natural ventilation strategies for shopping malls retrofit: a case

UNIVERSITA’ DEGLI STUDI DI TRENTO

Dipartimento di IngegneriaCorso di Laurea Magistrale in Ingegneria per l’Ambiente e il Territorio

Natural Ventilation Strategies for

Shopping Malls Retrofit : A Case Study

Relatore LaureandoProf. Paolo Baggio Giuseppe Gentile

CorrelatoriDott. Ing. Annamaria BelleriDott. Ing. Roberto Lollini

Anno Accademico 2013 - 2014

C O N T E N T S

1 energy consumption in shopping malls 1

1.1 Consumption Data Analysis 1

1.2 Retrofit approach 6

1.3 Possible benefits 8

1.4 Research programme 8

1.4.1 Framework Programme 7: CommONEnergy 8

1.4.2 Annex 62 10

2 ventilative cooling strategies 12

2.1 Air conditioning systems 14

2.1.1 Central 14

2.1.2 Packaged 15

2.1.3 Individual Room Air Conditioning 16

2.2 Mechanical Ventilation 16

2.3 Hybrid Ventilation 20

2.4 Natural Ventilation Strategies 21

2.4.1 Stack based natural ventilation 21

2.4.2 Wind based ventilation 25

2.4.3 Night Ventilation 30

2.4.4 Ground Ventilation 30

2.4.5 Evaporative Cooling 31

2.4.6 Limitations 32

3 retrofitting ex officine gugliemetti 34

3.1 Weather Data 34

3.2 Climate Potential Analysis 40

3.3 The project 44

3.4 Solutions implemented 50

3.4.1 Stack Effect on Western Atrium 51

3.4.2 Ground Coupled Ventilation on Eastern Hall-way 51

3.5 Building the model 53

3.5.1 Internal Gains 61

3.5.2 Ventilation and Infiltration 70

3.5.3 Constructing the network 70

3.5.4 Control algorithms 73

3.6 TRNSys and TRNFlow 74

4 results and discussion 75

4.1 Outcomes 75

4.1.1 Temperatures decrease 75

4.1.2 Air Changes 83

4.1.3 Energy Balance 94

4.1.4 Adaptive Comfort Analysis 97

4.2 Energy Consumption 105

iii

4.3 Discuss on simulations results 106

4.4 Model Limitations 107

4.4.1 Thermal zoning 107

4.4.2 Mechanical Ventilation 107

4.4.3 Weather Data 108

5 summary 109

iv

A B S T R A C T

More than 30 % of primary energy consumption in EU buildings isused for services sector, and up to half of the energy used by a wellinsulated building can be spent on cooling. For the specific buildingtypology of shopping malls, 21% of total energy demand is spent forcooling and 12% for ventilation purposes (Harper et al., 2007).

Last decades’ increased concern over the adverse environmentalimpact of energy use and the rising price of fossil fuels has encour-aged the design and construction of energy efficient buildings. Nat-ural ventilation has therefore become an energy efficient and envi-ronmentally friendly option to overtake full air conditioned system,reducing cooling load and providing year round comfort with gooduser control and negligible maintenance.

With this work we study and analyse the possibilities to exploitventilative cooling potential in high energy consuming structures asshopping malls, using natural ventilation strategies to contribute, whenincluded in specific solution sets, moving them from consumerism toleading examples for energy conservation. The aim is to provide abetter understanding of limitations and potential of ventilative cool-ing solutions, looking for availability of natural driving forces on con-struction site and trying to overcome pollution, noise levels and vi-sual comfort problems. The analysed structure is the Genoa’s demo-case of CommONEnergy, an European project whose vision is to shiftretrofit intervention on shopping malls from single-action to a sys-temic approach involving innovative methods and tools. This casestudy will be evaluated by means of building modelling and dynamicsimulations in TRNsys coupled with TRNflow, developing differentsolutions related to lowering cooling need, overheating and mechan-ical ventilation loads. Outcomes from the proposed solution will becompared with the baseline building submitted by architects to assesspotential savings analysis as well as possible comfort improvement.

Results will point out how natural ventilation efficiency is strictlyrelated with building geometry and indoor air quality restraints: park-ing lots use of upper plan roof and underground floor limits place-ment and dimension of inlet vents, while aesthetic needs exclude thepossibility to use wind-catcher to improve ventilation effect. Adap-tive comfort analysis will show that occupied hours in category I canbe extended by up 23 % in warmer months of the year if a naturalventilation solution is implemented, leading to a possible wideningof set-points temperatures range with consequent better results in en-ergy savings. In western glazed atrium, where stack effect ventilationis well exploitable, overheating degree hours from April to October

vii

can be decreased by 27%, while air changes provided by natural ven-tilation reach 23% of total occupied hours and 83 % of total closinghours in the same time period. Outcomes would be more reliable ifwind data from a local weather station would be adopted instead ofthe one located in Genoa’s airport (far 10 km south-west from build-ing site), highlighting specific wind pattern and representing a morerealistic behaviour of the airflow network.

viii

1 E N E R GY C O N S U M P T I O N I NS H O P P I N G M A L L S

1.1 consumption data analysis

The present study is focused on a peculiar building typology, so inthis chapter we review consumption data for shopping malls to pointout the share of cooling and ventilation energy consumption in retailbuildings.As displayed in fig, 1.1 ,heating and ventilation plus air condition-ing needs shares 1/3 of total energy demand pattern of commercialbuildings.

Focusing on the European Union and according to Eurostat database,energy demand in the whole EU-28+Norway residential and servicesector in 2012 was 5165 TWh.The residential sectors share of the finalenergy demand is 66% while service sector’s share is 34%. The divi-sion varies from country to country, as shown in figure 1.2. In Italy,Cyprus, Malta, Luxembourg and Netherlands the energy use in theservice sector is above 40%.

In the US market the top three end uses in commercial sector arelighting, space heating and cooling, as shown in figure 1.3.

Sustainability reports from shopping centre owners (Steen & Strom(2012), Unibail-Rodamco (2013), Intu Group (2013), Britishland (2014)and IGD (2014)) show the share of the average energy consumptionin food retailers as follows:

• 50% for food conservation by refrigeration

• 25% for lighting

• 20% for heating, ventilation and air conditioning (HVAC)

• 5% for electric appliances and others internal processes

1

2 energy consumption in shopping malls

Water heating 12%

Lighting 26%

Other 22%

Heating and ventilation

12%

Appliances 7%

AC 21%

Commercial

Figure 1.1: Energy demand pattern for commercial building(source: State of the Environment Report 2007, en-vcomm.act.gov.au)

As underlined by these studies, a smart designed cooling plantsand ventilation system could lead in the best scenario to about 20%energy savings of the total amount of energy needed in a commercialbuilding. More recent reports (Schönberger et al., 2013) show thatthis fraction can vary from one retailer type to another (see fig. 1.4).

The same authors estimated the specific energy use of Europeanfood stores, discovering that the total energy consumption ranges be-tween 500 and 1000 kWh/m2yr. Food stores specific energy use isup to five times higher compared to residential and office buildings.Further, Schönberger et al. (2013) report an average energy consump-tion of 270 kWh/m2yr for non-food stores smaller than 300 m2 and200 kWh/m2yr for stores larger than 300 m2 . Another study [7] ledby technical teams working on CommONEnergy project (see 1.4.1),based on several sustainability reports from real estate companiesand their shopping centres, analysed 132 structures and their energyconsumption per square meter, the results display how the specificenergy need for shops area are double than those for common area(see tab. 1.1). This happens because shops tenants regulates their ownset-points for final regulation of internal temperatures, narrowing therange adopted for common area and leading to higher consumptionof final energy.

1.1 consumption data analysis 3

0% 20% 40% 60% 80% 100%

AustriaBelgiumBulgaria

CyprusCzech Rep.

DenmarkEstoniaFinlandFrance

GermanyGreece

HungaryIreland

ItalyLatvia

LithuaniaLuxembourg

MaltaNetherlands

PolandPortugalRomaniaSlovakiaSlovenia

SpainSweden

UKCroatia

Residential Service

Figure 1.2: Breakdown of building energy use by sector in EU-28+Norway in residential building sector and service building;source:Entranze 2013

Specific energy Specific energy

consumption of shops consumption of common areas

kWh/m2yr kWh/m2yr

small shopping centre 280 117

medium shopping centre 263 117

large shopping centre 248 117

very large shopping centre 228 117

TOT 261 117

Table 1.1: Specific Energy Consumption for shops and common areas in EUshopping malls. source: CommONEnergy project

The constructive configuration, which as well influences the energyconsumption, is mainly given by the final use of the building (e.g


Figure 1.3: U.S. commercial sector energy consumption by end use - datafrom Berkeley National Laboratory, 2012

shopping malls are characterised by big open spaces and large atria).This configuration may include aspects such as:

. Building envelope: geometry, construction material and insula-tion

. Building equipment and lighting

. Technologies for heating, ventilation and air conditioning

Larger amount of energy consumption can likely be found in thosecountries of EU28 with the highest gross leasable area (GLA index1).Therefore UK, Germany, Spain, France and Italy have in descend-ing order the larger energy consumption and account for 19% of totalconsumption of EU28 plus Norway and Switzerland ([7]).

1 Area for tenant occupancy and for which tenants pay rent, thus the area that pro-duces income for the property owner

1.1 consumption data analysis 5

!ht

Figure 1.4: Share of total energy demand in retail building. source: retailforum for sustainability, 2008

Figure 1.5: Total final energy consumption in EU shopping centre buildings,source: deliverable 2.1, CommONEnergy, 2013


1.2 retrofit approach

A common approach to assure thermal comfort in buildings duringthe summer season relies on air conditioning. This kind of strategycan be very energy intensive and can lead to high CO2 emission andheat from the capacitors ( intensifying heat island effect in metropoli-tan areas). Nowadays the new sensitiveness for environmental ori-ented design and energy efficiency in architecture has fostered thedevelopment of strategies to supply internal comfort exploiting natu-ral sources such as wind and sun instead of relying on traditional me-chanical thermal plants. During the design process of a new buildingor for the energy retrofit of an existing one, a planner can minimizethe need of HVAC systems controlling three main areas:

solar gains Controlling solar gains is not only about managing theorientation of the building in the early design process but in-volves the design of smart overhang and shading devices tominimize solar gains during the cooling season but and at thesame time to provide the right amount of daylight to reduce ar-tificial light demand.Furthermore, green roof or cool roof strate-gies could be implemented to promote evaporative cooling andenhance the albedo of flat surfaces.

thermal mass Thermal mass and insulating external surfaces canprovide a perimetric external thermal tank to stabilize daytimetemperatures and peak shave their highest value. Ground orwater sources can be also suited as thermal storage system insome cases.

natural ventilation Choosing the right shape, orientation, sizeof window and wisely exploiting thermal gradient inside thezones can lead to air movement which can partially or totallyassure the required air change rates to maintain indoor air qual-ity. On the other hand a smart natural air flowing can helpto reduce overheating and dissipate hotness inside the massivelayers of the envelope during the coolest hours of the night.

Note that all of the above mentioned strategies can be implementedin a retrofit process of an existing building, but in most cases thermalbehaviour of the envelope can be controlled modifying layers andglazed surfaces can be substituted with more efficient ones and pro-vided with control algorithms to maximize the benefits of naturalventilation strategies. A preparatory assessment of what strategieswould work best is necessary to design a targeted refurbishment andavoid unnecessary approach.

For this reason a special task has been developed within the Com-mONEnergy project (see 1.4.1) to detect systemic inefficiencies asso-ciated with functions, logistics,management, safety and facilities in

1.2 retrofit approach 7

EU shopping malls. Three different types of questionnaires were sub-mitted to owners, tenants and customers to collect technical data andexplore the influence of energy saving aspects on customers’ choices.For further details regarding the structure of questionnaires see [18].The main output of this analysis is a list of system inefficiencies inshopping centres, meaning improper design, operation and mainte-nance of the various technical arrangement of the building. Descend-ing Retrofitting Drivers (RD) were then defined to assess energy sav-ing potential, addressing key components and technologies that canbe implemented in existing architecture systems and ignoring ineffec-tive strategies. For the HVAC fields, results were merged with previ-ous reports ([1], [3]) on system deficit in retail shop and commercialbuilding to find some typical issues retrieved below:

Wrong HVAC units usually oversized and with no maintenancecosts and noise level provided

No outdoor air economizer built in air handling units to pro-vide free cooling and ventilation

Simple thermostats with manual control can be regulated tovery high or low set-points by staff

No schedule to shut down HVAC system or reduce its loadwhen the stores are closed

Constant air volume (CAV) systems cannot adjust air changesto different operating time of the day

Lack of bioclimatic solution to extend comfort band and mini-mize load exploiting natural sources

Focusing on cooling and ventilation topics, specific inefficienciesregard mainly energy losses in ventilation, absence of free coolingstrategies and unmodulated airflow for different periods of the daywhich lead to energy losses for higher than necessary air distributionrates and consequently demand for cooling or heating.


1.3 possible benefits

Renovation of commercial buildings through low energy HVACand smart solution for energy efficiency can lead to:

. Decrease cooling and heating demand, and their energy costaftermath

. Reduce emission of carbon dioxide (CO2) as a consequence ofless primary energy consumption

. Protect the environment and preserve natural resources

. Improve satisfaction of users and ensure efficient management

For the specific case of retrofitting stock building, according toMcGraw-Hill Construction [8] the operating costs are decreased upto 10% while the CIBSE manual (CIBSE, AM10:2005) outlines capitalcost savings of the order of 15% for non-air conditioned buildingscompared to the naturally ventilated. US Environmental ProtectionAgency found that energy consumption can be reduced by 30% withthe endorsement of sustainable strategies, and in particular the an-nual electricity usage in a shopping centre is known to be up to 50%less where natural ventilation is employed over mechanical ventila-tion (BCSC,2012)

1.4 research programme

Latter energy efficiency legislation has been focused on transform-ing existing buildings into energy conservative structures, in this sec-tion we discuss some of the most recent programme and project re-lated to natural ventilation strategies and retrofit for efficiency pur-poses.

1.4.1 Framework Programme 7: CommONEnergy

CommONEnergy is an European financed project whose aim is totransform shopping malls from high energy consumptive structureto beacon of efficiency and sustainability, through the developmentof innovative technologies and using an integrated design process.The project involves 23 partner from different countries and with dif-ferent roles, varying from researcher institution and consultants toenterprises owner. To make the approach as holistic as possible eachone of the partner will be involved from early design stage to thebuilding process, matching ideas and coordinating efforts to reach aSystemic Retrofitting Approach (SRA) focused on:

• Multifunctional façade modules

1.4 research programme 9

• Natural sources exploitation (daylighting and ventilation)

• Integration of active components

• Energy modelling and retrofit approach for targeted building

• Intelligent Building Energy Management (iBEMS)

Figure 1.6: SRA Approach source: CommONEnergy presentation

These targets will be addressed with integrated design processsuited specially to retrofit shopping malls, using integrative mod-elling environment to develop solution-sets for minimizing energydemands and increasing sustainability and energy efficiency. The fi-nal aim is to provide comfort and healthy conditions for visitor whilereducing energy demand up to 75% and using natural sources andpassive strategies.

Three demo-cases will be evaluated throughout the 48 months du-ration of the project, each one representing typical climate conditions,architectural category and building technologies. Those demo casesare:

valladolid (spain) Deep retrofitting Mercado del Val, preserving his-torical heritage and focusing on façade modules, refrigerationto cabinets and iBEMS

trondheim (norway) Light retrofitting of City Syd focusing on light-ing, iBEMS and energy storage

genoa (italy) Reconversion of Officine Guglielmetti and Coop foodstore focusing on natural ventilation, lighting, green solutions,HVAC, iBEMS

In this work we assess the potential of ventilative cooling strategiesfor the Genoa demo-case, modelling the baseline in the beginningand then simulating with TRNflow a possible strategy to lower cool-ing demand with the aid of a controlled air-streaming network. Asone of the goal of CommONEnergy is to conduce a replication potential


Figure 1.7: CommONEnergy project’s building distribution: demo-cases inred, reference buildings in yellow

analysis, the case study will be independently evaluated thou main-taining flexibility to apply the same procedure in different social, andeconomical and climatic condition.

