2017) ‘Comparative Study of Passive
Methods for Reducing Cooling Load ‘, Energy Procedia . Elsevier B.V., 142, pp. 2689 –
2697. doi: 10.1016/j.egypro.2017.12.212.
Zhao, H. X. and Magoul ès, F. (2012) ‘A review on the prediction of building energy
consumption ‘, Renewable and Sustainable Energy Reviews . Elsevier Ltd, 16(6), pp.
3586 –3592. doi: 10.1016/j.rser.2012.02.049.