Smart Buildings: ICT as a driving energy-efficient solution for retrofitting of existing buildings

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DEGREE PROJECT ENERGY AND ENVIRONMENT, SECOND CYCLE, 30 CREDITS

STOCKHOLM SWEDEN 2018,

Smart Buildings: ICT as a driving energy-efficient solution for

retrofitting of existing buildings

GIUSEPPE SGRÒ

KTH ROYAL INSTITUTE OF TECHNOLOGY

SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT

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Smart Buildings: ICT as a driving energy-efficient solution for retrofitting of existing buildings

Giuseppe Sgrò

Master of Science Thesis

KTH School of Industrial Engineering and Management Energy Technology

SE-100 44 STOCKHOLM

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Master of Science Thesis TRITA-ITM-EX 2018:725

Smart Buildings: ICT as a driving energy-efficient solution for retrofitting of existing buildings

Giuseppe Sgrò

Approved

2018-10-31

Examiner

Prof. Joachim Claesson

Supervisor

Dr. Marco Molinari

Commissioner Contact person

Abstract

It is widely recognized how energy efficiency can contribute to decreasing GHG emissions, especially in the building sector, where buildings will play an increasingly important role for the future energy system, being both the largest energy consumers and becoming one of the greatest producers of renewable energy.

In this new energy context, where renewable sources will be the main supplier for the production of electricity, there will be a growing need for dynamic control as well as intelligent and interconnected systems, which will lead to the creation of a new ICT architecture based on the interaction between Smart Buildings and Smart Grid, where buildings will take the role of proactive participants in the smart electricity network, facilitating the reduction of energy consumption and GHG emissions as well as other societal benefits.

However, in order to fully reach the ICT architecture model and at the same time achieving the energy savings targets, the main effort should be pointed towards the existing building stock, since it represents the urban dwelling type with the lowest energy efficiency and therefore it should be upgraded to the extent possible into an energy efficient smart building stock.

The aim of the thesis is to identify and analyse the potential energy saving which can be obtained through ICT solutions in an existing Swedish single-family household built during the

‘record years’ (1961-1975), without the need for extensive change or renovation.

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In a first place, it will be created the building energy model representative of the Swedish residential building stock built between 1961 and 1975. This energy model will be defined according to the European project TABULA and based on secondary data sources.

Then, the potential energy saving will be identified through the IDA ICE software, in which it will be analyzed the most energy-efficient combination of smart controls and connected devices to achieve energy performance improvement, under a set of constraints and limitations.

Finally, this energy saving, obtained merely through the introduction of ICT technologies, will be complemented with on-site renewable source generation.

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Sammanfattning

Det är allmänt vedertaget att effektiv energianvändning kan bidra till minskade koldioxidutsläpp, framför allt inom byggsektorn. Påverkan från byggnader väntas öka i framtidens energisystem där de både är de största konsumenterna och är på god väg att bli de största producenterna av förnybar energi.

I denna nya kontext, där förnybara källor blir de största leverantörerna av el, kommer det skapas ett växande behov av dynamisk kontroll såväl som smarta och sammanlänkade system. Det kommer i sin tur leda till skapandet av ny ICT-arkitektur som grundar sig i interaktionen mellan så kallade Smart Buildings och Smart Grid, där byggnader antar en mer proaktiv roll i det smarta elnätet vilket möjliggör minskad energikonsumtion och minskade utsläpp av växthusgaser, bland andra samhälleliga fördelar.

För att uppnå den framtida modellen för ICT-arkitektur fullt ut samtidigt som målsättningen för energisparande bibehålls, behöver dock den huvudsakliga satsningen ägnas åt befintliga byggnader. Befintliga byggnader utgör den andel urbana bostäder med lägst energiprestanda, därför bör de i största möjliga grad uppgraderas till att möta målbilden av energieffektiva smarta byggnader.

Arbetet ämnar identifiera och utvärdera den potentiella energibesparingen som kan uppnås genom ICT-lösningar i befintliga svenska enfamiljshus, byggda under Rekordåren (främst 1961 till 1975), utan omfattande förändringar eller renovering.

I första hand framförs en modell som visar energibehovet av de svenska bostadshusen byggda mellan 1961 och 1975. Modellen definieras enligt det europeiska projektet TABULA och baseras på sekundära datakällor.

Därefter identifieras den potentiella energibesparingen med hjälp av mjukvaran IDA ICE, där den mest energieffektiva kombinationen av smarta kontrollanordningar och sammanlänkad utrustning för att uppnå en förbättrad energiprestanda fastställs under framförda bivillkor och avgränsningar.

Slutligen kombineras energibesparingen som uppstår genom ICT-teknologi med tillbyggnaden av förnybara energikällor.

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Acknowledgements

I would like to express my sincere gratitude to my supervisor Dr. Marco Molinari for the continuous support of my thesis study. He has been always available whenever I ran into a trouble spot or had a question about my research, and he allowed me to work on my ideas, steering me in the right direction whenever he thought I needed it.

Besides my supervisor, I would also like to thank Prof. Joachim Claesson as the examiner of this thesis, and I am deeply grateful for his availability and very valuable comments.

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List of Figures

Figure 1. The share of global energy-related CO2 emissions by sector in 2015 (Adapted from UNEP,

2017) ... 17

Figure 2. The share of global final energy consumption by sector in 2015 (Adapted from UNEP, 2017) 18 Figure 3. Total final energy use by sector in Sweden (1970-2016) (Adapted from Swedish Energy Agency, 2018b) ... 19

Figure 4. Distribution of different sub-sectors energy use in the residential and service sector in Sweden in 2015 (Adapted from Swedish Energy Agency, 2018a) ... 20

Figure 5. Final energy use in the residential and services sector by subsector in Sweden (1984-2016) (Adapted from Swedish Energy Agency, 2018b) ... 20

Figure 6. Energy used for heating and DHW in SFH and Multi-dwelling buildings in Sweden in 2015 (Adapted from Swedish Energy Agency, 2018a) ... 21

Figure 7. Number of dwellings by type of building and period of construction in Sweden (Adapted from Swedish Energy Agency, 2018c) ... 22

Figure 8. Environment - CO2e abatement potential by sector within 2030 (Adapted from GeSI, 2015). .. 30

Figure 9. Environment - CO2e abatement potential by use case within 2030 (Adapted from GeSI, 2015). ... 31