1.4.2 Annex 62

Ventilative Cooling is application of ventilation flow rates to reducethe cooling loads in buildings. This strategy utilizes the cooling andthermal perception potential of outdoor air.In November 2013 the Executive Committee of International EnergyAgency approved a four year program on ventilative cooling namedAnnex 62, to develop strategies to reduce cooling in building via natu-ral, mechanical or hybrid ventilation. The project raised from the fre-quently noticed overheat problem in highly insulated building, whichcan be partially solved with the aid of outdoor air, to act as reducerof cooling loads, both in summer and in mid-season periods. The"cooling challenges" could therefore be a boost to study new solutionto the overheating problem and could moreover expand the comfortzone of users (see reports on adaptive comfort models [10], [16]). Thisannex will focus on:

. Develop methods to predict and reduce the overheat phenom-ena and minimize cooling needs

1.4 research programme 11

. Test and discover old and new energy efficient ventilative cool-ing solutions

. Give flexible guidelines to integrate ventilative cooling in build-ing, suggesting key factor and control strategies for differentclimatic conditions

. Demonstrate the reliability of results through evaluation of welldocumented case studies

2 V E N T I L AT I V E C O O L I N GS T R AT E G I E S

As seen in the previous chapter, HVAC plants account for highenergy load in commercial structure but they are also crucial to thecomfort satisfaction of user and productivity of workers. In shop-ping malls HVAC systems are regulated in an integrated way, so thatboth common areas and tenants are ventilated and air conditionedby the same plant units; but different tenants means different tem-perature set-points and different air change per hour because of thevolumes and final uses, so it is crucial to design a flexible distribu-tion system to meet capacity under time and space varying condition(note that in commercial building the need for air conditioning andventilation varies with opening and closing hours).Whether passivedesign strategies are implemented or not, it is therefore important tobuild an intelligent building control system (iBEMS) to monitor andmanage the equipments for heating, lighting, cooling and ventilation.

qtot = n · qper +A · qA (2.1)

where:

• n is the number of people predicted by the occupancy profile

• A is the floor area of the environment

• qper is the specific air change in l/sec · pers

• qA is the area specific air change in l/sec ·m2

category Airflow per person[l/s · pers] Airflow for building

emissions pollutions

[l/s ·m2]

very low low noneI 10 0.5 1 2

II 7 0.35 0.7 1.4III 4 0.2 0.4 0.8

Table 2.1: UNI EN 15251 : Recommended ventilation rates for non-residential buildings for three categories of dissatisfied percent-age (I = 15% ; II=20%; III= 25% )

12

ventilative cooling strategies 13

category Airflow per person[l/s · pers] Air speed for

cooling [m/s]

Warehouse 6.5 0.05÷ 0.2Barbers shops 14 0.05÷ 0.2

Shops 11.5 0.05÷ 0.2Foodstores 9 0.05÷ 0.2Restaurants 10 0.1÷ 0.2

Table 2.2: UNI 10339: recommended air changes and air speeds for coolingcommercial building

Figure 2.1: Recommended airchanges to meet comfort and healthy condi-tion.source: AIVC, Guide to energy efficient ventilation

Measured occupation data from existing similar buildings are morereliable than literature ones, which in most cases refers to occupantload (also known as exit population1) and are useful for exit emergen-cies design and fire code comply, but could lead to oversizing HVACequipment if adopted for ventilation design. In any case, ventilationshould be provided only when time schedules foresee a zone to beoccupied, otherwise only minimum (required by regulations) flow ofair changes should be provided.

1 Number of persons for which a building or part there of is designed

14 ventilative cooling strategies

2.1 air conditioning systems

Shopping malls HVAC system types can be divided in three maincategories [11]: central, packaged, and individual AC.

2.1.1 Central

A central HVAC system uses chilled water to cool air, while heatingis generated in a boiler and then distributed with steam or hot waterpiping wich ends in radiators, fan-coil or baseboard heaters. The sys-tem is broken down into three major subsystems: the air-handlingunit, the chilled water plant, and the boiler plant. Air handling unit

Figure 2.2: Scheme of a HVAC central system. source [11]

condition and supplies air for the different rooms of the building, fil-tering and conditioning outside air depending on outdoor conditions.In case of variable air volume system (VAV) the air flowing into con-ditioned space can be controlled via a terminal valve box with a reheatcoil to higher the temperature if shops tenants find it too low for theircomfort. On the other hand, constant air volume systems (CAV) donot allow to reduce inlet air flow and rely on reheat coils to control thedelivered cooling temperature. The chiller water system is basically avapour compression cooling system with an evaporator section thatsupplies chilled water to the coil units of the air treatment batteries,and a condenser who rejects heat to condenser water which is then

2.1 air conditioning systems 15

circulated to a cooling tower to exchange heat with the environment.The heating water system in a central HVAC is composed by a boilerand a pump to circulate hot heating water (or steam) in preheatingcoils, local radiators and reheat coils for the final control of the airtemperature from the occupants.

2.1.2 Packaged

This system do not use water as intermediate cooling medium butsupplying air is cooled directly with an exchange process in the evap-orator coil. For the heating part, this systems are provided with a gasfurnace or an electric resistive coil, or sometimes they work as heatpumps so that the condenser expels heat into the building rather thanon the outside.

Figure 2.3: Scheme of a HVAC packaged system. source [11]

Figure 2.3 shows how rooftops unit can directly use external airfor cooling purposes, moving it through a filter and then throughthe evaporator coil to be conditioned. The distribution system startswith a big indoor blower connected to the pipework that ends insupply diffusers. The cycle is the same vapour compression cycleseen for the central systems in the previous section. In split solutions,the condensing unit is placed externally on the rooftop while theevaporating unit is located near the rooms to be conditioned, and thetwo sides are connected via a ductwork where the refrigerant flows.


2.1.3 Individual Room Air Conditioning

Sometimes temperatures in commercial structures are controlledvia AC window units or package terminal heat conditioners (PTAC),treating every room with its own units as done in residential build-ings. This solution allows more flexibility to control indoor air qual-ity but needs more mantainance and it is more expensive due to theredundancy of the equipment. As pointed out by Woods and Fitzger-ald [9], “open-door” policy observed by retail stores during shoppinghours, in a mall where temperature control in common areas is morerelaxed than in shops , will heat the central spaces in cold seasonswhile cool the same spaces during summer.

2.2 mechanical ventilation

The primary role of ventilation is to provide fresh air for all metabolicneeds and control moisture level in enclosed spaces, but in some caseit is used to cut polluting concentration (e.g for cooking or smokingareas) and to fight overheating problems. A low indoor air qualityinfluence both comfort perception and health: latter studies focusedon sick building syndrome point out relationship between pollutantsconcentration persistence and short term illness symptoms duringperiods of occupancy as well as long term ill health effects. Anotheraspect that should be considered when designing a ventilation sys-tem is energy saving, which connect this topic strictly together withair tightness, partitioning, mantainance and control, so that the de-sign process becomes a multi-criteria analysis between a wide rangeof parameters (see. Chap 1 on integrated design process). Duringthe early design stage of a ventilation plant, at least these influencefactors should be considered :

• Building type and architecture

• Climate conditions

• Sources of pollutants, noises and odours

• Internal Environmental Quality (IEQ)

• Payback time

A traditional way to provide ventilation is by using a system of fanand duct to circulate air into indoor environment. These systems areusually structured by two main parts:

INPUT: FRESH AIR PART where air is taken from the outside, pro-cessed through layers of filters and usually warmed in heatexchangers prior to be delivered into the indoor environment.

2.2 mechanical ventilation 17

This process should not be confused with air conditioning, whichis a more complicated operation to cool air through a refrigera-tion cycle.

OUTPUT: EXHAUST AIR PART where exhaust air is removed fromthe inside of the building and evacuated on the outside. In mostcases during the itinerary from inside to outside the air is forcedinside a heat recovery system to warm the incoming airflow.

A distribution system can then rely on three main configuration (seelecture [12]):

mechanical exhaust ventilation (mev): continually extracts ex-haust air with a fan system while inlet external air is providedby windows. Extraction strategy can be single-point if it in-volves a fan for every extraction room or multi-point if a singleremote is used to collect exhaust air. Deriving small negativepressure in building prevents condensation and mould growth,while it can be a problem for helping the infiltration of exte-rior pollutants. Intermittent exhaust ventilation can be imple-mented to control air inlet when outdoor quality is poor, butif the fans run only part time at a higher rate the system mustbe bigger than when it are designed to run continually on lowmode (Sherman, 2004). Furthermore, the occupants who con-trol ventilation must be aware when it should be provided, andif the system is faulty (i.e. too noisy) they could choose to turnit permanently off with consequent under-ventilation issues. Tosolve this problem a timer can be installed to run the systemwhenever needed.

mechanical supply ventilation, also known as positive input ven-tilation (PIV) or supply only ventilation (SOV), consists in a fanto supply air to inside spaces and ventilation openings in theexternal envelope to allow air flow out of the building. Thepositive deriving pressure allows exterior contaminates to stayoutside, and external air can be supplied in a continuous orintermittent way like in MEV.

balance exhaust and supply uses a supply fan and an exhaustfan to provide indoor air exchange. It is the most common strat-egy for a shopping malls, and the name "balanced" derives fromthe fact that if inlet and outlet systems move the same amountof volume, the internal pressure is almost neutral. This strat-egy can be improved with a heat exchanger to pre-conditionsupplied air, while a time speeder switch can be provided to fitair change rates with the schedule of occupancy. The systemcan be centralized if one big single unit is assigned to draw in-side, filter and pre-condition outside air and then deliver it tothe rooms. Otherwise the system is called decentralized and


every zone of the building has its dedicated ventilation system(inlet and outlet) with heat recovery unit. A centralized sys-tem can be designed with large heat recovery unit, such as heatwheels where the heat is stored inside a honeycomb rotatingmesh, or Kantherm systems where two stationary heat batteriesacts as complement of the other, so that when one battery isloading because of the exhaust air streaming on it the other isreleasing heat, and their role reverse every 50 second via a valvewhich alternates air flowing direction.

The energy consumption of this model is strictly related with en-ergy losses inside the pipes for the distribution process and energyload from the fans moving the air. Since high airtight standards arenow required in nZEB (infiltration rate should be reduced to less than5 m3/hr ·m2 ), almost all the exhausted air passes through the out-put system so that the heat recovery process can be highly energyefficient.Furthermore, newest heat recovery units are able to act as thermaltank to save heat that is not required immediately to pre-warm out-side air when needed. Finally, mechanical ventilation can be used toboost passive strategies such as night cooling, even though heat recov-ery is generally incompatible with wholly natural ventilation systemsdue to the high resistances encountered through the pipes track andinside heating exchange units.

2.2 mechanical ventilation 19

Figure 2.4: Different types of heat exchangers for mechanical ventilationsystems


2.3 hybrid ventilation

They hybrid ventilation system is a combination between mechani-cal and natural ventilation strategies, so that when outdoor tempera-tures lay inside the comfort band the air changes and climate controlcan be partially granted with external air, used as an aid for the au-tomated mechanical ventilation system.The interaction between thetwo systems can be designed in different operating way:

complementary design if both systems operate together, jointlyor separately controlled with a time schedule pattern. This so-lution offer great flexibility to the system because of the oppor-tunity to rely on pre thermal processing the air in hotter andcolder months of the year while relying directly on outside airtemperature during warmth seasons.

zoning design can be useful if significant ∆t are expected insidethe building (i.e. due to different internal load or gains); in thiscase mechanical ventilation can be provided for the zone withhighest cooling loads and where the heat could be extractedand treated for other purposes, while natural ventilation can beimplemented where it would work better because of the geom-etry of the environment, prevailing winds or low overheatingproblems.

contingency design merges both natural and mechanical ventila-tion in each part of the building, so that each system can beused as a backup for the other in case of breakdown.

Even if an hybrid mode system provides more flexible and reliablesolution to the ventilation problem, reducing cold draft and detach-ing the efficiency from weather condition, it is decisive to provide asmart control system to monitor inside and outside climate parame-ters (temperatures, wind) and therefore regulate the right fraction ofnatural mode over mechanical mode, setting the right speed of fansand opening factor of windows.

2.4 natural ventilation strategies 21

2.4 natural ventilation strategies

Natural (or passive) ventilation is a way to provide ventilation toa building using outside air, without using powered mechanical sys-tem. Whether this strategy has lower cost for both running and main-tenance aspects, in cases where high air changes are needed to main-tain temperatures and healthy conditions, passive ventilation may notbe enough and it should be coupled with an active system. In thiscase, an economical balance should be made between the implement-ing cost and operative efficiency of natural ventilation process (interms of capital savings) and the possibility to reduce HVAC systemminimizing load and right-fitting the size of active plants. Anyway,the CO2 reduction contribution from a passive system involving onlynatural sources could never be reached by electrical plant (even ifoptimized and well dimensioned) and natural ventilation strategiesallow the users to have an immediate control over their environmentthat could never be granted with mechanical systems (see [16] foradaptive comfort analysis). According to Aynsley [5] , the reliabilityof a natural ventilation system lies on two test:

summer behaviour : during the hottest days of the year the maindriver of ventilation process is the wind, so if external windpressure is not strong enough the system could stop function-ing properly. Furthermore, if outside air is widely off set pointcondition the incoming flow should be shut off and air changesshould be provided in another way such as counting on bigvolumes offered by high ceilings or atria to buffer the inactiveventilation period.

winter behaviour : when the outside air is cold natural ventilationcan be responsible for excessive heat loss and cold draughts, soa detailed analysis should be led to avoid energy wasting andcomfort decrease.

Internal temperature analysis are therefore crucial to understandwhether natural ventilation is enough and when vice versa mechan-ical power must be provided in order to satisfy comfort. Par. 2.4.1,2.4.2 describes the principles of natural ventilation phenomena.

2.4.1 Stack based natural ventilation

Natural ventilation is mainly driven by two different effect: stackand wind. The stack effect is due to temperature difference, whichin compressible fluids becomes a density difference and then a buoy-ancy force. Considering a closed environment, its internal pressurecan be described with the well known Stevin’s formula:

P = P0 − ρ0 · g ·H


Where:

• P is the external or internal pressure [Pa]

• P0 is the pressure at a reference level [Pa]

• ρ0 is the external or internal air density at a reference level[kg/m3]

• g is gravitational acceleration [m/s2]

• H is height above the reference level [m]

The in/out pressure difference across a window located at H meterson the façade will be:

∆p = Pext,0 − Pint,0 − [(ρext − ρint) · g ·H]

then, considering air regulated by perfect gas laws and small tem-perature differences between inside and outside, density differencecan be related with temperature difference through the followingequation:

ρext − ρintρint

=Tint − TextText

obtaining:

∆P = ρi · g ·Tint − TextText

· (H0 −H)

In which H0 is the height of the neutral plan of the building, wherethe air won’t enter nor exit because ∆p = 0. Fixing the height of theopening and increasing the ∆T it is then possible to see how the effectvaries its strength (see fig 2.5)

Figure 2.5: Inside/outside pressure difference for stack driven ventilationeffect. source: Lion, 2012


Fig. 2.6 explains graphically what happens inside and outside thebuilding in terms of pressure difference, and simply locates neutralpressure level in the middle of the façade because of the symmetry ofthe problem.

