Application of Smart Readiness Indicator for Mediterranean buildings in retrofitting actions

Abstract Recent years have seen an increasing need to invest in smart, energy-efficient technologies in buildings to improve health and convenience for occupants and to reduce energy consumption and carbon emission impacts. Digitalization and developments in the information and communication technology sector play a critical role in improving the efficiency of the European energy market and remaining in the current progress of sustainable and renewable energy systems. Therefore, the European Union Member States are required to establish an optional common scheme for defining and calculating a descriptor, called a smart readiness indicator to assess the capabilities of buildings to adapt their operation to the needs of the occupants and the electricity grid and to achieve more efficient operation. This indicator is calculated using a methodology proposed and developed by the European Commission Directorate-General for Energy which depends to a great extent on various factors such as building type and climate conditions. The effectiveness of these parameters on the Smart Readiness Indicator is reflected by the weighting coefficients which need to be initially defined by the legislator. Therefore, the main step to assess the viability of this methodology, is to test it in different situations, i.e., various building types, climate conditions, etc. To this end, the proposed methodology is applied in two service buildings with different levels of energy and indoor environment quality performance located in an area with a Mediterranean climate. The possible effects of smart services and retrofit actions on indoor environment quality and energy performance in the buildings were assessed through energy simulation for two separate rooms in the buildings, a monitoring campaign and a survey to assess the occupants’ subjective opinion about the indoor environmental quality using the questionnaire proposed by the Centre for the Built Environment of the University of California. The results imply that, although the proposed methodology was able to recognise the overall characteristics of the sample buildings, some amendments are still required to capture the specific features of non-residential Mediterranean climate buildings. More specifically, the defined weighting factors fail to reflect the actual energy performance of the service buildings and need to be revised. Moreover, the current retrofitting actions which were implemented to improve energy efficiency and thermal comfort in the building were not as effective as expected in enhancing the SRI value.


LIST OF TABLES
.12. Example of spreadsheet provided by [24] with functionality levels and impact scores for a specific service ..  feasible. According to [1], a "building automation and control system" is defined as "a system comprising all products, software and engineering services that can support energy efficient, economical and safe operation of technical building systems through automatic controls and by facilitating the manual management of those technical building systems". In another words, automation and control systems are sets of tools and software which can contribute to more monotonous and economic actions for energy performance and security improvements. A constantly monitored system is able to record and analysis the information to energy consumption improvement, diagnosis and alert of system failures and connect building technical systems to other services in the building. However, there is not sufficient detailed definition of control and automation systems of buildings provided by EPBD.
As it was mentioned before, Member States should define the guidelines in the Directive based on their specific needs and conditions (geographically, financially…) and accordingly, implement necessary strategies in the buildings. For this aim, based on the Directive recommendations, Member States should be prepared technically and theoretically regarding construction and energy and utilize three useful tools including trigger points, One-Stop-Shop (OSS) and the building renovation passport to perform in a more efficient way [2]. Trigger points are certain periods in the building's life when the most efficient decisions and appropriate intervention can be made to improve the energy performance of the building. In addition, the One-Stop-Shops for energy renovations of buildings are "transparent and accessible advisory tools from the client perspective and new, innovative business models from the supplier perspective" [3] which is supported also by the "Smart financing for smart buildings" initiative. In order to develop working models and frameworks in which climate mitigation and energy performance of buildings will effectively improve, the European Commission, Joint Research Center (JRC) has effectively involved. The third tool introduced by the Directive is the building renovation passport which is a document (in electronic or paper format) which is a step-by-step road map for a long-term (up to 15-20 years) deep renovation for a specific building [1].
The area of concentration of this Master's thesis is to analyze the smart readiness indicator (SRI) defined by the "new" EPBD directive and assess the proposed calculation methodology by applying it in the building in the Mediterranean climate region and evaluate the effectiveness of possible retrofit actions on SRI, the energy performance of the building and indoor environment quality (IEQ).