Figure 10. ICT infrastructure (Adapted from Morán et al., 2016). ... 36

Figure 11. Feedback control scheme (Adapted from Aste, Manfren and Marenzi, 2017). ... 38

Figure 12. "Building Type Matrix" – classification of the Swedish housing stock (Reproduced from TABULA Project Team, 2012) ... 43

Figure 13. Climate Zone in Sweden (Reproduced from Mälardalens University, 2012) ... 44

Figure 14. North-East façade of the Single-Family House (IDA ICE 4.8)... 45

Figure 15. South-West façade of the Single-Family House (IDA ICE 4.8) ... 45

Figure 16. The first floor of the Single-Family House (IDA ICE 4.8) ... 46

Figure 17. The second floor of the Single-Family House (IDA ICE 4.8) ... 46

Figure 18. Delivered energy demand for heating and DHW (KWh/m²) in TABULA reference model ... (Adapted from TABULA WebTool, 2017) ... 54

Figure 19. Overall used energy system by month (Base Model)... 55

Figure 20. Monthly Used Energy for cooling, heating and DHW (Base Model) ... 55

Figure 21. Control strategy lighting system ... 58

Figure 22. Control strategy electric radiators system ... 60

Figure 23. Control strategy shadings system ... 62

Figure 24. Overall used energy system by month (ICT control system) ... 69

Figure 25. Monthly Used Energy for cooling, heating and DHW (ICT control system) ... 70

Figure 26. PV generated electric energy per month ... 73

Figure 27. Monthly Purchased/Sold Energy ... 73

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List of Tables

Table 1. Thermal transmittance of the elements of Construction ... 48

Table 2. Equipment internal gains ... 49

Table 3. Heating power design of the electric radiators ... 51

Table 4. Air supply and return for each room ... 52

Table 5. Delivered energy overview (KWh/m²) in the IDA ICE Base Model ... 54

Table 6. Rooms Temperature and CO2 levels in the IDA ICE Base Model ... 56

Table 7. Delivered energy for Lighting System Control ... 58

Table 8. Rooms Temperature and CO2 levels Lighting Control Strategy compared to Base Model ... 59

Table 9. Delivered energy for Electric Radiators System Control ... 60

Table 10. Rooms Temperature and CO2 levels Electric Radiators Control Strategy compared to Base Model ... 61

Table 11. Delivered energy for Shadings System Control ... 63

Table 12. Rooms Temperature and CO2 levels Shading Control Strategy compared to Base Model ... 63

Table 13. Delivered energy for Ventilation System Control ... 65

Table 14. Rooms Temperature and CO2 levels Ventilation Control Strategy compared to Base Model ... 66

Table 15. Rooms Temperature and CO2 levels of ICT Control System compared to Base Model ... 68

Table 16. Annual delivered energy overview of ICT Control System compared to Base Model ... 69

Table 17. Design of the PV system ... 71

Table 18. Annual energy overview of a PV system facing South ... 72

Table 19. Annual energy overview of a PV system facing West ... 74

Table 20. Annual energy overview of a PV system facing East... 74

Table 21. Annual PV generated energy (South-West-East) ... 75

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1. Introduction

1.1. Context of the study

The EU has set the long-term goal of decreasing GHG emissions within 2050 by 80-95%

compared to 1990 levels (European Commission, 2012). This objective is far more ambitious than the 20% reduction embodied in the well-known 20-20-20 target.

Therefore, in order to achieve the 2050 goal, significant investments will be needed in the whole energy system, which will target the use of new low carbon technologies, renewable energy deployment, and improvement of energy efficiency (European Commission, 2013).

Among all these objectives, the main focus should go to the energy efficiency, as its improvement is a priority in all decarbonisation scenarios.

Especially in the building sector, greater energy efficiency in new and existing buildings is essential to achieve the goal of having nearly zero-energy buildings (nZEB) as the standard buildings in the future.

Whatever the way forward, scenarios show that the energy fuel mixes will change substantially in the next years and it will depend, mainly, on the acceleration of technological development (European Commission, 2012).

Technological innovation will bring new possibilities and new options for the future. In particular, digitalization is providing new opportunities for combined solutions in which energy efficiency and renewable energy will work together in order to provide clean energy results at the lowest cost (IEA, 2017b).

Moreover, new digital technologies will play an increasingly important role throughout the energy supply chain. In this new energetic context, where renewables will be the main provider for the electricity generation, there will be a growing need for intelligent and interconnected systems, offering new functions to the user and modifying completely the concept of the city, which will be upgraded to a so-called “smart city”.

According to the United Nations (2015), cities occupy only 2% of the Earth's land but represent 60-80% of energy consumption and 75% of carbon emissions. Furthermore, 70-80% of these emissions come from buildings (Morvaj, Lugaric, and Krajcar, 2011), so it is evident their role when it comes to reducing energy consumption and achieving climate change goals.

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In fact, as stated by Wurtz and Delinchant (2017), buildings are both the largest consumers of energy in the electricity grid and they are going to be among the major producers of renewable energy.

This transition to a more sustainable energy grid based on renewable energy sources will require more dynamic control to compensate for the uncertainty and volatility of wind and solar energy.

Furthermore, through advanced information and communication technologies, consumers will be able to participate actively in monitoring and controlling their energy consumption (Spataru and Barrett, 2013).

The current electricity network treats buildings as isolated and passive units (Kok, et al., 2009), but in order to reach energy savings targets, current buildings need to be upgraded to the so- called “smart buildings” which will be able to communicate with their surroundings (Morvaj, Lugaric, and Krajcar, 2011).

The goal is to create a new ICT architecture based on the interaction between Smart Buildings and Smart Grid (Kok, et al., 2009), where buildings have to become proactive participants in the smart electricity network (Warmer, et al., 2009), facilitating the reduction of energy consumption.

However, in order to fully reach the ICT architecture model and at the same time achieving the energy savings targets, besides the development of new smart buildings characterized by low energy demand and renewable energy generation, the main effort should be pointed towards the existing buildings stock (D'Agostino, Cuniberti and Maschio, 2017).

European cities are mostly composed of inefficient residential buildings, whose energy demand can even exceed 200 kWh/m² per year (Gonzalez, et al., 2016).

The European Union Directive on the energy performance of buildings (European Union, 2010) stated that about 40% of energy consumption in Europe is due to buildings (Patti, et al., 2014), making the building stock responsible for 36% of the total EU CO2 emissions (D'Agostino, Cuniberti and Maschio, 2017).