Figure 2.6: Stack effect visualization and neutral pressure level position.source: : AM10 Natural Ventilation in Non-Domestic Buildings,CIBS

The neutral pressure level H0 is located near to the biggest opening,as is deducible to see that the bigger the opening is, the easier willbe to make air flow through it. This evidence has and importantresponse for natural ventilation opening design, because - as pointedin fig 2.7:

if the neutral pressure level is placed too low , for exam-ple due to small exhaust air exits recirculation stream can hap-pen in the highest storeys.


if same openings area are used in each storey unbalance inflow streaming can happen with consequent discomfort for theusers

Figure 2.7: Neutral pressure level relation with size and placement offaçade openings. source: : AM10 Natural Ventilation in Non-Domestic Buildings, CIBS


The efficiency of the buoyancy process can be improved by:

• Increasing vertical volume with high ceilings.

• Increasing ∆T between the top and the bottom of the environ-ment

• Reducing airflow resistance, such as obstacles within the air net-work path

• Exploiting Venturi effect to help expelling exhaust air

2.4.2 Wind based ventilation

Air movement around a building is a complex three dimensionalproblem, ruled by an aleatory phenomenon as is the wind. The pres-sure due to wind streaming against a surface is calculated by thefollowing formula:

Pw = Cp ·1

2· ρ · v2ref

where

• Pw is the wind induced pressure [Pa]

• Cp is the pressure coefficient

• ρ is the external air density [kg/m3]

• vref is the wind speed at a reference height [m/s]

Fig. 2.8 explains how the pressure difference varies with the windspeed vref for two pressure coefficient. Note that the relation betweenpressure and temperature in stack driven effect is linear (see fig 2.5),while in wind driven ventilation the pressure follows a power law.

Figure 2.8: Pressure generated by wind for different speeds. source:Lion2012


The obtained value will be an overpressure at the windward sideof the building, and an underpressure at the leeward side and theparallel sides of the building (see Fig.2.9), depending on the Cp coef-ficient.

Figure 2.9: Wind pressure profile on the windward and leeward side of abuilding

The intensity of wind pressure at a certain height H of the buildingdepends on wind profile, which up to a z0 level called roughness lengthis governed by a logarithmic law

v(H) =u∗k· lnH− d

z0

with

• v(H) is the wind speed at a reference height H [m/s]

• u∗ is the friction velocity (see [17]) [m/s]

• k is the Von Karman constant

• d is a displacement height depending on terrain [m/s]

• z0 is roughness length (see fig. 2.11)

As shown in fig.2.10, over the height z0 wind speed is constant andcalled geostrophic speed

Topographic features such as highlands, valley or mountains candevelop local wind acceleration (up to 54 % on windward side of ahill [4]) or deceleration, so in this case it is needed to confront build-ing site datas against those one recorded at the airport to see if mul-tiplying factor should be involved for correction. A common wayto do this is by assuming that a stable atmospheric boundary layeris present between the building site and where the wind station isplaced, accounting terrain differences and height difference with thefollowing formula:


Figure 2.10: Wind pressure profile changing with terrain roughness

vo = vm ·[hbhm

]αstat·[h0hb

]αsituwhere:

. v0 is the desired in-site speed of the wind;

. vm is the speed of the wind at the local meteo station;

. h0 is the height above the ground of the site where wind datais needed;

. hm is the height above the ground of the station measuringwind speed ;

. αstat is a constant depending on terrain configuration at stationsite;

. αsitu is a constant depending on terrain configuration wherewind data is needed;

Optimal wind data should be taken from a local site with topogra-phy configuration similar to that one of the building site. The idealwind pattern would be having light stationary summer breeze to pro-vide fresh air movements and night time cooling, and small or nowind at all during cold days of winter to avoid heat losses and colddraughts.

The other concerning area about which a designer should be care-ful when treating wind data is the effect that shielding objects andbuilding geometry cause on the distribution of air around buildingsurfaces. Accounting right overpressure and underpressure on façade


Figure 2.11: Roughness length for different terrain configurations

and roof elements means calculating the right cp for each wind blow-ing direction. Wind driven strategies can be divided in two maincomplements:

cross ventilation , which exploit both overpressure and under-pressure façade to develop an air stream across the room. Toget a constant airflow ratio and avoid draughts, opening sizesof outlet part should be larger than air inlet area, so that airis gently introduced by the vacuum created in the depressedpart of the façade and is then removed efficiently even if sloweddown by building internal resistances. The dynamic pressureat windward openings in cross-ventilated buildings increases


with the porosity of the building (ratio of area of wall openingsto area of walls), so that when wall openings are about 1/5 ofthe total wall area, the effective pressure difference can be 1.4times the dynamic pressure at eaves level, meaning that windspeed through windows would be higher than local wind speed(Aynsley et al, 1977). With more than 60% of wall opening ,the wind pressure difference between windward and leewardmatches the dynamic pressure at eaves level. Cross ventilationcan be effective in a plan horizontal range not bigger than 5

times the ceiling’s height of the ventilated environment (see fig.2.12 and [19]).

single sided ventilation , is a simple passive cooling strategythat can be achieved by opening windows only in one side ofthe environment. In this case best performances can be obtainedplacing windows at different heights, to induce local recircula-tion in a plan depth up to 2.5 times the height of the ceiling[19].

H

5H

Figure 2.12: Cross ventilation plan efficiency. source [19]

H

2H

Single-sidedFigure 2.13: Single sided ventilation efficiency. source [19]


For both cross and single sided ventilation, the air volume flowinginside a vertical opening on external walls can be calculated as:

Q = Cd ·A ·√ptot − pstat

ρ

with:

• Cd is the coefficient of discharge of the opening (usually 0.61)

• A is the opening area [m2]

• ptot is the total pressure (dynamic+static) across the orifice [Pa]

• pstat is the static pressure measured at the ceiling level [Pa]

• ρ is the air density [ kgm3 ]

According to Heiselberg & Sandberg (2006), the common practiceof using the static pressure data instead of dynamic plus static onesfor calculating airflow through openings can result in underestima-tion by up to 50% if the building is well desgned, while an overes-timation by up 66 % if the building is poorly designed for naturalventilation.

2.4.3 Night Ventilation

In masonry or concrete structure, wherever high thermal mass isused to cut temperature peaks and laminate heat waves, night time’purging’ can be exploited to dissipate the heat stored into the buildingfabric. This technique can ensure a reduction of internal temperaturefor the next day, and in night time unoccupied rooms can be partic-ularly efficient because no restraint on air speed and cold draughtsare involved. Furthermore, the difference between internal and ex-ternal temperatures is greatest during the night, so the stack effectefficiency is maximised with this passive strategy. Night ventilationcan be achieved passively through ventilation from vertical and hor-izontal vents as well as window and doors or by using mechanicalventilation without air conditioning.

2.4.4 Ground Ventilation

Ground coupled air cooling exploit a system similar to heat ex-changer strategy in mechanical ventilation, with the difference thatpre-warming or pre-cooling source is soil and not air. Driver of thisscheme is then the high thermal capacity of the ground, whose effectis to have an almost constant temperature (mean whole year tempera-ture of the site) at 5 meters of depth, so that winter air can be warmedfrom below zero up to 5 °C, while summer hot air can be cooled from28 °C to around 17 °C [14].


Figure 2.14: Soil temperature variation with depth in different months ofthe year. source: dimplex.co.uk

A simple way to implement this practice is to locate air inlets inunderground storey. When the whole building rises above the levelof the ground, groundwork bed can be exploited or concrete passage-ways can be build between foundations, or pipes can be buried inthe ground to help keep high air quality standards from the start tothe end of the heat exchanging process. In this case some mechanicalfans support could be necessary, and the reducing cooling effect dueto continue operation in a small local area of soil should be accounted.Another aspect to focus is potential bacteria growth, so that when airstreams directly on the bed rocks installing air filter would be manda-tory to keep high air quality standards, and mechanical ventilationshould be supplied to keep the air in motion.

2.4.5 Evaporative Cooling

Evaporative cooling uses evaporation as natural exchange processto dissipate heat into the surrounding medium. Hot dry air flowsthrough wet surfaces or thin film cascade of cold water, and is cooledby the loss of latent heat of evaporation. The same process occurswith plants’ transpiration cycle and evaporation of moisture contentin the first layer of the ground. Outside landscape planning can beused to channel wind direction as well as increase evaporation andcooling rate.An evaporative cooling system can be direct or indirect: the first oneconsist in increasing the water content of an incoming air draughtmaking it stream through evaporated water. The process causes thecooling of the air mass that can therefore be sinked into the buildingto displace stale air, but the increased relative humidity ratio could


create discomfort to users and cause growth of legionaries disease.Indirect evaporative cooling eliminates this issue making the evapo-ration happen inside a heat exchanger, so that the water content ofcooled air remains unaffected.

2.4.6 Limitations

Mechanical ventilation strategies requires significant amounts ofenergy to move the fans, and because of thermal and mechanicallosses the streaming air can be warmed by up to 2 °C from the be-ginning of the route to the delivery point [14]. Moreover the duct netrequires space and mantainance to keep the process efficient, and thelack of control by the occupant can narrow their thermal comfort zone(see [16] for adaptive comfort). On the other hand, natural ventilationstrategies have major drawbacks, such as:

• Aleatory driving forces, notably for wind ventilation

• Aesthetic Impact

• Heat losses and draughts in colder seasons

• Security issues

• Fire and compartment restraints

• Air quality control, especially in terms of pollutants and noise

Noise and pollutant sources can be identified in the first designstage so that solution can be implemented to minimize their impact,otherwise mechanical ventilation should be preferred over naturalventilation at least during occupied hours.

Fire safety code requires the evacuating ways to be smoke proof,so louvres and vents cannot be installed to connect a environmentwith, for example, internal stairwells. This restraint is quite curbing,considering how staircases usually run from the top to the bottom ofthe building, being potentially well exploitable for stack ventilationpurposes. A possible solution is to use a iBEM control system andinstall airtight and fire resistive vents to isolate fire compartments incase of emergency. Sensors should be periodically checked and keptefficient for the global system to work properly (see ASHRAE/ACCAStandard 180 for minimum requirements for mantainance)

Trickle vents can be placed in window frames or modulated piv-oting window can be adopted to avoid cold draught and guaranteeventilation in winter days without having excessive heat loss.

Security can be compromised by near ground placed windows, es-pecially for night ventilation strategies; it is then desirable to usenight opening windows in the upper part of the building while in-stalling burglarproof vents in the lower part.


Insects screen acts as barrier for flying bugs, and especially in trop-ical zone they protect against the spreading of insect transmitted ill-nesses. As for the filters used to guarantee air quality, screens’ meshesact as a significant resistance to airflow, as shown in tab 2.3 from [5]

% Wind speed reductionWind speed

through

bronze wire screen

5.5 wires/cm

Porosity 80%

Wind speed

through

plastic coated

fibreglass

7 wires/cm

Porosity 66%

Wind speed [m/s] Clean Dusty Clean Dusty0.5 50% 64% 80% 84%1 45% 60% 65% 75%

1.5 29% 43% 47% 56%2 25% 35% 43% 50%

2.5 20% 34% 40% 46%

Table 2.3: Effects of insects screen on natural ventilation wind speed

3 R E T R O F I T T I N G E X O F F I C I N EG U G L I E M E T T I

This chapter presents the case study retrofit project for Ex OfficineGuglielmetti. First we analysed weather data generated by Meteonormto assess the potential suitability of natural ventilation.Then, we de-scribe the simulation model used to predict energy performance, bothfor the baseline proposal by the architects and for the solution pro-posed to exploit natural ventilation potential.

3.1 weather data

Required data for energy modelling and natural ventilation study-ing include site wind velocity (speed and direction), outdoor temper-atures and solar radiation data for the building site. Weather stationsare often placed at considerable distance from the site, so that theydo not account for heat island effect or topography influence on winddirection and speed specific for the building site. A way to computethe difference between station measured data and wind site data hasalready been shown in section 2.4.2. Collected data for the locationare illustrated below,note that they are taken from a weather stationplaced in Genoa’s airport, located about 10 km south-west from thebuilding site (see fig. 3.1):

Figure 3.1: Distance from weather station to building site)

34

3.1 weather data 35

• Global yearly solar radiation on the horizontal plan, Ig,h =

1363 kWh/m2

• Beam yearly solar radiation on the horizontal plan, Ib,h = 722 kWh/m2

• Yearly average dry bulb external temperature, Tdb,av = 16.5°C

• Yearly maximum dry bulb temperature, Tdb,max = 32.2°C

• Yearly minimum dry bulb temperature, Tdb,min = 1.1°C

• Yearly average relative humidity, RHav = 68%

• Heating days HD = 99°C

• Heating degree days HDD = 26050°C

• Global winter solar radiation on the horizontal plan, Ig,h,winter =

185 kWh/m2

• Beam winter solar radiation on the horizontal plan, Ib,h,winter =

101 kWh/m2

• Winter average dry bulb external temperature, Tdb,av,winter =

9.1°C

• Winter average relative humidity, RHav = 64%

• Cooling days HD = 160°C

• Cooling degree days HDD = 16710°C

• Global summer solar radiation on the horizontal plan, Ig,h,winter =

828 kWh/m2

• Beam summer solar radiation on the horizontal plan, Ib,h,winter =

378 kWh/m2

• Summer average dry bulb external temperature, Tdb,av,winter =

22.3 °C

• Summer average relative humidity, RHav = 71%

Dry bulb external air temperature frequency is plotted in fig. 3.2,while fig. 3.3 represents ground total irradiation.

36 retrofitting ex officine gugliemetti

0%

25%

50%

75%

100%

0

200

400

600

800

-15 -10 -5 0 5 10 15 20 25 30 35 40 45

Cum

ulat

ive

freq

uenc

y, f

h[%

]

Freq

uenc

y, N

h[h

r]

Dry Bulb Temperature, Tair [°C]

Nh_AVE fh_AVE

Figure 3.2: Dry bulb yearly external air frequency (Nh) and cumulative fre-quency (fh)

0%

25%

50%

75%

100%

0

500

1000

1500

2000

100 200 300 400 500 600 700 800 900 1000 1100

Cum

ulat

ive

freq

uenc

y, f

h[%

]

Freq

uenc

y, N

h[h

r]

Total Horizontal Irradiance, Gt [W/m2]

Nh_AVE fh_AVE

Location: Genova

Figure 3.3: Total yearly horizontal irradiation frequency (Nh) and cumula-tive frequency (fh)

3.1 weather data 37

Wind data have been collected as well from the same airport’sweather station (Weather station ID 161200 - Genoa/Sestri), whichis the nearest wind data station to the building site. These data arerepresented in fig. 3.4 , 3.5, 3.6. Fall and winter season have been splitfrom summer and spring to have a better outlook on wind based ven-tilation potential in warm months.

WRPLOT View - Lakes Environmental Software

WIND ROSE PLOT:

Genovajan-apr

COMMENTS: COMPANY NAME:

MODELER:

DATE:

4/28/2014

PROJECT NO.:

NORTH

SOUTH

WEST EAST

4%

8%

12%

16%

20%

WIND SPEED (m/s)

>= 10.1

8.5 - 10.1

7.0 - 8.5

5.5 - 7.0

3.9 - 5.5

2.4 - 3.9

1.9 - 2.4

1.4 - 1.9

1.0 - 1.4

Calms: 6.49%

TOTAL COUNT:

2880 hrs.

CALM WINDS:

6.49%

DATA PERIOD:

Start Date: 1/1/2000 - 00:00End Date: 4/30/2000 - 23:00

AVG. WIND SPEED:

4.70 m/s

DISPLAY:

Wind SpeedDirection (blowing from)

Figure 3.4: Wind blowing direction and speed for winter season in Genova.



WIND ROSE PLOT:

Genovamay-aug


MODELER:

DATE:

4/28/2014

PROJECT NO.:

NORTH

SOUTH

WEST EAST

3%

6%

9%

12%

15%

WIND SPEED (m/s)

>= 10.1

8.5 - 10.1

7.0 - 8.5

5.5 - 7.0

3.9 - 5.5

2.4 - 3.9

1.9 - 2.4

1.4 - 1.9

1.0 - 1.4

Calms: 11.68%

TOTAL COUNT:

2952 hrs.