Problem statement
As it was mentioned in the previous section, SRI was introduced by the latest published EPBD directive and it is in the beginning point of its way. Therefore, the methodology of SRI calculation needs to be comprehensively studied, evaluated and examined from different aspects and in various conditions. The lack of researches in this field could hinder the effective implementations and prevent the building owners, occupants and stakeholders to take full advantage of this scheme. This study was carried out to contribute to fill this research gap thorough assessment of the proposed methodology for a specific building in a particular climate condition and investigate the relation of this indicator with building retrofitting.
The area of concentration of this work is the analyzing and implementation of the proposed SRI calculation methodology in two service buildings in the Mediterranean climate in Portugal. One of these buildings has been constructed in 2008 and no energy certification study has been conducted for this building so far. But the building envelope and technical systems in the building have already passed the national regulations. The other one has been constructed in 2015 beside the first building (partially integrated from inside) with the higher energy performance and energy class C. The objective of this work is to analyze the SRI calculation methodology in the Mediterranean climate and to investigate the effect of building renovation on SRI as well as energy-saving and IEQ It is achievable by comparing SRI before and after implementing the possible retrofitting actions. More specific goals of the research were included in the following research questions: · Which factors are effective on SRI assessment for a building?
· Is there any relation between building retrofitting and SRI improvements?
· Does the higher SRI actually guarantee better energy performance in the building?
· Does the higher SRI really guarantee better IEQ?
· In which ways the SRI in a building can be improved?

Methodology
The methodology applied in this study is mainly based on the methodology introduced by European Commission Directorate-General (DG) Energy which is a checklist approach filled through site visiting and a sort of calculations based on the data provided in the spreadsheets. This methodology will be explained in chapter 3. Then, two case study buildings were selected and analyzed through an on-site investigation. In order to evaluate the indoor environment quality for the buildings with different SRI and technical building services, a sort of measurements was carried out for two separate rooms in two case buildings. Moreover, two sets of surveys were performed to assist SRI assessment and to evaluate occupants' overall satisfaction of indoor environment quality in the case study buildings. In addition, to analysis the buildings' energy performance under the influence of smartness and energy-efficient actions, the building simulation was carried out using DesignBuilder Software for two separate rooms.

Thesis structure
This thesis consists of five chapters (besides the introduction and conclusion chapters

LITERATURE REVIEW
In this chapter, the recent researches in the field of smart building definitions, SRI methodology assessment and building retrofitting strategies in the Mediterranean climate are presented.

State-of-the-art on smart buildings
It is evident in the recent studies that the building stock in Europe is just at the beginning point of its smart-ready way [4]. Although there has been a viable concern in different studies to discuss smart buildings, the definition of smart building often varies between the publications. Nevertheless, the most imperative step to developing relevant technologies and systems related to smart-ready buildings is to have a united interpretation of smart buildings as a reference. According to [5], a smart building is defined as a building in which advanced building technology systems are integrated for the efficient performance of the buildings in terms of energy efficiency, occupational health and comfort, security, sustainability, and building marketing. Similarly, Wang et al [6] described the smart building as a building that provides an optimal comfort level and energy consumption as well as sustainability issues by employing intelligent technology and renewable energy resources.
In addition, several other studies agree that one of the most indispensable aspects of smart buildings is system synthesis which improves the building functionality and performance.
Kiliccote et al [7] described a smart building is a building in which the self-aware, gridaware end-use systems are combined and are in a monotonous interaction with occupants needs and environmental conditions. Likewise, Buckman et al [8] defined smart buildings as buildings that adaptively integrate entire building systems including smart system, operation, control, material, and construction to improve building performance. In a distinctive prospect, the smart building defined as a building which is integrated into smart grids. As it was described in [9], a building which is integrated to a smart city system with active modules in thermal and electric energy systems and involves actively in energy generation, load shifts and energy-storing can be considered as a smart building. The Buildings Performance Institute Europe (BPIE) defines a smart building as a dynamic micro energy-hub which with energy generation, control, store, demand response and interconnection with electric vehicles improve the flexibility of the energy systems while provides a healthy and comfortable living and working environment for the occupants [10]. A smart building was also defined as a part of a smart environment that provides more efficient living and working environments for occupants [11]. Moreover, according to the Continental Automated Building Association (CABA) a smart building has the ability to behave in relation to the effects of parameters around it [12].
As it was mentioned before, regarding the smart readiness indicator there has been a few studies carried out so far. In one of this work conducted by Janhunen et al [13], the applicability of the SRI to cold climate countries in Northern Europe was explored. Since most of the buildings in Northern European countries enjoy advanced information and communication technologies with high energy consumption profiles, they were an exceptional test environment for the indicator. The findings implied that this indicator was not able to recognize the specific features of cold climate buildings, specifically those using advanced district heating systems. This research also suggests that the applicability of SRI as a fair rating system across the EU member states is uncertain because of the subjective nature of the proposed methodology for SRI relevant building services selection. In the other study, the smart-readiness metrics were used to determine the smart-readiness level of the current typical Dutch residential building in [14]. The regular Dutch terraced house is the most common type residential building in the Netherlands, so the smart-readiness assessment in the study was focused on typical Dutch terraced house and its design variations that currently available or could be developed in the future. Based on the modeling and simulation results of the tested case studies, the typical Dutch terraced house had significant untapped potential that can be optimized to adjust the current building to be ready in the smart building transformation. It was also shown that the indicators depend on the occupant behavior which could cause the same building to have different smart-readiness levels according to the occupancy pattern.