Approximately 97% of the European Union’s building stock is not considered energy efficient (less than 3% of the building stock in the EU qualifies for an A-label¹) (BPIE, 2018a) and 75- 90% of those standing today will still be in use in 2050 (European Commission, 2015).

1 Label A is viewed as ‘very efficient’ building in every country, but requirements and calculation methods for EPCs differ among countries, e.g. for Germany very efficient is 50 kWh/m² (BPIE, 2017).

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While new buildings can be designed and constructed to be able to produce homes with lower energy use, the biggest impact on the energy demand can be made by improving the energy inefficient existing building stock (Gonzalez, et al., 2016).

In this context, with low demolition rates (0.1% per year) and low refurbishment rates (1.2% per year), the EU must increase the number of deep renovations (savings of 60% or more) and accelerate the rate of retrofitting of existing building stock by more than 2% per year (European Commission, 2015).

The recognition of retrofitting solutions has risen over the last years and several retrofit definitions have been introduced (e.g. minor, deep, major and NZEBs renovation), aiming to reduce energy consumption through a combination of efficient technologies, controls, renewable energy, windows and envelope solutions (D’Agostino, Cuniberti and Maschio, 2017).

Although deep energy renovation will take precedence in the coming years, its development will keep going slowly, mainly because of the initial costs of deep envelope improvements and the absence of incentives to increase the energy performance of buildings (IEA, 2017a).

Therefore, system optimization through improved controls will be able to offer significant energy savings, becoming the alternative to energy reductions due to improvements in building envelopes and equipment. Savings can vary between 15% and 50%, depending on the control technology (Grözinger et al., 2017 cited in IEA, 2017a, p.137).

The importance of improved controls and ICT is also supported significantly by the European Union, which has declared the following (Patti, et al., 2014): “Information and Communication Technologies have an important role to play in reducing the energy intensity and increasing the energy efficiency of the economy, in other words, in reducing emissions and contributing to sustainable growth”.

In conclusion, in order to develop effectively the concept of the smart city, existing buildings which account for most of the building stock with the lowest energy efficiency (BPIE, 2011) should be upgraded as much as possible into energy efficient buildings (Patti, et al., 2014). With their potential of providing high energy performance and CO2 savings as well as other societal benefits, smart buildings thanks to the deployment of Information and Communication Technologies will play a key role for a sustainable future (BPIE, 2011).

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1.2. Statement of the problem

The building sector has a significant impact on world energy demand: it accounts for almost 55% of global electricity demand and 36% of the world's final energy consumption. In addition, it plays an important role in climate change, since buildings are responsible for almost 40% of global energy-related CO₂ emissions (UNEP, 2017).

Therefore, in order to reach an energy-efficient world, governments, businesses and individuals need to transform the building sector through a multitude of actions, including increasing global energy awareness (WBCSD, 2009). In this context, the EU has committed to reducing greenhouse gas emissions to 80-95% below 1990 levels within 2050 (European Commission, 2012).

However, despite the aforementioned goal, studies conducted by the OECD (Organisation for Economic Cooperation and Development) indicate that energy consumption by the building sector in the OECD countries has continually increased since the 1960s and will continue to do so in the coming years (WBCSD, 2009). Moreover, 75-90% of those standing today are expected to still be in use in 2050 (European Commission, 2015), given that the construction rate is overall low (BPIE, 2017) with low demolition rates (0.1% per year) and low refurbishment rates (1.2% per year) (European Commission, 2015). Therefore, these numbers might be expected also in Sweden where the residential sector has a construction rate yearly of around 1.3%, with one-two dwelling buildings at a rate of nearly 0.6% (SCB, 2018a and 2018b).

Considering that about 84% of total building energy (WBCSD, 2007) is typically consumed during the operational phase (assuming a building life of more than 50 years), there is an opportunity to significantly improve the energy performance of the existing building stock and, at the same time, the quality of living conditions of people (BPIE, 2018a).

This opportunity consists of technological innovation, which in the building sector is depicted by ICT that will play a key role in the future energy transition. According to IEA (UNEP, 2017), ICT could allow 230 EJ of cumulative energy savings to 2040, reducing the energy consumption of buildings worldwide by up to 10% while improving thermal comfort and delivering greater service to occupants.

Thus, there is a need to examine and concretely analyze the potential energy saving obtained through ICT in the building sector and this proposed research seeks to develop it through a case study of an existing building.

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1.3. Aim and scope

The concept of today's cities has changed over the years. It is estimated that in 2050 almost 80%

of the world's population will live in cities (United Nations, 2015). Cities will become the key to achieving energy and climate goals, whose biggest participants will be the so-called “smart buildings” that through advanced Information and Communication Technologies (ICTs), are going to be seen as the key players rather than isolated and passive units.

However, given the low renewal rate of the building sector, the main focus to achieve the transition to smart buildings of tomorrow should be addressed to the existing building stock.

To this end, assuming that future cities will be shaped entirely by smart buildings, what is the mere contribution that ICT potential can provide in reducing energy consumption in buildings?

The aim of the thesis is to identify and analyze the potential energy saving which can be obtained through ICT solutions in an existing Swedish single-family household (SFH) built during the ‘record years’ (1961-1975), without the need for extensive change or renovation.

This total potential energy saving achieved through ICT will be the combination of two systems:

control and measurement of internal loads which can reduce the internal energy consumption of SFH and, secondly, by the production of renewable energy generation on site, since ICT will enable the full integration with the smart grid.

However, the maximum potential energy saving is limited by the optimal indoor temperature and maximum CO2 level requirements recommended by secondary data sources for the various rooms of the building (daylight requirements have not been taken into consideration).

Moreover, the study scope is delimited to the existing Single-Family building stock in Sweden with a particular emphasis on the buildings constructed during the ‘record years’, as it is the period when there was the largest construction in Sweden and whose houses have undergone retrofitting interventions in the last years. Therefore, it will be analyzed the most representative SFH based on TABULA parameters, limiting the building model of the overall Swedish residential building stock.

Electricity is the most common form of energy used in Swedish single-family houses, therefore the potential energy analysis will focus mainly on electrical savings, assuming that heating, cooling and DHW needs are provided electrically.

Environmental impact and cost analysis are considered outside the scope of this study.