CALM WINDS:

11.68%

DATA PERIOD:


AVG. WIND SPEED:

3.55 m/s

DISPLAY:


Figure 3.5: Wind blowing direction and speed for spring/summer seasonsin Genova.

3.1 weather data 39


WIND ROSE PLOT:

Genovaset-dec


MODELER:

DATE:

4/28/2014

PROJECT NO.:

NORTH

SOUTH

WEST EAST

3%

6%

9%

12%

15%

WIND SPEED (m/s)

>= 10.1

8.5 - 10.1

7.0 - 8.5

5.5 - 7.0

3.9 - 5.5

2.4 - 3.9

1.9 - 2.4

1.4 - 1.9

1.0 - 1.4

Calms: 5.60%

TOTAL COUNT:

2927 hrs.

CALM WINDS:

5.60%

DATA PERIOD:


AVG. WIND SPEED:

5.14 m/s

DISPLAY:


Figure 3.6: Wind blowing direction and speed for autumn season in Gen-ova.


3.2 climate potential analysis

To estimate ventilative cooling potential we applied the methodproposed by NIST [15] to shopping mall building typology and fit itaccording to their specific needs. This method assumes that the heat-ing balance point temperature (Tb) establishes the outdoor air tem-perature below which heating must be provided to maintain indoorair temperatures at a defined internal heating set point temperature(Thsp). At this temperature the conductive and ventilative losses ex-actly offset internal and solar gain [15]. Therefore, when outdoortemperature (To) exceeds the heating balance point temperature, di-rect ventilation is considered useful to maintain indoor conditionswithin the cooling set point temperature (Tcsp). At or below theheating balance point temperature, ventilative cooling is no longeruseful because outside air is too cold, but heat recovery ventilationis required to meet minimum air change rates for indoor air qualitycontrol and reduce heat losses. The weather file used for the anal-ysis derives from historical data series (2000-2009) of a weather sta-tion located at the airport of Genoa, which is part of the Meteonormdatabase (Weather station ID 161200 - Genoa/Sestri). We consideredthe building occupied for 12 hours per day and set the cooling setpoint temperature to 26 °C during the day and to 28 °C during thenight, as well as the heating set point temperature to 20 °C duringthe day and 14 °C during the night. Considering an average envelopethermal transmittance of 0.27 W/m2K, the resulting heating balancepoint temperature is

Tb = Thsp −qi

mmin · cP +∑UA

= 12.27°C.

where:

. qi is the internal gains (solar + internal), assumed 20

[Wm2

]. cp is the air capacity

[J

kg·sec

]. mmin is the minimum required mass flow rate

[kgsec

].∑UA is the envelope thermal conductance

[WK

]Note that this value is similar to the 12 °C temperature suggestedby Bourgeois [Bourgeois et al. 2000] to avoid cold drafts in directventilative cooling strategies. For each hour of an annual climaticrecord for the Genoa city we then computed the following:

If To < Tb no ventilative cooling will be required;

If Tb 6 To < Tb + (Tcsp − Thsp) and To−dp 6 17°C the coolingventilation rate may be maintained at the minimum ventilationrate, which has been estimated as 1.7 l/sm2(0.00204kg/s − m2)

3.2 climate potential analysis 41

according to the EN 15251 values for department stores (Cat. II– low polluting building);

If Tb + (Tcsp − Thsp) 6 To 6 Tcsp − 3°C and To−dp 6 17°C theminimum cooling ventilation rate needed to maintain indoorair conditions within the cooling set point temperature are com-puted with the following equation:

m =qi

cP · (Tcsp − To)

[kg

s ·m2

]If To > Tcsp–3°C or To − dp > 17 °C the ventilative cooling isno longer useful and night-time cooling potential is evaluatedas the internal gains that may be offset for a nominal unit night-time air change rate have been computed as:

NCP =(H · ρ · cP ·

(Tcsp−night − To

))

3600

[W

m2 ·ACH

]where:

. H is floor height [m]

. ρ is air density [ kgm3 ]

. Tcps−night is temperature cooling set point at night [°C]

.∑UA is the envelope thermal conductance [ W

K ]

Figure 3.7 depicts monthly average diurnal temperature swing, andglobal horizontal radiation on the ground for the same time referenceperiod. For warmth month the gap between day and night is quitenarrow (about 2.5°C) so it is expected that night ventilation won’t besuccessful for ventilative cooling purpose as the optimal value shallbe 5°C. The climatic cooling potential for night ventilation has beenfurther analysed with the method proposed by Artmaan (2007), com-puting the following value for each night of the year.

CCP =

9:00∑21:00

mh · (Tin − To)

withmh = 1 h if Tin − To > 3Kmh = 0 h if Tin − To < 3K

According to the same study, for efficient night cooling CCP shallbe at least 80 K · h, while in Genoa this value overtakes 40 K · h onlyin September (see fig. 3.8)


0

200

400

600

800

1000

1200

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

jan feb mar apr may jun jul aug sep oct nov dec

Globa

l horizon

tal rad

iatio

n [W

/m²]

Mon

thly average

diurnal te

mpe

rature sw

ing [K]

Figure 3.7: Monthly average diurnal temperature swing and global irradia-tion in Genoa.

0

2

4

6

8

10

12

14

16

0

5

10

15

20

25

30

35

40

45

jan feb mar apr may jun jul aug sep oct nov dec

Internal heat g

ains th

at can

be offset fo

r a nom

inal unit n

ighttim

e ventilatio

n [W

/m²‐AC

H]

Average CC

P pe

r night [K

h]

Figure 3.8: Monthly average Climatic Cooling Potential and night coolingoff-setted internal gains

3.2 climate potential analysis 43

Number of hours when ventilative cooling is effective according to[15] are represented in figure 3.9 for every month of the year. Outsidetemperature pattern for Genoa suggests that for this case study ven-tilative cooling could be well exploited during warmth season whiledaytime ventilation wouldn’t be successful for summer season. Bluebars shows percentage of hours when ventilative cooling is not useful,so that further analysis on night ventilation should be performed toassess its efficiency.

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

jan

feb

marapr

mayjunjul

aug

sep

oct

nov

dec

year

ventilative cooling no

t req

uired

direct ven

tilative cooling with

ven

tilation rate m

aintaine

d at th

e minim

um (E

N 15251)

direct ven

tilative cooling useful

direct ven

tilative cooling no

t useful ‐‐> con

sider nighttim

e ventilatio

n

Figure 3.9: Ventilative cooling potential for Genoa demo case, according to[15]


3.3 the project

The Genoa demo case project regards a deep retrofitting of an oldCOOP shopping center of about 5600sqm (fig.3.11) located on the leftbank of the Bisagno river, about ten kilometers north-east of Genoacity (44°26’20” N , 8°57’47” E , azimuth 10°). The actual mall willbecome a new bigger structure which will incorporate the nearbysouthern factory (Officine Guglielmetti, about 24.000 sqm of plan sur-face) (see fig. 3.12).

Figure 3.10: Satellite picture of Genova and building site. source: GoogleEarth

Figure 3.11: Actual COOP shopping mall seen from Guglielmetti bridge.source: Google Map

3.3 the project 45

Figure 3.12: Satellite image of the building site. In blue: actual shoppingmall. In orange: Guglielmetti factories. source: Google earth


The renovation project designed by the architects , from here pointedout as baseline, will merge the two structures into a single buildingwith a semi-underground floor dedicated to parking lots and an up-per storey for the commercial floor.The new shopping mall will in-clude a green park and a municipal theatre on the roof level (fig. 3.19),as well as a four storeys hotel and a wellness centre on the southernwing (fig.3.17). The underground floor is assigned to the parking lotand warehouses; the southern zone is used as entrance for the hoteland has been neglected from simulation since it is not part of theCommONEnergy project. Commercial floor involves two commonareas running on the main axes of the building (north to south andeast to west), surrounded by shops and two media store on the southwing and northern wing. A big COOP foodstore (6350 m2) will belocated next to the western glazed hallway, on the south-eastern cor-ner of the storey. The project proposal designed from the architectsinvolves a big glazed atrium located on the western facade, with anelevator placed on the southern side that will guarantee access to theopen green park on the roof as well as the commercial gallery andthe underground parking lot. See fig. 3.18

Figure 3.13: Proposal of the architects, 3D render of the new shopping cen-ter. source: INRES (2014)

3.3 the project 47

Figure 3.14: Proposal of the architects, 3D render of the new shopping cen-ter. source: INRES (2014)

Figure 3.15: Proposal of the architects, 3D render of northern wings. source:INRES (2014)


Figure 3.16: Proposal of the architects, 3D render of southern wings withhotel

Figure 3.17: Proposal of the architects, 3D render of the hotel. source: IN-RES (2014)

3.3 the project 49

Figure 3.18: Glazed atrium on the west entrance, suitable for stack ventila-tion. source: INRES (2014)

Figure 3.19: Proposal of the architects, 3D render of the green park on theroof. source: INRES (2014)


3.4 solutions implemented

Due to commercial dynamics and uncertain destination use of shopstores, as well as for the fact that shops tenants can control the finalsetpoints of their stores, ventilative cooling solution were focused onthe common areas of the shopping mall. In this environments of thebuilding, natural ventilation is supposed to work better because ofbigger volumes involved and lack of resistances. So, as shown in bluein fig. 3.20, the intervention has been focused on two narrow straightareas crossing the building on his north/south and east/west axis.

Figure 3.20: Highlight of the intervention zones for implementing ventila-tive cooling strategies

The two main restraint to design a ventilative cooling strategy forthis demo case are:

geometry The main axes of the building is oriented on north-southdirection, with a total depth of about 350 meter from the twoopposite facade walls. As shown in par. 2.4.2, wind cross ven-tilation would not affect a zone deeper than 30 meters (if theceiling height is 6 meter like in this democase), while singleside ventilation would not be effective in a distance greater than12 meters from the windows. Keefe (2010) states that passivestrategies such as natural ventilation work well in a distanceof 7 meters from the building edge, even though this distancecan be improved in some cases. For this demo case purposesthe distance is wider than what any natural driving force couldcover, so it is crucial to divide the common areas into sub-zonesand define different strategies to exploit building layout.

parking lots Both the underground and the roof floor are used asparking lots, so inlet air located on roof or on underground floormight compromise indoor air quality. To avoid this risk night

3.4 solutions implemented 51

ventilation can be used - when the whole building is closed andno car are in the parking lots - or wind catcher inlet passagescan be installed (at least 4 meters above rooftops’ vehicular waylevel according to UNI 10339).

3.4.1 Stack Effect on Western Atrium

Since the height difference from the top of the glazed surface tothe bottom of the western common area is 9.8 meters, a stack effectventilation strategy could be implemented to take out exhaust hot airwhile letting in fresh air from the outside. For this reason inlet ventshave been placed on the external facade of thermal zone F1_S_SHP -which is clear from traffic pollutants - and on the western entrance ofthe common area, facing an external open hallway. Cold air shouldbe stream in from the stack effect produced by the glazed atrium, andshould flow up to the top where pivoting vasistas windows have beendesigned as part of the transparent skylight (see fig. 3.21) .

Figure 3.21: Stack ventilation effect on the western atrium

3.4.2 Ground Coupled Ventilation on Eastern Hallway

Semi underground floor has been exploited as a thermal storageto precondition external air before introducing it on the inside of thestructure. The pollutants problem has been solved adopting an exter-nal vents placed on the lower eastern facade (where vehicular traffic isexpected only for warehouses services) and noticing that the entrancefor the shopping mall is isolated from the parking environment bytwo couple of sliding doors (3.22).

This strategy would exploit the tapis roulant shaft to connect un-derground storey with commercial floor, so that a small depressioncreated by the wind on the external facade will be transferred to thecommon area by the false ceilings of the surrounding shops - seeschemes in fig. 3.23


Figure 3.22: Underground air inlet for ground coupled cooling strategy

Figure 3.23: Ground coupled ventilation effect on the eastern common area

3.5 building the model 53

3.5 building the model

To predict the energy performance of the building, a dynamic sim-ulation software (TRNSYS) has been used. 3D geometric surface in-formation has to be input into TRNSYS using a plug-in for GoogleSketch Up named TRNSYS3d. The first step was thermal zoning bothstoreys of the building introducing right simplification without com-promising the integrity of the structure. As the software TRNsys isbased on a lamped parameter model, three main parameters mustbe maintained when translating the building geometry into an en-ergy model: surface area, orientation (azimuth angle) and tilt (zenithangle); so for example the transparent/opaque ration of an externalsurface can be simplified if the three previous proprieties are rightlyassigned. A thermal zone can enclose volumes with same tempera-ture set point conditions, solar gains, internal loads and ventilationneed. For this case study 7 different types of thermal zones have beenidentified and defined with the following acronyms:

• Shopping areas and stores (SHP)

• Common areas and hallways (CMA)

• Parking lots and zones connected to the outside (PRK)

• Warehouses (WRH)

• Media stores (MDS)

• Restaurants (RST)

• Services (SVC)

Note that as pointed out in par.3.3, the hotel and fitness centerrooms have been neglected from the analysis because they do notbelong to the tasks of the project. Every surface adjacent with thesezone has an adiabatic boundary condition, assuming that comfortset-points for hotel and s.p.a would be the same as those one set foranalysed zones. Underground parking areas have been modelled asthermal zones with no set points for heating/cooling, and with highventilation rate (supposed 10

kghm2 ) to simulate their connection to the

outside on western and eastern facade. Shading effect of overhangs,roof shelter and urban context (three building on the west facade)have been added to the model as "shading group".

Fig. 3.24, and 3.25 show the two thermal zoned storeys of the newshopping mall.


Figure3.24:Therm

alzoningfor

theunderground

floorof

thebuilding


Figu

re3.

25:T

herm

alzo

ning

for

the

first

floor

ofth

ebu

ildin

g


Each thermal zone has then been build in TRNSYS3d obtaining the3D model shown in fig. 3.26, 3.27 , 3.28 from different perspectives

Figure 3.26: Sketch Up 3D model of the building from the south side

Figure 3.27: Sketch Up 3D model of the building from the north side

Figure 3.28: Sketch Up 3D model of the building from the west side


In tab. 3.1 are presented the specifics for the thermal model builtin Sketch Up, each of the 37 resulting zone is identified with an IDcomposed by floor number (F0=underground, F1=commercial floor),main orientation of the external facade (N=north, S=South, E=east,W=west) and finally the acronym which defines the thermal zonetypology as defined above. Height in the real building is consideredfrom ceiling to floor, while in the model is considered from middlepoint of ceiling’s total layers depth and middle point of floor’s totallayers depth. Underground floor has been simplified to a uniformheight while commercial floor has been set to two heights, 5 m onthe northern wing and 7.4 m from eastern-western common areas tosouth.

The geometric model was then imported in TRNBuild to define,for each thermal zone, internal gains, constructions for internal andexternal surfaces, as well as glass and frame proprieties for everyglazed area. Tab. 3.2 to 3.9 shows the construction assigned to walls,roof and glazed areas.