State-of-the-art of building strategies in Mediterranean climate
During the last decade, many countries have put significant effort toward energy efficiency improvement in existing buildings. Building retrofitting offers many challenges and opportunities which can vary depending on different circumstances such as climate conditions, building type and economic situation besides many uncertainties such as climate change, energy policy change and human behavior change. All of these factors could be highly effective during building retrofitting technology selection. There have been many studies conducted in this field that examined the building retrofitting in various perspectives.
However, the area of concentration in this section is on review the studies have been done regarding the challenges and opportunities of building retrofitting in the Mediterranean climate.
Some studies analyzed different building envelope performance in the Mediterranean region and found that energy demand can be reduced by using proper windows, shading devices and building envelope materials [15][16][17][18]. Using passive strategies has been also one of the main areas of interests for the researches in this field. A study on passive cooling techniques was carried out by Imessad et al [19] to evaluate the impact of thermal mass and eaves and night ventilation on energy demand. They showed that cooling energy demand is more affected by thermal transmittance values than by the envelope thermal mass and recommended the optimum overhang length for south-facing windows.
Also, it was suggested that the combination of both natural ventilation and horizontal shading devices improves thermal comfort for occupants and significantly reduces cooling energy demand. Accordingly, Gil-Baez et al [20] studied on the effects of passive refurbishment solutions to improve the envelope of school buildings (insulation, shading and glazing) in a building in the Mediterranean climate. The results showed that energy demands reductions are relatively lower compared with those reported in equivalent schools in other climates.
Climate change as one of the main potential challenges of building retrofitting in the Mediterranean region has been studied in [21][22][23]. It was shown that the demand for cooling and the risk of overheating increase considerably in all the prediction scenarios for climate patterns in the future. While in some studies it was suggested that increased thermal insulation and reductions in infiltration will have a greater effect on global energy demand, in some researches it was proven that the facade improvement is not an effective measure in the Mediterranean climate, and the use of adaptive setpoint temperatures is the most efficient measure.

Conclusion
To sum up, according to several pieces of research have been conducted to define the smart building, it can be said that the main objectives of smart buildings are to optimize the energy consumption and thermal comfort based on different factors such as occupants' behavior and climate using smart technologies integrated with renewable energy sources.
However, the indicator which assesses the level of smartness of buildings has been recently introduced with the lack of sufficient and reliable scientific researches. In addition, in order to develop the study for the retrofitted buildings in the Mediterranean region, it seems necessary to identify the main character and effective retrofit actions of the buildings in this region. Based on the several studies, because of the long summers and the intense need for cooling, considering passive measures in retrofit buildings in the Mediterranean climate is the main area of interest of many works in this field.