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1.4. Significance of the study

According to the European Commission (2010), the building sector will be one of the key enablers for achieving the European decarbonisation goal by 2050. In line with this objective, the European Union has launched a multi-annual roadmap for the years 2014-2020 with the aim of facilitating the road to future smart cities. The vision for this roadmap states: “By 2050, most buildings and districts could become energy neutral, and have a zero CO₂ emission. A significant number of buildings would then be energy positive, thus becoming real power plants, integrating renewable energy sources, clean distributed generation technologies and smart grids at district level” (European Commission, 2010).

However, in order to achieve the roadmap vision and the European decarbonisation goal, the greatest effort is represented by the energy inefficiency of the existing building stock, considering that in Europe around 80% of the expected building stock in 2030 is already standing today (European Commission, 2010).

Although there are other methods to improve buildings energy efficiency, such as renovation/refurbishment or use of high-efficiency equipment (Morán, et al., 2016), it is expected that the reduction of energy use through ICT systems will be around 15% in the next years (European Commission, 2009).

Furthermore, building envelopes retroﬁtting solutions are not always economically viable for energy consumption reduction in existing buildings (Aghemo, et al., 2013), as supported by the REEB project in which a key stakeholder Jean-Yves Blanc (Senior Vice President of Schneider Electric) has stated: “Building automation and controls are most effective to enable energy savings in the building sector. Technical building equipment and controls have an average payback period shorter than 10 years. Insulations, windows, etc. have an average payback period longer than 10 years“ (Hannus, Samad, and Zarli, 2010).

Therefore, the findings of this cross-disciplinary research will allow a theoretical and practical multilevel knowledge useful to the whole community, considering that energy and technology will play an increasingly important role in our modern society.

On a theoretical level, one intended outcome of the study is to show which are the steps to be taken in order to achieve the future smart buildings integrated into the smart electricity network and identify optimal solutions to reduce energy consumption in existing buildings.

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A second intended outcome of the study, on a practical level, is to determine quantitatively the potential energy saving that can be achieved with the implementation of simple controls in an existing building, paving the way for further case studies.

1.5. Research approach

In order to answer the research question, two subsequent methods will be applied.

First, it will be created the building energy model representative of the Swedish residential building stock built during the ‘record years’ (1961-1975). This energy model will be defined according to the European project TABULA and based on secondary data sources.

Then, the potential energy saving will be identified through the IDA ICE software in which it will be analyzed the most energy-efficient combination of smart controls and connected devices to achieve energy performance improvement. Energy saving, obtained merely through the introduction of ICT technologies, will be complemented with on-site renewable source generation.

However, some limitations have to be pointed out regarding the computational model developed in IDA ICE.

The representative building has been modelled through TABULA, which provided the thermal transmittance values of some parts of the building and its total estimated energy consumption, and no physical measurements have been used. Other parameters useful for the base model of the building are based on secondary data sources and the background study conducted for a single-family household in Sweden.

Furthermore, the study will not go into detail on how the ICT system is built and developed, as it would shift the focus of thesis, hence a general description of the ICT system will be just provided. For this reason, only simple controllers will be used in IDA ICE, without having made an economic analysis of the products.

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2. Background

2.1. Climate change and Energy Savings in buildings

According to UNEP (2017), buildings are responsible for almost 40% of global energy-related CO2 emissions. While buildings construction accounts for 11% of energy-related CO2 emissions, more than one-quarter (28%) are represented by accounting for the upstream energy production (Figure 1).

Figure 1. The share of global energy-related CO2 emissions by sector in 2015 (Adapted from UNEP, 2017)

Despite huge efforts to reduce CO2 emissions globally, the buildings sector is failing to meet its environmental targets. CO2 emissions from buildings and construction have increased by about 1% per year between 2010 and 2016, releasing 76 GtCO2 in cumulative emissions during this period (UNEP, 2017).

The International Energy Agency (IEA) has called for an overall reduction of 48 Gt in carbon emissions below business-as-usual (BAU) emissions for all sectors by 2050 (IEA, 2008), where buildings are responsible for about 18.2 Gt of this 48 Gt reduction.

Furthermore, the building sector has a significant impact on world energy demand: it accounts for around 36% of the world's final energy consumption (Figure 2). According to UNEP (2017), the global building sector consumed about 30% (125 EJ) of global final energy use in 2016, while the building construction, including the production of building materials, represented a further 6% (26 EJ).

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Moreover, buildings and construction account for almost 55% of global electricity demand (UNEP, 2017) up from 48% in 1990 (IEA, 2017a).

Figure 2. The share of global final energy consumption by sector in 2015 (Adapted from UNEP, 2017)

Of the total building sector (30%), the residential sub-sector accounts for about three-quarters of buildings energy use (73.33%) and its energy demand has increased globally by 30% between 1990 and 2014 (IEA, 2017a).

According to IEA (2017a), the global trend is that buildings will continue to represent a growing energy demand, which could increase to more than 160 EJ in 2060 if no decisive action is taken to improve the energy performance of buildings.

Moreover, nearly 97% of the European Union’s building stock is not considered energy efficient (less than 3% of the building stock in the EU qualifies for an A-label²) (BPIE, 2018a) and 75- 90% of those standing today will still be in use in 2050 (European Commission, 2015).

Therefore, immediate steps must be taken to improve the energy efficiency of the existing building stock and address the energy demand of the buildings asset (IEA, 2017a).

2 Label A is viewed as ‘very efficient’ building in every country, but requirements and calculation methods for EPCs differ among countries, e.g. for Germany very efficient is 50 kWh/m² (BPIE, 2017).

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In order to meet its climate and energy targets, the EU has released the 2020 package, which sets three key targets: 20% cut in greenhouse gas emissions (from 1990 levels), 20% of EU energy from renewables, 20% improvement in energy efficiency (European Commission, 2007).

Sweden has gone even further (UNEP, 2017) and has already exceeded its target of 50% of its total energy needs from renewable energy sources in 2012 (Eurostat, 2016).

In 2016, the total final energy use amounted to 375 TWh, which is a slight reduction compared to 2012 (377 TWh). As shown in Figure 3, the industrial sector accounted for 142 TWh, the transport sector amounted to 87 TWh, and the residential and service sector accounted for 146 TWh, which represents almost 40 per cent (38.93%) of Sweden's total energy use (Swedish Energy Agency, 2018b).

Figure 3. Total final energy use by sector in Sweden (1970-2016) (Adapted from Swedish Energy Agency, 2018b)

Residential and service subsectors (Figure 4) consist of households (87 TWh) which represents almost 59%, commercial (29 TWh), public administrations (16 TWh), agriculture (7 TWh), construction (5 TWh), forestry (2 TWh), and fishing (1 TWh) (Swedish Energy Agency, 2018b).