Nº ZONE ID AREA [m2] HEIGHT [m] VOLUME [m3] AIRNODE

A H V CAPACITANCEreal model real model real model kJ/K

1 F0MWRH2 156 156 4.00 5.00 624 780 9360

2 F0ESVC 71 71 4.00 5.00 284 355 4260

3 F0NPRK 9742 9742 3.00 5.00 29226 48710 584520

4 F0EWRH1 571 571 4.00 5.00 2284 2855 34260

5 F0WPRK 191 191 4.00 5.00 764 955 11460

6 F0NPRK1 222 222 4.00 5.00 888 1110 13320

7 F0MWRH1 461 461 4.00 5.00 1844 2305 27660

8 F0MPRK 8846 8846 3.00 5.00 26538 44230 530760

9 F1WSHP 1325 1325 4.50 5.00 5963 6625 79500

10 F1WCMA1 561 561 6.40 7.40 3590 4151 49817

11 F1NCMA 545 545 4.50 5.00 2453 2725 32700

12 F1ECMA1 871 871 6.40 7.40 5574 6445 77345

13 F1MSHP1 596 596 6.40 7.40 3814 4410 52925

14 F1ECMA2 128 128 6.40 7.40 819 947 11366

15 F1ESHP2 126 126 6.40 7.40 806 932 11189

16 F1MSHP2 134 134 6.40 7.40 858 992 11899

17 F1WPRK 292 292 6.40 7.40 1869 2161 25930

18 F1WMDS 2855 2855 6.40 7.40 18272 21127 253524

19 F1SSVC 186.8 186.8 6.40 7.40 1196 1382 16588

20 F1SMDS 217 217 6.40 7.40 1389 1606 19270

21 F1MSVC 88 88 6.40 7.40 563 651 7814

22 F0MRST 830 830 4.00 5.00 3320 4150 49800

23 F0ERST 155 155 4.00 5.00 620 775 9300

24 F1SSHP 439 439 6.40 7.40 2810 3249 38983

25 F1NPRK 131 131 6.40 7.40 838 969 11633

26 F1MSHP3 292 292 6.40 7.40 1869 2161 25930

27 F1MCMA2 208 208 6.40 7.40 1331 1539 18470

28 F1EPRK 518 518 6.40 7.40 3315 3833 45998

29 F1EWRH1 1091 1091 6.40 7.40 6982 8073 96881

30 F1MSHP0 733 733 6.40 7.40 4691 5424 65090

31 F1NSHP 721 721 4.50 5.00 3245 3605 43260

32 F1NMDS 3562 3562 4.50 5.00 16029 17810 213720

33 F1MCMA1 510 510 6.40 7.40 3264 3774 45288

34 F0SSVC 140 140 4.00 5.00 560 700 8400

35 F1WCMA2 884 844 6.40 7.40 5658 6246 74947

36 F1EFDS 6352 6352 6.40 7.40 40653 47005 564058

37 F1EWRH2 338 338 6.40 7.40 2163 2501 30014

Table 3.1: Geometric features of the 3D energy model

FO_EXTERNAL_WALL Boundary conditions External

Optical characteristics of finishing layers and convective heat transfer coefficientsAbsortance Reflectivity Emissivity Conv. heat transfer Conv. heat transfer

(W/m2K) (kJ/hm2K)I Inside/front 0.6 0.9 3.1 11.0

O Outside/back 0.6 0.9 17.8 64.0Layers (inside/front to outside/back)

Nº Material Thickness Thermal conductivity Density Specific heat Resistance(m) (W/mK) (kg/m3) (kJ/kgK) (m2K/W)

- Front sup. resistance - - - - 0.327

- Back sup. resistance - - - - 0.056

1 Wall_board 0.01 0.35 750 1 0.029

2 Mineral Wool 0.13 0.0444 80 0.9 2.925

3 Leca Block 0.2 0.4 1200 1 0.500

Total thickness UTrnsys (W/m2K) U (W/m2K)0.34 0.276 0.261

Table 3.2: Envelope layers for underground walls and northern facade


F1_EXT_WALL Boundary conditions External







1 Wall_board 0.01 0.35 750 1.1 0.029

2 Mineral Wool 0.09 0.044 80 0.9 2.025

3 Leca Block 0.2 0.4 1200 1 0.500


Table 3.3: Envelope layers for commercial floor (F1)

F0_ADJ_WALL Boundary conditions Internal



O Outside/back 0.6 0.9 17.8 64.0Layers inside/front to outside/back




1 Wall_board 0.01 0.35 750 1.1 0.029

2 Mineral Wool 0.026 0.044 80 0.9 0.585

3 Leca Block 0.2 0.4 1200 1 0.500


Table 3.4: Layer composition of internal walls

F1_EXT_RF Boundary conditions External







1 Spiroll block 0.25 0.9 2400 0.88 0.278

2 Concrete slab 0.05 1.111 1400 1 0.045

3 Bitumenroof 0.005 0.169 1200 1 0.030

4 XPS 0.14 0.048 120 0.5 2.917

5 Lightweight concrete 0.15 0.889 1500 1 0.169


Table 3.5: Layer composition of external roof


F0_GRD Boundary conditions Boundary

Optical characteristics of finishing layers and convective heat transfer coefficientsAbsortance Reflectivity Emissivity Conv. heat Transfer Conv. heat transfer


O Outside/back 0.9 0.0 0.001

Layers (inside/front to outside/back)Nº Material Thickness Thermal conductivity Density Specific heat Resistance

(m) (W/mK) (kg/m3) (kJ/kgK) (m2K/W)- Front sup. resistance - - - - 0.327

- Back sup. resistance - - - -1 Stone foundation 0.005 2.083 1500 0.88 0.002

2 XPS 0.08 0.034 50 1.4 2.361

3 Concrete slab 0.002 1.111 1400 1 0.002

4 Floor 0.03 0.722 1800 0.2 0.042


Table 3.6: Layer composition of ground level

F1_ADJ_FLOOR Boundary conditions Adjacent







1 Floor tiles 0.02 0.722 1800 0.2 0.028

2 Concrete slab 0.16 1.111 1400 1 0.090

3 XPS 0.082 0.034 50 1.4 2.420

4 Concrete slab 0.05 1.111 1400 1 0.090

5 PI - shingle 0.05 1.910 2400 1 0.026


Table 3.7: Layer composition for ceiling

EXT_WD Boundary conditions External

Glazing propertiesNº Name winID Thickness Thermal transmitance U Solar factor g

(mm) (W/m2K)1 7382 1.4 0.614

Frame propertiesNº %frame Thermal transmitance U Solar absorptance

(W/m2K)1 Data from TRNSYS library 30% 3.03 0.6

Table 3.8: External windows features

EXT_SL Boundary conditions External

Glazing propertiesNº Name winID Thickness Thermal transmitance U Solar factor g

(mm) (W/m2K)1 5001 0.354 0.298

Frame propertiesNº %frame Thermal transmitance U Solar absorptance

(W/m2K)1 Data from library 30% 3.03 0.6

Table 3.9: External skylights features


3.5.1 Internal Gains

Internal gains due to occupants, appliances and lights have beendefined for each thermal zone. For the occupancy profiles and sched-ules, data provided from INRES-COOP, one of the partner of Com-mONEnergy project, have been used instead of literature data.

Occupancy

The human body works like a machine which transform fuel intoenergy when a work is done 1. If this process generates more heatthan needed to maintain a constant temperature, this heat must bedissipated in some way to avoid dangerous rising of the body’s inter-nal temperature. There are two way to reject this heat:

SENSIBLE heat transfer = 324 kJ/hr according to ISO 77302, which

includes

→ Radiant loss to cooler surfaces

→ Convection loss to cooler air (40% of the total sensible heattransfer according to ISO 7730)

→ Dry respiration heat exchange of air entering cold in thelungs and being blown warmer

LATENT heat transfer = 0.12 kg/hr according to ISO 7730, whichincludes

→ Evaporation of sweat

→ Water diffusion through the skin

→ Latent respiration heat loss

Multiplying those values for measured occupation data (columnthree of tab. 3.10) will lead to obtain internal gains for each hourof occupancy. The schedule representing the pattern of occupancyduring opening hour was measured as well and is reported in 3.11.

1 the rate of heat produced by all chemical reaction within all the body is called MET,measured in [met. 1 MET = 105.4 W/h]

2 Standing, light work or working slowly in retail buildings


OCCUPANCY

Nº ZONE ID IG_PER_RAD IG_PER_SENS IG_PER_LAT(persons/m²) (nr of persons) (kJ/h) (kJ/h) (kg/h)

1 F0MWRH2 0.1 15.6 3033 2022 1.87

2 F0ESVC 0 0 0 0 0.00

3 F0NPRK 0.2 1948.4 378769 252513 233.81

4 F0EWRH1 0.1 57.1 11100 7400 6.85

5 F0WPRK 0.2 38.2 7426 4951 4.58

6 F0NPRK1 0.2 44.4 8631 5754 5.33

7 F0MWRH1 0.1 46.1 8962 5975 5.53

8 F0MPRK 0.2 1769.2 343932 229288 212.30

9 F1WSHP 0.2 198.75 38637 25758 23.85

10 F1WCMA1 0.2 112.2 21812 14541 13.46

11 F1NCMA 0.2 109 21190 14126 13.08

12 F1ECMA1 0.2 174.2 33864 22576 20.90

13 F1MSHP1 0.2 89.4 17379 11586 10.73

14 F1ECMA2 0.2 25.6 4977 3318 3.07

15 F1ESHP2 0.2 18.9 3674 2449 2.27

16 F1MSHP2 0.2 20.1 3907 2605 2.41

17 F1WPRK 0.2 58.4 11353 7569 7.01

18 F1WMDS 0.2 456.8 88802 59201 54.82

19 F1SSVC 0 0 0 0 0.00

20 F1SMDS 0.2 34.72 6750 4500 4.17

21 F1MSVC 0 0 0 0 0.00

22 F0MRST 0.25 124.5 24203 16135 14.94

23 F0ERST 0.25 23.25 4520 3013 2.79

24 F1SSHP 0.2 65.85 12801 8534 7.90

25 F1NPRK 0.2 26.2 5093 3396 3.14

26 F1MSHP3 0.2 43.8 8515 5676 5.26

27 F1MCMA2 0.2 41.6 8087 5391 4.99

28 F1EPRK 0.2 103.6 20140 13427 12.43

29 F1EWRH1 0.1 109.1 21209 14139 13.09

30 F1MSHP0 0.2 109.95 21374 14250 13.19

31 F1NSHP 0.2 108.15 21024 14016 12.98

32 F1NMDS 0.2 569.92 110792 73862 68.39

33 F1MCMA1 0.2 102 19829 13219 12.24

34 F0SSVC 0 0 0 0 0.00

35 F1WCMA2 0.2 176.8 34370 22913 21.22

36 F1EFDS 0.25 1270.4 246966 164644 152.45

37 F1EWRH2 0.1 33.8 6571 4380 4.06

Table 3.10: Internal gains due to occupancy for each zone of the model

Appliances

Internal heat gains due to equipment and machines are accountedwith the following load scheme for each zone type:

• Appliances internal gain for the food-store (FDS) = - 9.4 W/m2,calculated on the layout of refrigeration cabinets, based on EPTAdata.

• Appliances internal gain for warehouses (WRH) = 5 W/m2

• Appliances internal gain for media stores (MDS) = 2 W/m2

• Appliances internal gain for services (SVC) = 6.5 W/m2

Those values are multiplied for the area of each zone to obtain thetotal internal load due to equipment and are split in radiant and con-vective fraction of sensible heat loss according to ISO 7730 (see 3.12).


SCHEDULES OF OCCUPANCY

SHP CMA MDS FDS WRH PRK SVC RSTORARIO fraction fraction fraction fraction fraction fraction fraction fraction

00:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

01:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

02:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

03:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

04:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

05:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

06:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

07:00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.40

08:00 0.05 0.05 0.05 0.05 0.05 0.10 0.00 0.60

09:00 0.05 0.05 0.05 0.05 0.05 0.05 0.00 0.50

10:00 0.10 0.10 0.10 0.10 0.10 0.05 0.00 0.20

11:00 0.30 0.30 0.30 0.30 0.30 0.05 0.00 0.20

12:00 0.30 0.60 0.30 0.30 0.30 0.10 0.00 0.40

13:00 0.50 0.70 0.50 0.50 0.50 0.10 0.00 0.80

14:00 0.40 0.60 0.40 0.40 0.40 0.10 0.00 0.70

15:00 0.40 0.50 0.40 0.40 0.40 0.05 0.00 0.10

16:00 0.50 0.40 0.50 0.50 0.50 0.05 0.00 0.00

17:00 0.50 0.40 0.50 0.50 0.50 0.10 0.00 0.10

18:00 0.70 0.80 0.70 0.70 0.70 0.10 0.00 0.10

19:00 0.70 0.80 0.70 0.70 0.70 0.13 0.00 0.30

20:00 0.30 0.60 0.30 0.30 0.30 0.13 0.00 0.80

21:00 0.00 0.00 0.00 0.00 0.00 0.13 0.00 1.00

22:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00

23:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10

24:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

h/day 4.8 5.9 4.8 4.8 4.8 1.34 0 7.30

Table 3.11: Pattern of occupancy for each thermal zone type of the model


0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

00:0001:0002:0003:0004:0005:0006:0007:0008:0009:00 10:0011:0012:0013:0014:0015:0016:0017:0018:0019:0020:00 21:0022:0023:0024:00

Occup

ancy fractio

n

Orario

SCH_SHP_PER SCH_CMA_PER SCH_FDS_PER SCH_MDS_PER SCH_WRH_PER SCH_PRK_PER SCH_SVC_PER SCH_RST_PER

Figure 3.29: Daily function of occupancy for each zone type of the model

The schedule of use of the equipment is shown in tab 3.30 and in fig.3.13

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Appliances fractio

n

Orario

SCH_FDS_APL SCH_MDS_APL SCH_WRH_APL SCH_RST_APL

Figure 3.30: Daily function of appliances pattern for each zone type of themodel


APPLIANCES

Nº ZONE ID IG_APL spec. IG_APL IG_APL_RAD IG_APL_SEN(W/m²) (W) (kJ/h) (kJ/h)

1 F0MWRH2 5 780 758 2050

2 F0ESVC 6.5 461.5 448.6 1212.83 F0NPRK 0 0 0 0

4 F0EWRH1 5 2855 2775.0 7502.95 F0WPRK 0 0 0 0

6 F0NPRK1 0 0 0 0

7 F0MWRH1 5 2305 2240.4 6057.58 F0MPRK 0 0 0 0

9 F1WSHP 0 0 0 0

10 F1WCMA1 0 0 0 0

11 F1NCMA 0 0 0 0

12 F1ECMA1 0 0 0 0

13 F1MSHP1 0 0 0 0

14 F1ECMA2 0 0 0 0

15 F1ESHP2 0 0 0 0

16 F1MSHP2 0 0 0 0

17 F1WPRK 0 0 0 0

18 F1WMDS 2 5710 5550.1 15005.819 F1SSVC 6.5 1214.2 1180.2 3190.920 F1SMDS 2 434 421.8 1140.521 F1MSVC 6.5 572 555.9 1503.222 F0MRST 5 4150 4033.8 10906.223 F0ERST 5 775 753.3 2036.724 F1SSHP 0 0 0 0

25 F1NPRK 0 0 0 0

26 F1MSHP3 0 0 0 0

27 F1MCMA2 0 0 0 0

28 F1EPRK 0 0 0 0

29 F1EWRH1 5 5455 5302.2 14335.730 F1MSHP0 0 0 0 0

31 F1NSHP 0 0 0 0

32 F1NMDS 2 7124 6924.5 18721.933 F1MCMA1 0 0 0 0

34 F0SSVC 6.5 910 884.52 2391.48

35 F1WCMA2 0 0 0 0

36 F1EFDS -9.4 -59708.8 -58036.9 -156914.737 F1EWRH2 5 1690 1642.6 4441.32

Table 3.12: Internal gains due to presence of appliances for each zone of themodel


SCHEDULES OF USE OF THE APPLIANCES

FDS MDS WRH RST SVCORARIO fraction fraction fraction fraction fraction

00:00 0.65 0.1 0.1 0.1 0.101:00 0.65 0.1 0.1 0.1 0.102:00 0.65 0.1 0.1 0.1 0.103:00 0.65 0.1 0.1 0.1 0.104:00 0.65 0.1 0.1 0.1 0.105:00 0.65 0.1 0.1 0.1 1

06:00 0.65 0.1 0.1 0.1 1

07:00 0.65 0.1 0.1 0.71 0.508:00 1 0.1 1 1 0.75

09:00 1 1 1 0.6 0.510:00 1 1 1 0.1 0

11:00 1 1 1 0.2 0

12:00 1 1 1 0.2 0.25

13:00 1 1 1 1 0.75

14:00 1 1 1 1 0.515:00 1 1 1 0 0.25

16:00 1 1 1 0 0

17:00 1 1 1 0 0

18:00 1 1 1 0.6 0.25

19:00 1 1 1 1 0.520:00 1 0.1 0.1 1 0.521:00 1 0.1 0.1 1 1

22:00 1 0.1 0.1 1 0.75

23:00 1 0.1 0.1 0.13 1

24:00 0.65 0.1 0.1 0 1

h/day 17.95 11.8 12.7 9.64 9.5

Table 3.13: Schedule of appliances activation for each zone of the model


Lighting

Internal gains generated by lighting appliances have been com-puted according to data provided by INRES-COOP, which are summedin tab. 3.14. Each value has been multiplied for the area of the zoneand then split into its radiative and convective part (as done abovewith internal gain from appliances). Schedule of light equipmentswitching on and off is presented in tab. 3.15

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

00:00

01:00

02:00

03:00

04:00

05:00

06:00

07:00

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

24:00

Lightin

g fractio

n

Orario

SCH_SHP_LGT SCH_CMA_LGT SCH_FDS_LGT SCH_MDS_LGT

Figure 3.31: Daily function of lighting pattern for each zone type of themodel


LIGHTING

Nº ZONE ID IG_LGT spec. IG_LGT IG_LGT_RAD IG_LGT_SEN(W/m²) (W) (kJ/h) (kJ/h)

1 F0MWRH2 15 2340 3369.6 5054.42 F0ESVC 0 0 0 0

3 F0NPRK 2.2 21432.4 30862.6 46293.94 F0EWRH1 15 8565 12333.6 18500.45 F0WPRK 2.2 420.2 605.1 907.632

6 F0NPRK1 2.2 488.4 703.3 1054.97 F0MWRH1 15 6915 9957.6 14936.48 F0MPRK 2.2 19461.2 28024.1 42036.19 F1WSHP 14 18550 26712 40068

10 F1WCMA1 8 4488 6462.7 9694.011 F1NCMA 8 4360 6278.4 9417.612 F1ECMA1 8 6968 10033.9 15050.913 F1MSHP1 15 8940 12873.6 19310.414 F1ECMA2 8 1024 1474.6 2211.815 F1ESHP2 15 1890 2721.6 4082.416 F1MSHP2 15 2010 2894.4 4341.617 F1WPRK 2.2 642.4 925.5 1387.618 F1WMDS 15 42825 61668 92502

19 F1SSVC 0 0 0 0

20 F1SMDS 15 3255 4687.2 7030.821 F1MSVC 0 0 0 0

22 F0MRST 10 8300 11952 17928

23 F0ERST 10 1550 2232 3348

24 F1SSHP 15 6585 9482.4 14223.625 F1NPRK 2.2 288.2 415.0 622.526 F1MSHP3 15 4380 6307.2 9460.827 F1MCMA2 8 1664 2396.2 3594.428 F1EPRK 2.2 1139.6 1641.0 2461.529 F1EWRH1 15 16365 23565.6 35348.430 F1MSHP0 15 10995 15832.8 23749.231 F1NSHP 14 10094 14535.4 21803.32 F1NMDS 8 28496 41034.2 61551.433 F1MCMA1 8 4080 5875.2 8812.834 F0SSVC 0 0 0 0

35 F1WCMA2 8 7072 10183.7 15275.536 F1EFDS 15 95280 137203.2 205804.837 F1EWRH2 15 5070 7300.8 10951.2

Table 3.14: Internal gains due to lighting equipment for each zone of themodel


SCHEDULE OF LIGHTING EQUIPMENT USE

SHP CMA MDS FDS WRH PRK SVC RSTORARIO fraction fraction fraction fraction fraction fraction fraction fraction

00:00 0.05 0 0.05 0.05 0.05 0.05 0.05 0.05

01:00 0.05 0 0.05 0.05 0.05 0.05 0.05 0.05

02:00 0.05 0 0.05 0.05 0.05 0.05 0.05 0.05

03:00 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

04:00 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

05:00 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

06:00 0.05 0.05 0.05 0.5 0.05 0.05 0.05 0.507:00 0.05 1 0.5 0.5 0.5 1 0.05 1

08:00 0.5 1 1 1 1 1 0.05 1

09:00 1 1 1 1 1 1 0.05 1

10:00 1 1 1 1 1 1 0.05 1

11:00 1 1 1 1 1 1 0.05 1

12:00 1 1 1 1 1 1 0.05 1

13:00 1 1 1 1 1 1 0.05 1

14:00 1 1 1 1 1 1 0.05 1

15:00 1 1 1 1 1 1 0.05 1

16:00 1 1 1 1 1 1 0.05 1

17:00 1 1 1 1 1 1 0.05 1

18:00 1 1 1 1 1 1 0.05 1

19:00 1 1 1 1 1 1 0.05 1

20:00 1 1 0.05 0.05 0.05 1 0.05 1

21:00 0.05 0.05 0.05 0.05 0.05 1 0.05 1

22:00 0.05 0.05 0.05 0.05 0.05 1 0.05 1

23:00 0.05 0.05 0.05 0.05 0.05 0.05 0.05 1

24:00 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05

h/day 12.8 14.25 12.8 13.25 12.8 16.15 0.95 17.55

Table 3.15: Schedule of daily light equipment use for each zone of themodel


3.5.2 Ventilation and Infiltration

To simulate the behaviour of the mechanical plant that would sup-ply minimum air changes (see Chapter 2), the following values havebeen used, according to standard EN 15251:2008:

• Specific ventilation fresh air mass for shops, common areas,foodstore, mediastores and restaurant = 7.35 kg/hm2

• Specific ventilation fresh air mass for warehouses and services=3.02 kg/hm2

Heat recovery for ventilation system has been set to zero to evaluatethe passive behaviour of the building. Infiltration values have beenset to zero as well. For the activation schedule of mechanical ventila-tion plant, during occupied hour the air changes are those prescribedby EN 15251 and descripted above, while during closing hours (21-8)the ventilation in every zone is kept at the minimum value of 3.02

kg/hm2.

3.5.3 Constructing the network

For the reasons explained par 3.4, the whole net of common areashas been divided into four sub-network, each one controlled by adedicated algorithm and connected to zone F1_M_CMA1 (HUB zone).Fig. 3.32 illustrates graphically this division, while below is provideda description of the strategy adopted in each one of them:

subnet 1 involves the zone F1_N_CMA (northern common area) -so the control algorithm is set on its temperature - and is con-nected to the outside with a two air vents placed on the lowerpart of the mall’s northern entrance.

subnet 2 involves the thermal zone F1_E_CMA1 (eastern commonarea) - whose temperature controls the on/off switch of the sys-tem.

subnet 3 involves thermal zones F1_W_CMA1 (western commonarea) and F1_S_SHP (shops adjacent to western common areaand facing south),and it is controlled by thermostats in the hall-way.

subnet 4 regards the F1_W_CMA2 (western glazed hallway) whichhas been designed with vasistas windows on the top of theglazed facade. The strategy is a ground coupled ventilation asin eastern common areas, exploiting the shaft created by tapisroulant in F0_N_PRK and delivering cool air to the upper floor.


Link Link From To From To Own height OpeningID Name Node Node height height factor Factor

1 WI_EXT_V_GRID1 EN_F0EPRK F0_N_PRK 0.20 0.20 1 1*OF_SUBNET3

2 WI_VIRTUALF0F1 F0_N_PRK F1_E_CMA1_AN1 5.00 5.00 0 1

3 WI_COUPLINGEAST F1_E_CMA1_AN1 F1_E_CMA1_AN2 8.70 8.70 0 1

4 WI_INTVSHP0 F1_E_CMA1_AN2 AN_FCEILING_E 12.15 12.15 1 1*OF_SUBNET3

6 WI_EXTN_AIR_O AN_FCEILING_E EN_F1MSHP0 12.15 12.15 1 1*OF_SUBNET3

7 WI_EXTS_AIR_O AN_FCEILING_E EN_F1MSHP1 12.15 12.15 1 1*OF_SUBNET3

11 WI_EXTS_AIR_O EN_F1SSHP F1_S_SHP 5.15 5.15 1 1*OF_SUBNET2

14 WI_VSTAS_ATRIOW F1_W_CMA1_AN2 EN_F1MSHP0 14.60 14.60 1 1*OF_SUBNET2

12 WI_INT_H_AIRINW F1_S_SHP AN_FCEILING_W 9.50 9.50 0 1

13 WI_AIR_V_INLF1 AN_FCEILING_W F1_W_CMA1_AN2 9.75 9.75 1 1*OF_SUBNET2

17 CR_002 F1_W_CMA1_AN2 EN_CRACKW 14.80 14.80 1 1

16 WI_COUPLINGWEST F1_W_CMA1_AN1 F1_W_CMA1_AN2 8.70 8.70 0 1

15 WI_EXTW_AIRIN EN_F1WCMA F1_W_CMA1_AN1 5.15 5.15 1 1*OF_SUBNET2

8 WI_VIRT_WTOM F1_W_CMA1_AN1 F1_M_CMA1_AN1 6.85 6.85 1 1

9 WI_VIRT_MTOE F1_M_CMA1_AN1 F1_E_CMA1_AN1 6.85 6.85 1 1

19 WI_COUPLINGMID F1_M_CMA1_AN1 F1_M_CMA1_AN2 8.70 8.70 0 1

20 WI_EXTNAIRIN EN_F1NCMA F1_N_CMA 5.15 5.15 1 1*OF_SUBNET1

21 WI_VIRTUALNTOM F1_N_CMA F1_W_CMA1_AN1 7.50 7.50 1 1

24 WI_EXTNAIRIN2S EN_F0NPRK F0_N_PRK1 0.15 0.15 1 1*OF_SUBNET4

25 WI_COUPLINNPRK F0_N_PRK1 F1_N_PRK 5.00 5.00 0 1

26 WI_INTVMSHP3 F1_N_PRK F1_W_CMA2 8.70 8.70 1 1

23 CR_003 F1_N_PRK EN_CRACKW 12.40 12.40 1 1

28 WI_VSTASWCMA F1_W_CMA2 EN_WCMA2N 10.55 10.55 1 0.2*OF_SUBNET4

5 CR_002 F1_E_CMA1_AN2 EN_CRACKE 12.40 12.40 1 1

10 CR_002 F1_M_CMA1_AN2 EN_CRACKE 12.40 12.40 1 1

22 WI_VIRMTOWCMA2 F1_M_CMA1_AN2 F1_W_CMA2 10.55 10.55 1 1

18 WI_VIRMTOWCMA2 F1_M_CMA1_AN1 F1_W_CMA2 6.85 6.85 1 1

Table 3.16: Linkages features in the network implemented for the solution

OPENINGS

Link Name Description Cd Width HeightExtra Crack

Lenght

WI_INT_H_AIRINE Horizontal internal air inlet 0.3 2.0 2.0 0.0WI_VIRTUALF0F1 Eastern shaft 1.0 6.4 14.0 0.0

WI_COUPLINGEAST Virtual surface for coupling east 1.0 25.4 32.5 0.0WI_EXT_V_GRID1 External inlet from west facade 0.3 5.0 0.4 0.0WI_EXTN_AIR_O External air inlet from roof 0.3 40.0 0.4 0.0

WI_INTVSHP0 Air inlet from hallway to shop M0 0.3 38.0 0.3 0.0WI_INTVSHP1 Air inlet from hallway to shop M1 0.3 25.0 0.3 0.0

WI_VSTAS_ATRIOW Vasistas on the glazed atrium 0.3 20.0 0.4 0.0WI_AIR_V_INLF1 Air inlet from falseceiling to west hallway 0.3 20.0 0.3 5.0

WI_INT_H_AIRINW Horizontal air vent for the shops 0.3 4.0 4.0 9.6WI_COUPLINGWEST Virtual surf. for west atrio coupling 1.0 15.2 36.0 0.0

WI_EXTS_AIR_O External inlet for western shops 0.3 35.0 0.3 0.0WI_EXTW_AIRIN External inlet from eastern facade 0.3 15.0 0.3 0.0WI_VIRT_WTOM HUB connection with west hallway 1.0 14.0 3.5 0.0WI_VIRT_MTOE HUB connection with east hallway 1.0 21.3 3.5 0.0

WI_COUPLINGMID HUB virtual surface for coupling 1.0 22.6 22.6 0.0WI_EXTNAIRIN External inlet for northern facade 0.3 8.0 0.3 0.0

WI_VIRTUALNTOM HUB connection with north hallway 1.0 7.9 5.0 0.0WI_VIRMTOWCMA2 HUB connection with glazed hallway 1.0 5.9 3.7 0.0

WI_EXTNAIRIN2S Air inlet from underground parking 0.3 15.6 0.3 0.0WI_COUPLINNPRK Tapis roulant shaft for subnet4 1.0 15.6 8.4 0.0

WI_INTVMSHP3 False ceiling for MSHP3 1.0 8.0 5.0 0.0

Table 3.17: Openings features for the airflow network network


Figure 3.32: Problem’s division into subnetwork, the red dot is the HUBzone connecting all of the four subnet

Cp-Gen

As already pointed out in 2.4.2, wind velocity and pressure coeffi-cient are the two main data required to compute the intensity and dis-tribution of wind pressure over the building envelope. The first oneis provided together with climate data by the meteo station placed inGenoa’s airport. To determine pressure coefficient a detailed analysisis required. The software Cp-Gen computes the pressure coefficientfor each facade of the building at an height H defined by the user andfor defined wind directions. Main input data regards the geometryof the building to analyse and the surrounding shading object geom-etry. Terrain roughness (defined with the roughness length z0) wasdefined as in fig. 3.33 ;

WIND0 45 90 135 180 225 270 315

DIRECTION

Facade elementENODE F1SSHP CP= -0.139 -0.123 -0.161 0.027 -0.142 -0.085 -0.207 -0.156

ENODE F1NCMA CP= 0.293 0.21 -0.076 -0.136 -0.14 -0.232 -0.184 0.116

ENODE F0EPRK CP= -0.14 0.093 0.259 0.262 -0.1 -0.212 -0.132 -0.127

ENODE F1WCMA CP= -0.061 -0.12 -0.135 -0.154 -0.178 0.293 0.32 0.163

ENODE F1MSHP0 CP= -0.088 0.078 -0.172 -0.264 -0.164 -0.297 -0.218 -0.089

ENODE F1MSHP1 CP= -0.158 -0.161 -0.239 0.208 0.145 0.067 -0.136 -0.149

ENODE F0NPRK CP= 0.05 0.361 -0.072 -0.147 -0.183 -0.312 -0.327 -0.017

ENODE CRACKW CP= -0.158 -0.158 -0.158 -0.112 -0.211 -0.238 -0.232 -0.186

ENODE CRACKE CP= -0.158 -0.176 -0.123 -0.04 -0.171 -0.315 -0.179 -0.157

ENODE WCMA2N CP= -0.125 -0.2125 -0.1695 -0.121 -0.1315 0.135 0.12 0.242

ENODE WCMA2S CP= -0.099 -0.165 -0.168 -0.154 -0.191 0.081 0.248 0.183

Table 3.18: Cp value for each external node implemented in the network


Figure 3.33: Roughness length z0 for the case study

3.5.4 Control algorithms

Each one of the four subnet works with a dedicated algorithm, sothat the proposed solution is flexible enough to activate ventilativecooling strategies only where required. The control policy splits theday into two main part:

Closing hours: from 9 p.m. to 8 a.m. the shopping mall will be un-occupied so night ventilation can be exploited to purge internalheat, without affecting thermal comfort. So during night timethe system is activated if

Tout > 12°C and Tout < Tcma

Opening hours: from 7 a.m. to 9 p.m. occupant’s comfort issue nar-rows the exploitable temperature range for natural ventilationstrategy, so that external air can be directly introduced in therooms only if its temperature falls inside the setpoints range. Inthis case the subnet would be activated if

20°C < Tout < 26°C


3.6 trnsys and trnflow

TRNSys is a dynamic simulation software that evaluates the wholebuilding performance, taking into account thermal mass effects usinga conduction transfer function method (CTF) [6].