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Figure 4. Distribution of different sub-sectors energy use in the residential and service sector in Sweden in 2015 (Adapted from Swedish Energy Agency, 2018a)

Figure 5 shows the final energy use in the residential and services sector between 1984 and 2016, and how household subsector has accounted for the major part of energy consumption in this sector (Swedish Energy Agency, 2018b).

Figure 5. Final energy use in the residential and services sector by subsector in Sweden (1984-2016) (Adapted from Swedish Energy Agency, 2018b)

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Households subsector, in turn, splits up into single-family houses (correspond to detached houses and terrace houses) and multi-dwelling buildings (correspond to apartments).

Figure 6 shows the energy use for heating and DHW in single-family houses and multi-dwelling building, in which electricity represents the most common form in single-family houses, whose consumption totalled 14 TWh in 2015 (Swedish Energy Agency, 2018a).

Figure 6. Energy used for heating and DHW in SFH and Multi-dwelling buildings in Sweden in 2015 (Adapted from Swedish Energy Agency, 2018a)

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2.2. Swedish residential building stock

The construction of buildings in Sweden has over 100 years of development. The intensive construction of the Swedish building stock has been launched in the major cities of the Stockholm area and in the southern part of Sweden. As a consequence, about 50% of buildings are located in the Stockholm area and 35% in the southern parts, mainly in Gothenburg and Malmö (Wang and Martinac, 2013).

According to the Swedish Energy Agency (2018c), there were 4859252 dwellings on the 31st of December 2017. Among these, 2069353 dwellings (43%) were in one or two-dwelling buildings (SFH), 2462972 dwellings (51%) were in multi-dwelling buildings, 247277 dwellings (5%) were in special housing and 79650 dwellings (2%) were in other buildings (Swedish Energy Agency, 2018c).

SFH are characterized by an average size that is double (122 square meters) of that of multi- dwelling buildings (60 square meters) (Swedish Energy Agency, 2018c).

The modern building construction booming periods have been 1940-1960 and 1965-1975, in which large amounts of residential buildings were designed and constructed (Wang and Martinac, 2013).

Figure 7 shows that nearly 931000 (45%) of SFH were built between 1961 and 1990, whereas with regard to multi-dwelling, most of them (52%) were built between 1951 and 1980 (Swedish Energy Agency, 2018c).

Figure 7. Number of dwellings by type of building and period of construction in Sweden (Adapted from Swedish Energy Agency, 2018c)

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According to the European Commission (2015), 75-90% of the European Union’s building stock standing today will still be in use in 2050, seeing as the construction rate is overall low (BPIE, 2017) with low demolition rates (0.1% per year) and low refurbishment rates (1.2% per year) (European Commission, 2015). Therefore, these numbers might be expected also in Sweden where the residential sector has a construction rate yearly of around 1.3%, with one-two dwelling buildings at a rate of nearly 0.6% (SCB, 2018a and 2018b).

In Sweden, around 480000 SFHs were constructed between 1961 and 1975 during ‘the record years’ (Hall and Vidén, 2005) in order to overcome a substantial demand for new housing (Ekström and Blomsterberg, 2016). To build these many houses in the short span of time, the buildings were constructed in a standardized way, characterized by low levels of thermal insulation, thus representing a great potential to improve energy efficiency and thermal comfort (Ekström and Blomsterberg, 2016).

According to BPIE (2018b), the average energy use of these dwellings is about 40% higher than the corresponding energy used in houses built between 2011 and 2013.

With a renovation cycle of 30-40 years, this building stock is currently facing the urgent need of retrofitting, whose energy efficiency potential represents a large part of the national energy savings potential between now and 2050 (Femenías and Lindén, 2012).

Therefore, the Swedish government has proposed to allocate 1 billion SEK (about €100 million) per year to the renovation of residential buildings in socio-economically challenged areas (BPIE, 2018b). However, in order to receive the support, the energy consumption of the building must be reduced and verified by at least 20% (UNEP, 2017).

2.2.1. The Swedish Million Programme

The first decades of the post-war era have been marked by a large and growing need for new housing all around Europe. In Sweden, the fast urban development, booming economy and the high demands for dwellings led to interminable house waiting lists (Hall and Vidén, 2005).

Because of this housing shortfall, the years between the 1960s and the 1970s were distinguished by large building investments in different areas in Sweden, especially during the period going from 1961 to 1975, which has been called ‘the record years’ and which was characterized by the

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construction of approximately 40000 apartment buildings, about 920000 multi-dwellings and almost 480000 single-family houses (Hall and Vidén, 2005).

One million of these dwellings were built during the “record years” (1965-1974) of the “Million Homes Programme” (Miljonprogrammet), with a distribution of 66% multi-family blocks apartments and 34% single-family houses. The goal of the Miljonprogrammet was to build 100000 houses each year for the following ten years, thus proving to be an outstanding goal to be achieved as the number of Swedish homes in that period was just three million (Hall and Vidén, 2005).

About half of the single-family houses were built in groups following an identical, rational blueprint and both multi-family blocks and single-family ones had pure and simple forms, more often with a traditional pitch for the roof. The majority of the single-family houses (over 70%) have been built detached, while fewer than 30% in a row or chain houses. The living space and the number of rooms had a substantial increase in single-family homes and in 1975 over 50% of the single-family houses under construction had at least five rooms and a kitchen (Hall and Vidén, 2005).

Nowadays, one-third of Sweden’s buildings are houses constructed during the Million Homes Programme (Bergström and Save-Öfverholm, 2011) and especially the dwellings of the ‘record years’ have now reached an age that requires a conspicuous maintenance measure (Hall and Vidén, 2005). In addition, they will reach soon a service life of 50 years, that is the time window commonly used as buildings lifespan in Swedish building stock energy retrofitting studies (Pombo, Rivela and Neila, 2016).

However, unlike other countries that adopted a demolition strategy for housing built between 1945 and 1975, Sweden has chosen to focus on a renovation plan, since demolitions are rare and controversial (Lind, et al., 2016). Many of its renovation and retrofitting projects are likewise employed as prototypes for a worldwide spreading of Swedish knowledge, experience and environmental technology (Bergström and Save-Öfverholm, 2011).