In its integrated plug-in TRNFlow, the building is assumed as anetwork of node and airflow links: each node is considered to havea uniform temperature and a pressure varying hydrostatically, whilecracks, windows, vents, ducts and fans represent the link from a nodeto another. COMIS algorithm is used to calculate air flow mass, whichconstruct a matrix of thermal equation for all the building zone plusBernoulli equation for each of the airflow path. The obtained matrixis solved numerically until the sum of all mass flow rates reaches zerowithin the specified tolerance (convergence condition).

Despite their simplicity, this model and airflow network models ingeneral have some important limitations:

• heavily dependency on wind profile, coefficient of dischargeand coefficient of pressure, which are not always available forthe building site;

• neglection of turbulent fluctuations of wind pressures, so thatcp dynamic coefficient should be calculated separately and thenadded as input;

• air speed in rooms cannot be evaluated since the Navier Stokesequation is not involved in the solution algorithm

The pressure pZ is a free parameter in the node which is evaluatedaccording to the continuity equation (mass flow balance in the node= 0 ). But the relation between mass flow rate m and zone pressurepZ is not linear, therefore an iterative process must be implementedto solve the system of nZ equation (where n is the number of zonesin the model). After the zone pressure has been calculated, m can becalculated and TRNsys and TRNflow can be coupled to exchange arecursive flow of information with a negative feedback [2], so that foreach timestep the outputs from thermal model are used as inputs forthe airflow model and vice-versa until balance is reached.

4 R E S U LT S A N D D I S C U S S I O N

In this chapter we present and discuss simulation outputs, com-paring the proposal by the architects with the solutions described inChapter 3.

4.1 outcomes

4.1.1 Temperatures decrease

Graphs 4.1, 4.3, 4.5, 4.7, 4.9, show the cooling effect for each oneof the common area analysed, the blue line represent temperaturestrend during the whole year and during the last three days of July(when an annual peak of temperature has been found for the pro-vided weather data). Red line indicates the temperature outcomingfrom the model with the ventilative cooling strategy proposal, whilethe blue one is the temperature in the baseline model. As can be seenin pictures 4.2, 4.6, the network works well in western and north com-mon area (subnet 1 and 2), while the solution works less efficientlyin the glazed hallway and in eastern common area (subnet 3 and 4,see 4.7, 4.3). This is probably because the air inlets on the easternfacade are too small (0.4 · 2.5 = 1m2) to serve the 5600 m3 volumeof W_CMA1. As previously pointed out in Chapter 3, indoor qualityproblems can be encountered when inlet air is connected to the under-ground parking lot, inlet air cannot be increased in this case. For thisthermal zone the air flow model shows a temperature trend, where airtemperature decrease up to 0.3°C time and during daytime tempera-ture are higher than in the baseline. This can be due to the fact thatthe coupling airflow of adjacent vertical airnodes is not computedin the baseline while TRNFlow model for the proposed solution cal-culates the air mass exchange through big horizontal openings, soduring the night warm air flows from lower to upper node, whileduring the day the air exchange with the upper hotter airnode leadto a small overheating compared to the baseline model In the sameway, the depression generated from the air flowing outside instead ofinside in western glazed atrium causes a suction effect for the hot airstocked in the adjacent M_CMA zones, leading to a consequent slightoverheating effect that can bee observed by the lower slope of the tem-perature curve during night ventilation hours in fig. 4.8. In subnet 1

and 2, summer temperatures are decreased respectively of 3.1 °C and2.3 °C for the days shown i fig.n 4.6 - 4.2. Considering the volumes

75

76 results and discussion

of air to cool for each zone (2500 and 3500 m3 respectively) thesetemperature decrease are significant. Tabs. 4.1, 4.2, 4.3, 4.5 showsoverheating degree hour for each zone of the network on a monthlybasis, confronting baseline building with proposed solution. Theseare calculated as sum of all positive differences between Tair,node

and Tset,cool, where Tair,node is the air temperature of the thermalzone while Tset,cool is the cooling set point temperature, assumed 26

°C.

Western Common Area

ODH Western Common Area [K]Baseline Solution difference % diff.

April 0 0 0 0%May 649 325 -324 -50%Jun 2902 1968 -934 -32%Jul 4928 3788 -1140 -23%

Aug 4610 3577 -1033 -22%Sept 1953 1279 -674 -35%Oct 12 1 -10 -89%

Tot 15054 10938 -4116 -27%

Table 4.1: Overheating degree hours (sum of thermal zone temperature de-grees above 26 °C) in the baseline building and in the proposedsolution for western common area

4.1 outcomes 77

Figure 4.1: April to October free running air temperature trend for baseline(blue), proposed solution (red) and outside temperature (green)

Figure 4.2: Free running air temperature trend for baseline (blue) and pro-posed solution (red) in the last three days of July

Eastern Common Area


ODH Eastern Common Area [K]Baseline Solution difference % diff.

April 0 0 0 0%May 98 106 8 8%Jun 1596 1589 -7 0%Jul 3497 3448 -49 -1%

Aug 3756 3597 -159 -4%Sept 1818 1588 -230 -13%Oct 0 0 0 0%

Tot 10765 10328 -437 -4%

Table 4.2: Overheating degree hours (sum of thermal zone temperature de-grees above 26 °C) in the baseline building and in the proposedsolution for eastern common area



4.1 outcomes 79

Northern Common Area

ODH Northern Common Area [K]Baseline Solution difference % diff.

April 0 0 0 0%May 747 293 -454 -61%Jun 3395 2079 -1316 -39%Jul 5441 3941 -1500 -28%

Aug 5282 3837 -1444 -27%Sept 2817 1504 -1313 -47%Oct 55 3 -52 -95%

Tot 17736 11657 -6079 -34%

Table 4.3: Overheating degree hours (sum of thermal zone temperature de-grees above 26 °C) in the baseline building and in the proposedsolution for northern common area




Western Glazed Hallway

Figure 4.7: April to October free running air temperature trend for baseline(blue), proposed solution (red and outside temperature (green)

4.1 outcomes 81

ODH Western glazed hallway [K]Baseline Solution difference % diff.

April 0 0 0 0%May 76 94 17 23%Jun 1236 1403 167 14%Jul 3066 3342 275 9%

Aug 3034 3259 225 7%Sept 1069 1217 148 14%Oct 0 0 0 0%

Tot 8481 9314 833 10%

Table 4.4: Overheating degree hours (sum of thermal zone temperature de-grees above 26 °C) in the baseline building and in the proposedsolution for western glazed hallway


Middle Common Area (HUB zone)


ODH Middle Common Area [K]Baseline Solution difference % diff.

April 0 0 0 0%May 222 116 -106 -48%Jun 2048 1618 -431 -21%Jul 4005 3524 -482 -12%

Aug 4107 3539 -568 -14%Sept 1973 1426 -547 -28%Oct 0 0 0 0%

Tot 12356 10223 -2133 -17%

Table 4.5: Overheating degree hours (sum of thermal zone temperature de-grees above 26 °C) in the baseline building and in the proposedsolution for middle common area



4.1 outcomes 83

4.1.2 Air Changes

A useful indicator of natural ventilation efficiency process is num-ber of hours when air change rate requirements can be met by nat-ural ventilation only. As explained in Chapter 2, each air zone ofthe model needs a specific air mass change to guarantee indoor airquality; for common areas, this limit is fixed to 7.35 kg/hm2 duringopening hours, while 3.05 kg/hm2 for unoccupied hours has beenset to avoid still air (even though ventilation during closing hoursis not mandatory). Fig. 4.11,4.14, 4.17, 4.20, 4.23, report the resultsof this analysis for each area at monthly level. Daytime (openinghours, from 8 a.m to 9 p.m), are distinguished from night time hourswhen ventilation algorithm controls the system (see par. 3.5.4 for con-trol strategies).Fig. 4.12,4.15, 4.18, 4.21, 4.24 depict frequencies of airchanges for each zone during occupied hours from April to October,to be confronted with minimum values from UNI EN 15251 to seepercentage of effective natural ventilation hours in terms of ventila-tion. Note that small percentages in the middle of graphs (highervalues of air changes) are generated by wind based ventilation, whilepeaks on lower values are caused by stack effect ventilation. This facthighlight the need of on-site wind data to assess a reliable study oncooling potential and air changes by natural ventilation. As well asfor peak shaving and cooling efficiency of the process (see par. 4.1.1),results show how some subnetworks work better than other in termof air changes supply. Western glazed hallway is still the less effi-cient subnet, with a mean efficient value of natural ventilation hourof 6% from April to October, while western and eastern common areaworks well especially in September, with a peak of efficiency of 43 %for the both sub-network. This behaviour can be well explained ob-serving that in warmer seasons (spring and fall) outside temperatureis more likely to be inside set points range, so that the windows canbe opened during occupied hours to provide air changes.



Number of occupied Efficient natural Percentagehours ventilation hours %

January 403 0 0.0%February 364 0 0.0%

March 403 0 0.0%April 390 0 0.0%May 403 91 22.6%June 403 67 16.6%July 403 16 4.0%

August 390 25 6.4%September 390 109 27.9%

October 403 82 20.3%November 390 2 0.5%December 403 0 0.0%

Table 4.6: Percentage of occupied hours when minimun ACR requirements(EN 15251) can be met thanks to natural ventilation in northerncommon area

Figure 4.11: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation

4.1 outcomes 85

Figure 4.12: Frequency distribution of air changes provided by ventilationstrategies during occupied hours in northern common area.mmin = 4005 kg/h according to UNI 15251

Figure 4.13: Frequency distribution of air changes provided by ventilationstrategies during night hours in northern common area


Western Common Area






Table 4.7: Percentage of occupied hours when minimun ACR requirements(EN 15251) can be met thanks to natural ventilation in westerncommon area

Figure 4.14: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation inwestern common area

4.1 outcomes 87

Figure 4.15: Frequency distribution of air changes provided by ventilationstrategies during occupied hours in western common area.mmin = 4123 kg/h according to UNI 15251

Figure 4.16: Frequency distribution of air changes provided by ventilationstrategies during night hours in western common area


Eastern Common Area






Table 4.8: Percentage of occupied hours when minimun ACR requirements(EN 15251) can be met thanks to natural ventilation in easterncommon area

Figure 4.17: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation ineastern common area

4.1 outcomes 89

Figure 4.18: Frequency distribution of air changes provided by ventila-tion strategies during occupied hours in eastern common area.mmin = 6401 kg/h according to UNI 15251

Figure 4.19: Frequency distribution of air changes provided by ventilationstrategies during night hours in eastern common area


Western Glazed Hallway






Table 4.9: Percentage of occupied hours when minimun ACR requirements(EN 15251) can be met thanks to natural ventilation in westernglazed atrium

Figure 4.20: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation inwestern glazed atrium

4.1 outcomes 91

Figure 4.21: Frequency distribution of air changes provided by ventilationstrategies during occupied hours in in western glazed atrium.mmin = 6504 kg/h according to UNI 15251

Figure 4.22: Frequency distribution of air changes provided by ventilationstrategies during night hours in western glazed atrium


Southern Shop






Table 4.10: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation insouthern shops

Figure 4.23: Percentage of occupied hours when minimun ACR require-ments (EN 15251) can be met thanks to natural ventilation insouthern shop

4.1 outcomes 93

Figure 4.24: Frequency distribution of air changes provided by ventilationstrategies during occupied hours in southern shop. mmin =

3226 kg/h according to UNI 15251

Figure 4.25: Frequency distribution of air changes provided by ventilationstrategies during night hours in southern shop


4.1.3 Energy Balance

The histograms in fig. 4.26, 4.27 are show the specific energy de-mands (in kWh/m2) for each one of the zones involved in the ventila-tive cooling strategy. For western common area the reduction of cool-ing demand is 11.7 kWh/m2, for northern common area 10 kWh/m2,while for the other zone the reduction is 2.8 kWh/m2 in the hub com-mon area and 4 kWh/m2 in eastern common area. In the westernglazed atrium, where the reduction of cooling demand is only 0.27

kWh/m2. In this case, infiltration losses are higher than the baseline.This happen because TRNflow computes separately ventilation andinfiltration losses, while in the baseline - where TRNflow is off - theseventilation losses take into account also infiltration losses.

Figure 4.26: Specific energy demand for each analysed common area in thebaseline case

Figure 4.27: Specific energy demand for each analysed common area in theproposed solution

4.1 outcomes 95

Fig. 4.28 and 4.29 represent the behaviour of the building in termsof specific energy demand (kWh/m2) at monthly level, both for thebaseline and the proposed solution.

Figure 4.28: Specific energy demand of the whole building in each monthof the year for the baseline case

Figure 4.29: Specific energy demand of the whole building with ventilationstrategy proposed in each month of the year


Fig 4.30 and 4.31 show the decreased total demand for commonareas, both for heating and for cooling needs. Note that the coolingdemand is lowered only by 3.4 kWh/m2yr because 82.7 % of the com-mon areas in the project building are involved in the solution networkfor ventilative cooling, so the efficiency looks diminished by the factthat only four of the eight common areas in the building are directlyaffected by external air changes in natural ventilation strategies.

Figure 4.30: Specific energy demand for each thermal zone function in thebaseline building

Figure 4.31: Specific energy demand for each thermal zone function in theproposed solution

4.1 outcomes 97

4.1.4 Adaptive Comfort Analysis

A comfort analysis has been computed to assess the differences be-tween baseline and solution according to adaptive comfort model ofUNI EN 15251:2008 studied by Nicol & Humphrey (2002). This com-fort model is used to evaluate comfort in naturally ventilated build-ing, and generally in building whose internal climate conditions arecontrolled by passive strategies. It has to be pointed out that adaptivecomfort method was developed analysing surveys and leading exper-iments on comfort satisfaction of people in offices building, dressingand acting differently from occupants of shopping malls.Comfort operative temperature is defined as in equation 4.1

Tcomfort = 0.33 · Trm + 18.8 (4.1)

where

Trm = 0.2 · Ted−1 + 0.16 · Ted−2 + 0.128 · Ted−3 + . . .

• Trm = moving average temperature from previous days

• Ted−n = external average temperature of n day before.

Three comfort categories are identified:

category i High level of expectation, mandatory for spaces occu-pied by sensitive and fragile persons→ Tcomfort ± 2°C

category ii Normal expectaction (80% of user will assert thermalsatisfaction)→ Tcomfort ± 3°C

category iii Moderate expectation, used for existing building →Tcomfort ± 4°C

Results have been represented from October to July - the time pe-riod when natural ventilation strategies are exploitable in this case -comparing Tcomfort with the operative temperature calculated by asimulation in free running mode. Graphs 4.32, 4.34, 4.36, 4.38 depictcomfort in baseline and in proposed solution for common areas northand west.


Tab. 4.11,4.12 and fig 4.33, 4.35 show a number of discomfort hourincrease in August and July, due to higher temperatures of outside air.In October category I is widened of about 20% of the hours, while inMay this percentage is 10%, this happens because warmer monthslike those in spring and fall works best for natural ventilation strate-gies in terms of cooling load reduction, air changes provided andcomfort behaviour as well. Among the rest of the cooling season, thepercentage of hour in each category is not very affected by proposedventilation strategies.


category category category discomfort discomfortI II III too cold too hot

Aprile 16.9% 47.7% 25.4% 3.3% 0.0%Maggio 64.5% 25.2% 9.5% 0.7% 0.0%Giugno 53.3% 20.8% 20.3% 0.0% 5.6%Luglio 6.5% 24.3% 29.3% 0.0% 40.0%

Agosto 5.0% 24.6% 41.7% 0.0% 28.8%Settembre 65.4% 22.8% 7.2% 0.0% 4.6%

Ottobre 52.1% 30.8% 11.1% 5.2% 0.0%

Table 4.11: Percentage of opening hours in each adaptive comfort categoryfor northern common area the baseline building




Ottobre 71.0% 24.2% 3.7% 0.9% 0.0%

Table 4.12: Percentage of opening hours in each adaptive comfort categoryfor northern common area in the solution building

4.1 outcomes 99

Figure 4.32: Operative temperature from April to October in the northerncommon area of the baseline

Figure 4.33: Percentage of opening hours in each comfort category fornorthern common area in the baseline building


Figure 4.34: Operative temperature from April to October in the northerncommon area of the solution building

Figure 4.35: Percentage of opening hours in each comfort category fornorthern common area in the solution building

4.1 outcomes 101

Western Common Area

Fig. 4.37,4.39 and Tab. 4.13, 4.14 show a number of discomforthour increase in August and July, due to higher temperatures of out-side air. In October category I is widened of about 20% of the hours,while in May this percentage is 10%, this happens because warmermonths like those in spring and fall works best for natural ventilationstrategies in terms of cooling load reduction, air changes providedand comfort behaviour as well. Among the rest of the cooling sea-son, the percentage of hour in each category is not very affected byproposed ventilation strategies.




Ottobre 47.3% 27.1% 18.2% 6.5% 0.0%

Table 4.13: Percentage of opening hours in each adaptive comfort categoryfor western common area of the baseline building


Figure 4.36: Operative temperature from April to October in the westerncommon area of the baseline

Figure 4.37: Percentage of opening hours in each comfort category for west-ern common area in the baseline building

4.1 outcomes 103




Ottobre 71.0% 24.2% 3.7% 0.9% 0.0%

Table 4.14: Percentage of opening hours in each adaptive comfort categoryfor western common area of the solution building

Figure 4.38: Operative temperature from April to October in the westerncommon area for the proposed solution


Figure 4.39: Percentage of opening hours in each comfort category for west-ern common area for the proposed solution

4.2 energy consumption 105

4.2 energy consumption

To assess total energy savings we calculated the final energy elec-trical energy for the common areas and for the whole building ex-pressed in [kWh/m2yr] (fig. 4.41, 4.42). It should be noted that wholebuilding charts are weighted on the area of every thermal zone type.

Outputs from the model are represented in terms of useful energy.To convert it into final energy efficiencies of systems are consideredto compute losses in final use and losses in transformation process.The scheme in fig. 4.40 represents the energy transformation processfrom primary energy to final use.

Figure 4.40: Scheme of energy transformation process. source: ecen.com

The systems efficiencies are considered as follows:

Lighting, appliances and refrigeration systems are directly poweredby electricity and transport losses are neglected so efficiency ofthe process is considered 1

losses due to air friction in ventilation ducts and concentrated pres-sure drop in valves, strictions and curves lead to an efficiencyof 0.45 Wh/m3 of air volume supplied.

The air conditioning system has an heat pump COPheat = 2.80 andEERcool = 2.50 which supplies the whole building.has beenconsidered to serve the whole building

The difference in terms of ventilation is really slight (0.3 kWh/m2yr)because common area represents only 6.6% of the total ventilated sur-face of the shopping mall and the strategy implemented is activatedonly when outside air falls inside the setpoints range of temperature,which typically occurs only in middle season. Electricity consump-tion for cooling decreases of 1kWh/m2yr considering common areasonly, and 0.4 1kWh/m2yr considering the whole building.


Figure 4.41: Final energy consumption share for common area/wholebuilding for the baseline model, [kWh/m2yr]

Figure 4.42: Final energy consumption share for common areas/wholebuilding for the proposed solution, [kWh/m2yr]

4.3 discuss on simulations results

Outcomes show that ventilation strategies work well in sub-networknumber 1 and 2 (common areas north and west), where stack ventila-tion is efficient due to the glazed atrium and long vasistas window onskylight’s top. In sub-network 4 (western hallway) simulations sug-gest an unexpected behaviour of overheating instead of cooling in thesolution. Other tests have been tried on the same facade to assess thepossibility to develop a single sided ventilation effect opening ventson the bottom of the glazed modules, or widening the opening factorof vasistas on the top. Both trials led to very small improvement interms of lowering temperatures (0.3°C varying opening factor from0.2 to 0.6), probably due to the overpressure effect already explainedin par. 4.1.1. This example point out well how opening size on fa-cade is not the only parameter controlling the efficiency of naturalventilation because, even if pivoting windows occupy an overall areaof 40 m2 (0.4 m x 100 m), this thermal zone is the one where solu-tion works less (+0.8 °C of overheating in July, in less than 10% ofopening hours air changes can be guaranteed via natural ventilation,even in warm months). Results are encouraging observing that thiscase study was particularly restrained by geometry and orientation of

4.4 model limitations 107

the previous building, and by IAQ issues that limited dimension andposition of air inlet and outlet. For other shopping malls, a similaranalysis shall lead to better results if roof level could be exploited forwind catcher placement or bigger opening area for inlet vents couldbe installed in the underground level for ground coupled ventilation.Finally, the position of Officine Guglielmetti, on the bank of Bisagnoriver aligned in the direction of the valley, suggests that outcomescould be enhanced if local wind data would be used instead of winddata from the airport.

4.4 model limitations

In this section we discuss the limitation of the model and the as-sumptions made to simplify the real building into a thermal model

4.4.1 Thermal zoning

Airflow networks are lamped parameters model and assume the airvolume within the zone as well mixed. This assumption can be validfor zone with ceiling height up to 3 meters. Air temperature strati-fication in atria can be estimated only by dividing the volume intomore air nodes and connect them through resistances which are notpresent in the real building. Furthermore, geometry simplification inthermal zoning takes to neglecting additional resistances in commonareas, for example in the hub thermal node two shops placed in themiddle of the common area have been neglected or the widening atthe end of northern common area has not been considered so that itsair flows only to western common area. Probably other temporaryshops will be built in the middle of hallways, offering an additionalresistance to the air flow and additional thermal capacitance that hasnot been considered in this model.

4.4.2 Mechanical Ventilation

The temperature of the air supplied by the mechanical system tothe model is assumed to be always the same as outdoor air. Therefore,air preheating due to the flow within the air ducts in the building isneglected which results in overestimation of heating consumption.


Figure 4.43: Neglected obstacles and shapes in thermal zoning modelling

4.4.3 Weather Data

Wind data have been selected from Genoa’s airport, that is not farfrom the building site but with a totally different topographic config-uration of surrounding terrain. The new shopping mall will rise nextto the bank of Bisagno river, in a valley with its own peculiar windpattern which can be significantly different from those measured atthe airport.

Figure 4.44: Position and distance from weather station to building site

5 S U M M A R Y

In this work we studied the performance of a commercial buildingthrough modelling and dynamic simulation in TRNSys. The finalaim was to reduce cooling demand and mechanical ventilation usethrough the development of a natural ventilation strategy. The studyhas been focused on common areas and hallways for these reasons:

Shops tenants controls their own set-point temperatures so itwould not be possible to have a fixed range for HVAC systemsactivation

Hallways offer small resistance to streaming air due to lack ofobstacles and big volumes (meaning small friction losses)

Big volumes of air in common areas enhance stratification andimproves the efficiency of stack effect natural ventilation

An airflow network was modelled using TRNFlow to assess efficiencyof two main schemes: a ground coupled ventilation in the eastern fa-cade and a stack effect on the western glazed atrium of the building.Results show reductions of 12.94 MWh/year for final energy ventila-tion and 9.4 MWh/year of final energy for cooling, with a shavingof peak energy consumption for cooling of 2.0%. The contribution ofimplemented systems is modest if compared with final energy con-sumption of the whole building (2680 MWh/year), due to the factthat the common areas (directly involved in the strategies) representonly 12.2% of total cooled area and 6.64% of total ventilated area ofthe mall. Moreover, the adopted control algorithm activates naturalventilation only in warm and summer months, while air supplieshave to be granted for the whole year during occupied hours. Thenfor ventilation purposes the solution is activated only for 58% of thetime (from April to October), and for 6.64 % of space (fraction ofhallway area over building’s total ventilated area).

109

110 summary

Percentage of hours exceedingminimum ventilation rates

via natural ventilation strategies

Opening hours Night-timeNorthern common area 14% 82%

Western common area 23% 83%Eastern common area 5% 28%

Glazed hallway 6% 27%Southern shops 17% 77%

Table 5.1: Percentage of opening/night hours when air changes providedby natural ventilation exceeds minimum requirement of ISO EN1521, in time period from April to June

CDH differences between baseline building and proposed solution

Northern Western Eastern Western Middlecommon common common common common

area area area area area[K] [K] [K] [K] [K]

April 0 0 0 0 0

May -454 -324 8 17 -106

Jun -1316 -934 -7 167 -431

Jul -1500 -1140 -49 275 -482

Aug -1444 -1033 -159 225 -568

Sept -1313 -674 -230 148 -547

Oct -52 -10 0 0 0

Tot -6079 -4116 -437 833 -2133

Table 5.2: Cooling degree hours difference between baseline building andproposed solution

summary 111

Frequencies analysis of air changes shows that cooling effect andACR are strictly related. In northern and western common area,where the reduction of overheating degree hours is 34% and 27%respectively, air change rates can be provided for 1/7 to 1/6 of to-tal opening hours via natural ventilation (see tab. 5.1). In the sameareas, percentage of opening hours in comfort category I is widenedby up to 23% in warm months, when outside air temperature is morelikely to fall inside set-point range. In western glazed facade the airflows out from vasistas windows instead of streaming in, causing asuction effect for the air of adjacent nodes. This leads to a slight over-heating of the zone (+833 ODH from April to October ) and a poorventilation effect (only in 6 % of total opening hours air changes canbe provided by mean of natural ventilation in this zone). A similareffect happens in eastern common area during occupied hours, but inthis case the overheating effect is due to air exchange with upper ther-mal node. Opening area of inlets could not be enlarged to solve thisissues, because parking on the roof and at ground floor bounded thepositions and dimensions of air vents due to air quality issues. Archi-tectural aesthetic needs excluded the possibility to use solar chimneysor wind catcher as ventilation effect booster. Furthermore, since thiscase study is a retrofit of an existing building, orientation and perime-ter of the storeys had to be aligned to the previous values (long axeon north-south measures about 350 meter and short axe on east-westdirection measure 90 meters), leading to poor employability of windbased ventilation strategies. In cross ventilation for example, air max-imum accessible depth is 5 times the height of the ceiling, so in thiscase no more than 40 meters. Even if solution strategies for this democase were quite limited for the reasons shown above, results showhow natural ventilation strategies can be exploited in shopping mallsto lower power peaks, energy consumption and to enlarge comfortrange. Detailed data for building simulations are crucial to obtain re-liable outputs, but deadlines and costs must be considered too in pre-liminary feasibility analysis like this case study. The applied methodcould be used to analyse potential savings of other commercial struc-tures as well as for building with similar occupancy schedule andoccupants behaviour (i.e museums).1

1 “The research leading to these results has received funding from the European Com-munity Seventh Framework Programme (FP7/2007-2013) under grant agreement n°608678”

112 summary

further developments

IAQ: indoor air quality of internal environment has not been anal-ysed; even if strategy in eastern common area was developed toprevent pollution, it should be assessed if pollutants from un-derground parking lots could get inside the commercial storeyduring.

Weather data: a local weather station is recommended to be installedon the building site to obtain specific data on wind speed anddirection and reliable outcomes of simulations.

Control Strategy: the adopted algorithm could be refined to workmonthly instead of on a yearly base, with a wider or tighterrange of set-point temperatures depending on the season. Newsimulations with ventilation strategies adopted only in springand fall could outline better performances of the whole system.Weather forecast could be implemented in the iBEM system ofthe mall to obtain a weather dynamic control algorithm.

B I B L I O G R A P H Y

[1] CIBSE Briefing 07. “Refurbishment for improved energy effi-ciency:an overview”. In: CIBSE Knowledge series (2007) (cit. onp. 7).

[2] S. Holst M. Hille A. Weber M. Koschenz. “TRNFLOW: Integra-tion of COMIS into TRNSYS TYPE 56”. In: 23rd AIVC and EPIC2002 Conference "Energy efficient and healthy buildings in sustain-able cities (2002) (cit. on p. 74).

[3] Pless et al. “Cherry Picking Versus Multiple Measures”. In: NR-CAN Archive (2011). url: https://www.nrcan.gc.ca/energy/publications/efficiency/buildings/6565 (cit. on p. 7).

[4] Apeatse Amos-Abanyie Koranteng. “An evaluation of the ef-fects of external landscaping elements on indoor airflow rateand patterns using CFD”. In: European Scientific Journal 10 (2014)(cit. on p. 26).

[5] Richard Aynsley. “Natural Ventilation in Passive Design”. In:BEDP Environment Design Guide Tec2 (2007) (cit. on pp. 21, 33).

[6] A. Daoud M. Hiller B.Delcroix M.Kummer. “Improved conduc-tion transfer function coefficients generation in Trnsys multi-zone building model”. In: Proceedings of 13th Conference of In-ternational Building Performance Simulation Association (2013) (cit.on p. 74).

[7] Raphael Bointner and Agne Toleikyte. “Deliverable 2.1, Shop-ping Malls Features in EU28+Norway”. In: CommONEnergy (2014)(cit. on pp. 2, 4).

[8] McGraw-Hill Construction. “Green Building Retrofit & Renova-tion”. In: SmartMarket Report (2009) (cit. on p. 8).

[9] Daniel Cash Shaun Fitzgerald Gwilym Still David Hamlyn PhilipArmitage. “Ventilation Approaches for Shopping Malls: An Ex-amination of Natural and Hybrid Strategies”. In: ASHRAE Trans-actions 118 (2012) (cit. on p. 16).

[10] Donna Cooper Richar de Dear Gail Brager. “Developing anAdaptive Model of Thermal Comfort and Preference”. In: (1997)(cit. on p. 10).

[11] Scott Koszalinski Detlef Westphalen. “Energy Consumption Char-acteristics of Commercial Building HVAC System”. In: ASHRAETransactions II : Thermal Distribution, Auxiliary Equipment andVentilation (1999) (cit. on pp. 14, 15).

113

https://www.nrcan.gc.ca/energy/publications/efficiency/buildings/6565

https://www.nrcan.gc.ca/energy/publications/efficiency/buildings/6565

114 Bibliography

[12] IDES EDU. “Mechanical Ventilation”. In: Educational PackageVentilation Lecture III (2011) (cit. on p. 17).

[13] Harper Joy Kanowski Mackay McKenzie Hatton Cork. “Stateof the environment report”. In: Proceedings of 13th Conference ofInternational Building Performance Simulation Association (2007).

[14] Inslington. “Low Energy Cooling”. In: Good Practice Guide 5

(2012) (cit. on pp. 30, 32).

[15] SJ Emmerich JW Axley. “A Method to Assess the Suitability ofa Climate for Natural Ventilation of Commercial Buildings”. In:Proceedings Indoor Air (2002) (cit. on pp. 40, 43).

[16] J. Fergus Nicol Kathryn J. McCartney. “Developing an adaptivecontrol algorithm for Europe”. In: Energy and Buildings 34 34

(2006), pp. 623–635 (cit. on pp. 10, 21, 32).

[17] R.B.Stull. “An introduction to boundary level meteorology”. In:Kluwer Academic Publishers (1988) (cit. on p. 26).

[18] Kristian Stenerud Skeie Matthias Haase Ruth Woods Sofie Mell-gard. “Deliverable 2.2, Shopping Malls Inefficiencies”. In: Com-mONEnergy (2014) (cit. on p. 7).

[19] “Use narrow floor plates for access daylight, views and naturalcooling”. In: Green Buiding Design & Construction Guidelines SF1

(1999) (cit. on p. 29).

natural ventilation strategies for shopping malls retrofit: a case

Documents