Nevertheless, so far, only around 15% of the ‘record years’ houses have been “modernized”

with new technological installations (Hall and Vidén, 2005).

Therefore, the Millions Homes Program houses and in particular those built during the ‘record years’ should be considered as a priority for energy retrofitting projects in Sweden with the aim to make its cities more sustainable and achieve its climate goals.

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2.3. Retrofitting of existing buildings

Energy saving and intelligent design are currently the common topics in the building sector, but most of the time this is related to new construction processes. Building from the new is easier because if well designed, the building is already set to be eco-friendly and with high energy performance.

On the other hand, the renovation of existing buildings is more complex, as it has to face several constraints to remedy the obsolescence of such buildings, which requires maintenance and redevelopment improvements due to the occurrence of performance decays in order to provide new qualities and performances that were not originally foreseen.

Energy retrofit solutions are placed within this framework, which are configured as a process of adaptation through the application of current technologies, technical elements and innovative systems for the improvement of the current performances of buildings energy efficiency.

Some authors have tried to give a more detailed definition of what retrofitting means and which are its various uses in the built environment.

El-Darwish and Gomaa (2017) provide a more general explanation of the term retrofit, which refers to the addition of new technologies or functionalities to previous systems for several reasons, such as improving the efficiency of the electrical system; strengthen older buildings to make them earthquake resistant; or the improvement of existing buildings with energy efficiency equipment.

On the other hand, Eames et al. (2014) provide a more specific description: “to retrofit literally implies providing something with a component or feature not fitted during manufacture or adding something that it did not have when first constructed”.

Even though the term retrofit has often been used interchangeably with terms such as

‘refurbishment’ and ‘renovation’, they have different specific meanings (Designing Buildings, 2016).

The term ‘retrofit’ is often related to the installation of new building systems, such as heating systems, but it can also refer to the fabric of a building, such as insulation or double glazing (Designing Buildings, 2016).

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On the other hand, while ‘refurbishment’ involves a process of improvement through cleaning, decorating, re-equipment and could include retrofit elements, the term ‘renovation’ entails a process of returning something to a good state of repair (Designing Buildings, 2016).

However, a single project might include elements of retrofitting, refurbishment and renovation (Designing Buildings, 2016).

2.3.1. Need for retrofitting

Although the need for retrofitting and renovation of existing buildings is currently gaining more attention in Europe, there are still rather limited renovation activities in progress in most countries (Jensen, et al., 2013).

Buildings retrofitting need to face various economic barriers and challenges that have prevented investment in improving energy efficiency (Monteiro, et al., 2017).

Financial barriers derive from the high initial costs that are related to building retrofits and lead to long payback periods (Monteiro, et al., 2017). For example, retrofit actions on building envelopes are not always possible or economically viable in existing buildings and particularly in historic buildings where conservation is a priority issue (Aghemo, et al., 2013).

A common challenge is the quantification of non-monetary benefits that can be achieved through the implementation of buildings retrofitting solutions. These can consist of better indoor air quality (IAQ), improved thermal comfort and lower noise levels. The inclusion of these solutions in a building retrofit analysis might help to convince household owners to undertake retrofitting actions (Monteiro, et al., 2017).

2.3.2. Retrofitting cost/benefits and technologies

Retrofitting of existing buildings provides significant opportunities to reduce global energy consumption and GHG emissions. This is considered one of the main approaches to achieving sustainable targets at relatively low costs (Ma, et al., 2012), as the overall benefits of investing in energy efficiency will exceed the initial investment costs (Simson, et al., 2016).

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In order to reduce primary energy consumption in buildings, it is possible to implement various efficiency strategies (Simson, et al., 2016), which may allow an upgrade of the building's energy and environmental performance to a higher standard (Rabani, Madessa, and Nord, 2017).

According to Rabani, Madessa and Nord (2017), there are four main criteria for the assessment of energy efficiency and sustainable performance regarding retrofit strategies: reduction of energy consumption and global GHG emissions, improvement of the IAQ, and upgrading of building functionality and its architectural quality.

An overview of the possible retrofit strategies that can improve the energy and environmental performance of the building can be classified into three main actions (Rabani, Madessa and Nord, 2017):

1) actions concerning the building envelope and design aspects, such as the reduction of air leaks and the improvement of thermal insulation also through the use of better doors and windows;

2) actions for building systems and equipment, such as the installation of high-efficiency HVAC systems, the implementation of renewable energy and the improvement of electric lighting equipment;

3) actions regarding building services and management tools, such as the use of sensors and control of buildings during operation.

However, retrofitting is a challenging task that requires a holistic and integrated approach (Shaikh, et al., 2017). Each strategy has an influence both on the performance of the building, but it has also a wider effect on the social, economic and environmental aspects and thus the building must be analyzed as a whole (Simson, et al., 2016).

Whilst building retrofitting offers great opportunities for improving energy efficiency, decreasing maintenance costs and providing better thermal comfort (Ma, et. al., 2012), the expected cost of a specific retrofit action (Rabani, Madessa, and Nord, 2017) and its perceived long payback periods (Ma, et. al., 2012), represent the key to its effective value. For instance, retrofitting of building services requires less cost investment while providing more environmental benefits than retrofit actions using renewable energy technologies (Rabani, Madessa, and Nord, 2017).

Therefore, building retrofitting optimization consists in determining and developing the most cost-effective retrofit technologies to achieve improved energy performance while maintaining

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adequate service levels and appropriate indoor thermal comfort, under a certain set of operational constraints (Ma, et. Al., 2012).

Nowadays, there are several building retroﬁt technologies already available in the market. Ma, et. al., (2012) have classified the main possible retroﬁt technology types that can be used in building applications into three groups: supply-side management, demand-side management, and human factors which represent a change of energy consumption patterns.

The retrofit technologies for supply-side management include mainly the use of renewable energy, such as solar hot water, solar photovoltaic (PV), wind energy, geothermal energy (Ma, et. al., 2012).

Retrofit technologies for demand-side management include strategies to reduce the demand for heating and cooling of buildings and the use of energy-efficient equipment and technologies (Ma, et. al., 2012).

There is a multitude of KPIs used in building retrofit assessment (Simson, et al., 2016) and determining the optimal retrofit strategy is a complex procedure that must be critically evaluated and supported by specific analysis (Rabani, Madessa and North, 2017), with the aim to find the most suitable and least invasive technology.

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2.4. ICT as the key player

2.4.1. ICT energy savings potential

The growing use of information and communications technology (ICT) has become part of all aspects of modern life, influencing the way people live and work (IEA, 2017a).

ICTs have steadily increased productivity and supported economic growth in both developed and developing countries, providing innovative products and services that are now an integral part of everyday life (GeSI, 2008).

Rapid advances in data collection and connectivity are fostering digitalization across the economy and the energy sector is no exception (IEA, 2017a).

Information and communication technologies have been identified to play a key role to combat climate change and increase the energy efficiency of the European Union (EU), and their potential for reducing energy consumption will provide an important contribution in all sectors of the European economy, such as smart grids, smart buildings, smart lighting, and smart manufacturing (Ye et al., 2008).

For example, smart grids can help to support the integration of renewable energy sources into electricity markets, while allowing better load management. Advanced energy controls are leading to more energy-efficient houses, commercial buildings and industrial plants (IEA, 2017a).

ICTs can enable improvements in the energy efficiency of the major energy-using sectors by, first reducing the amount of energy needed to provide a given service and, later, by directly monitoring and managing its energy consumption. Recent studies show that this energy potential can be used to reduce the buildings energy consumption in the EU by up to 17% and to reduce carbon emissions in transport logistics by up to 27% (Commission of the European Communities, 2009). Moreover, improvements to existing building automation systems can save a significant amount of energy and reduce CO2 emissions by only requiring small investments with short payback periods (Siemens, 2015).

Thence, it is evident how the digital world and the global energy system will increasingly converge, boosting opportunities for the energy sector in achieving the objectives of energy security, access to energy, economic growth and environmental sustainability (IEA, 2017a).

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A report (SMART 2020) made by GeSI (2008) has calculated direct emissions coming from ICT products and services as well as it has analyzed which other sectors could have significant CO₂ emissions reductions thanks to ICTs, quantifying also them in terms of cost savings.

Its following report (#SMARTer2030) highlighted how ICTs can achieve a 20% reduction in global CO2 emissions by 2030, which is almost ten times higher than the ICTs emissions footprint (1.97%) and could generate over $11 trillion economic benefits per year by 2030, linking 2.5 billion extra people to the "knowledge economy", providing 1.6 billion more people to health care access and 0.5 billion extra people accessing E-Learning tools (GeSI, 2015).

The report #SMARTer2030 (GeSI, 2015) analyzed how ICT-enabled solutions can potentially reduce annual emissions in five different sectors by 12.1 GtCO2e globally within 2030 (Figure 8), representing a reduction potential of 50% higher than that calculated in the previous report (7.8 GtCO2e).

Figure 8. Environment - CO2e abatement potential by sector within 2030 (Adapted from GeSI, 2015).

Among all the five sectors, the two most important to mention regarding energy savings potential are energy and buildings.

In the energy sector, ICTs can allow the integration of renewables onto the so-called Smart Grids, which, together with advanced energy management systems (EMS), can reduce 1.8Gt of CO_2e and generate $0.8 trillion in new revenue opportunities (GeSI, 2015).

Furthermore, ICTs can reduce 2.0Gt CO_2e in the building sector by providing tenants with the required systems needed for renewable energy generation. In addition, ICTs will allow increased thermal comfort and reduced energy consumption from lighting, heating and ventilation systems, while BMS (building management systems) will assure that these systems are used

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efficiently, decreasing energy costs by $0.4 trillion and creating $0.4 trillion of revenue opportunities (GeSI, 2015).

Although there are other methods to improve buildings energy efficiencies, such as renovation/refurbishment or use of high-efficiency appliances, it is believed that ICT systems will have a significant potential to reduce and optimize buildings energy consumption (Morán et al., 2016) through the employment of BMS, smart meters, lighting control systems and intelligent sensors (Ye et al., 2008) which allow decreasing energy peaks and shut down equipment when not used or required (Morán et al., 2016).

As shown in Figure 9, the analysis (#SMARTer2030) found that ICTs will have the greatest impact through Smart Manufacturing, Smart Agriculture, Smart Buildings and Smart Energy technologies (GeSI, 2015).

Figure 9. Environment - CO_2e abatement potential by use case within 2030 (Adapted from GeSI, 2015).

Therefore, this report highlights once more how the new impulse of reducing CO₂ emissions and improving energy efficiency in the building sector can be triggered by information and communication technology, which in turn, through data analysis, advanced controls and artificial intelligence, can bring the concept of smart building closer to reality (Molinari and Kordas, 2017).

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Today, most of the buildings are passive energy consumers and cannot communicate with the outside world. Furthermore, the percentage of CO2 emissions coming from buildings is increasing compared to the total city emissions (Morvaj, Lugaric and Krajcar, 2011).

Therefore, in line with the objectives of the energy-saving policy, current buildings need to be upgraded to the so-called smart buildings which can communicate with their surroundings, and occupants can monitor their energy consumption in real time, becoming active members of the energy system (Morvaj, Lugaric and Krajcar, 2011).

Smart buildings can be depicted as a joining link between architecture, urban planning, and ICTs (GeSI, 2015). They are characterized by a set of technologies used to make the design, construction and operation of existing and new buildings more efficient (GeSI, 2008).

The main smart buildings technologies are sensors, control systems, smart meters for integration into smart grids (GeSI, 2015), building management systems (BMS) that run heating and cooling systems based on occupant needs or software that turns off all appliances after everyone leaves home (GeSI, 2008).

For example, data collected through smart meters and other smart home solutions can be remotely communicated to users via their smart devices, allowing them to monitor their energy consumption such as lighting or heating. These solutions can be applied to large commercial complexes but also to smaller buildings, helping to promote the more efficient use of energy (GeSI, 2015).

However, the term smart building is often interchangeable with a smart home, hence a clarification of the two terms is necessary.

‘Smart homes’ and ‘smart buildings’ share some common functional and technical points, but they have quite different purposes. Güemes (2011) explained their difference through an analogy between cars and trucks: “Both are vehicles and share some basic technological guidelines, but with different implementations in their final forms in order to provide the required capabilities for each”.

Smart homes, also known as automated homes or domotics (Ricquebourg et al., 2006), have been defined as home environments that have environmental intelligence and automatic control, enabling them to respond to the residents behaviour and providing features that go beyond the

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capabilities of current buildings, such as increased security, e-health, improved comfort and IAQ as well as efficient use of energy (Molinari and Kordas, 2017).

Originally, smart home technology was used to just control environmental systems such as lighting and heating, but the latest development of intelligent technology allowed almost all the electrical components inside the house to be included in the system (Ricquebourg et al., 2006).

Therefore, the main difference between smart homes and smart buildings is about their purpose:

while smart homes are more geared towards comfort and well-being, smart buildings are mainly focused on efficiency, both in terms of resource use and economic costs (Güemes, 2011).

Because of the benefits they can bring to the whole economy, smart buildings are expected to play a significant role as units in the future smart cities and thence have been the subject of great attention in literature in the last years (Molinari and Kordas, 2017).

The IEA analysis regarding the role of digitalisation in buildings shows that smart controls and connected devices could save 230 EJ up to 2040, reducing the energy consumption of buildings by up to 10% globally while providing better thermal comfort (UNEP, 2017). Smart buildings would also contribute to reducing the global emissions of the energy sector, providing flexibility through storage, demand response and better management of energy supply and demand across the grid (UNEP, 2017).

Smart building energy management can ensure that energy is consumed when and where it is needed, taking into account user preferences, while real-time data collected through controls and sensors can help governments, businesses, and utilities to forecast and monitor the performance of the building in real time (UNEP, 2017), thus allowing the development of a new Smart Energy Network.

2.4.3. ICT enabling Smart Energy Network

In the 1950s, around 30% of the world's population lived in cities, while in 2010 the percentage rose to 50% and is expected to be 70% by 2050. Thence, cities are becoming centres of economic, political and technological power (Morvaj, Lugaric and Krajcar, 2011).

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In order to reduce emissions and increase energy, economy and information efficiency, cities need to undergo a change in their organization, while keeping secure and continuous access to critical infrastructures (Morvaj, Lugaric and Krajcar, 2011).

Morvaj, Lugaric and Krajcar (2011) defined a smart city as a city that increases its performance in meeting all its citizen's needs, and this description is aligned with the definitions in the literature, where a smart city is a city that combines ICT with its infrastructure systems.

Among all infrastructure systems, electric power systems play the role of a critical infrastructure. Renewable energy sources have become accessible to an increasing number of people, so it is becoming a real possibility to create a cluster of distributed generation facilities that will allow the continuous power supply to the city (Morvaj, Lugaric, and Krajcar, 2011).

However, this would require an intelligent and advanced control architecture, which would enable the integration of smart buildings into the smart grid (Warmer et al., 2009).

A smart grid is a concept that combines ICT and electrical power grids and its main feature is to establish a two-way communication in all nodes of the grid as well as to control and optimize the renewable energy sources present in the network, enabling the instantaneous balance of supply and demand at the level of buildings and even appliances (Morvaj, Lugaric, and Krajcar, 2011).

In addition, smart grids will allow buildings to change their traditional role from mere energy consumers to producers (Güemes, 2011). In fact, nowadays buildings are the main consumers of energy but they have also the potential to become one of the main producers of renewable energy (Wurtz and Delinchant, 2017), as well as service providers for utilities and system operators, providing a significant source of flexibility (Warmer et al., 2009).

Buildings associated with the smart grid can thus constitute a fundamental pillar of the scenario for the energy transition through their updating in the so-called smart buildings (Wurtz and Delinchant, 2017).

Smart buildings, indeed, can be seen as the adaptation of the smart grid concept to the level of the building's micro-grid (Wurtz and Delinchant, 2017), whose effective integration into the network still requires appropriate levels of digital technology and interoperability (Kolokotsa, 2016).

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The idea is to propose an energy micro-grid, which connects a cluster of distributed generation, multi-storage systems, electric vehicles, multi-loads, all entirely orchestrated by information and communications technology (Wurtz and Delinchant, 2017).

Therefore, ICT will play a key role in the development of the smart buildings which can be aggregated in neighbourhoods, districts, cities, and countries (Rawte, 2017) in order to generate and share local energy production as well as consumption capacity and thus create a global smart energy network that is sustainable, reliable and secure (GeSI, 2015).

2.4.4. ICT infrastructure

ICTs can enable smart buildings to communicate with internal devices and equipment as well as with its surrounding environment, such as with other buildings, thus creating active microgrids or virtual power plants (Morvaj, Lugaric, and Krajcar, 2011).

The ICT infrastructure design (Figure 10) can be developed through the integration of three main elements (Morán et al., 2016):

- Monitoring devices (sensors and actuators), that depend on the building systems and the parameters to be measured. Sensors have the function of monitoring and sending messages in case of changes, while actuators have the task of carrying out a physical action sent and supervised by the controller;

- Communication infrastructure, which has the task of transmitting the measurements from the monitoring devices to the control centre and the orders from the control centre to the actuators.

This infrastructure consists of a network which allows the communication between units as well as controllers that represent the brains of the system, acquiring data from the sensors and decide how the system will respond through programmed rules set by the user;

- BMS, which is the software that collects the measurements in the field and displays them to users via screens which in turn allow the communication and interaction between users and the system.

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Figure 10. ICT infrastructure (Adapted from Morán et al., 2016).

Monitoring devices (sensors and actuators)

ICT technologies can provide an ideal solution for monitoring numerous physical parameters and energy consumption. Based on these parameters, the sensors can be divided into two main categories (Morán et al., 2016):

- Sensor for monitoring physical parameters: air temperature, humidity, lighting, room occupancy, CO₂ concentration, etc.

- Sensor for monitoring consumption: gas, electricity, water, etc.

The role of sensors within an energy management system (EMS) is to provide information through environmental monitoring of the zone and thus enable corrective actions to be taken on the control of equipments, for example by adjusting the heating system according to a thermostat or turning off the lights when there is no occupancy (Domingues et al., and Morán et al., 2016).

Communication infrastructure

Communication between sensors, actuators and BMS is of particular importance to guarantee the correct control and management of the building.

Thanks to the communication technologies, sensors make the energy context visible, so the BMS can monitor and optimize the operation, allowing the appliances to consume less energy autonomously and provide feedback on their energy consumption in real time (Morán et al., 2016).

Smart Buildings: ICT as a driving energy-efficient solution for retrofitting of existing buildings

Smart Buildings: ICT as a driving energy-efficient solution for

retrofitting of existing buildings

GIUSEPPE SGRÒ

Smart Buildings: ICT as a driving energy-efficient solution for retrofitting of existing buildings

Giuseppe Sgrò

Abstract

Sammanfattning

Acknowledgements

Table of Contents

List of Figures

List of Tables

1. Introduction

2. Background