Introduction
In the coming years, the world needs to consider digitalization integration into the energy sector more than ever. This would be a key effort in improving efficiency and protecting the environment. Therefore, it was introduced by EPBD as an indispensable support for the European energy market to remain competitive, affordable, and secure in the decentralized and decarbonized network [1]. In addition, investments in the information and communication technology (ICT) integration into the construction sector should be accelerated across Europe to lead the future sustainable and renewable energy systems.
Besides, EPBD emphasis of the using ICT in the building sector as one of the main requirements for EU's 2020 target for nearly zero-energy buildings (nZEB), the 2030 longterm energy efficiency and renewable energy targets and the 2050 carbon economy goal [1].
For this aim, an indicator is needed to evaluate the level of readiness of the building services to record and transfer data and interact with occupants and network, or in other words, the level of smartness of building services. Smart readiness indicator (SRI) was defined as a cost-effective measure to help reducing energy consumption and carbon impacts, integration to renewable energy sources (RESs) while providing a healthy and comfortable living condition. Technical studies have been conducted by VITO 1 team under the authority of the European Commission (DG Energy) with the purpose to develop a calculation methodology and potential characteristics of this indicator. The first technical study was published in August 2018 aiming at analyzing the possible scope and characterizing of SRI [24]. The second technical study was conducted in December 2018 with the aim of further investigation on the methodology and features of SRI [25]. Meanwhile, this research has been developing and so far, three interim reports have been launched to present the latest developments and methodological progress. This chapter aims to introduce and analyze the methodology and definitions provided by these references.

SRI definition
The new provision of the amended EPBD requires the establishment of an optional European Smart Readiness Indicator (SRI) scheme as a common language to evaluate the capability of buildings to use ICT and electrical systems. This indicator is a tool to facilitate expected smart building objectives achievements regarding energy production, storage and fault diagnosis improvements as well as healthier, more comfortable and convenient life for occupants. Figure 3.1 shows the expected advantages according to smart readiness indicator catalogue provided by DG Energy [25].  [25] According to revised EPBD, SRI is "an assessment of the capabilities of the building or building unit to adapt its operation to the needs of the occupants and the grid and to improve its energy efficiency and overall performance" [1]. This indicator should be a cost-effective measure which support technology innovation in the building sector and raise awareness from ICT and smart technologies.

Methodological framework
The SRI framework is based on first and second technical catalogue provided by European Commission DG Energy [24,25] which should be in an efficient and costeffective approach, reflect the features and potential of innovative technologies, able to maintain energy performance and operation of the building and complement policy and market initiative such as Energy Performance Certificate (EPC), Eco-design and energy labelling and Building Renovation Passport (BRP). This framework follows a methodological approach in 5 principal tasks including:   the main tasks of SRI methodological framework [25] As it is depicted in Figure 3.4, the methodology of SRI assessment and implementation can be categorized into three different methods based on stockholders' feedback [26] which are described as follows: Checklist approach with limited, simplified services list Checklist approach, covering catalogue of smart services  Three potential assessment method [26] Method A: It is a simplified method with the aim of quick TBS assessment with identifying the main services and then to assess the key functionalities in detail. It was also proposed that the functionality levels of products are provided by manufacturers to make the self-assessment more straightforward [26]. However, it seems that this method cannot be applied properly, especially for the buildings with innovated and complex systems, so the functionality level is assigned for a group of systems, not a particular system individually.
Also, self-assessment opens the possibility of manipulation or wrong evaluation so the results cannot be trustworthy.

Method B:
This is a detailed assessment that can be applied for all types of buildings and can be implemented for both new constructions and existing or retrofitting In-use small building performance buildings. The evaluation process will be a complex task in this method and needs to be performed by a professional third-party assessor. This method is the area of concentration in this work which is described later in this chapter.
Method C: This is a long-term assessment of the functionality level of smart services in the building to evaluate their effectiveness on energy saving, flexibility, comfort improvements, etc. and to distinguish how much these improvements are because of smart controls or other factors such as using retrofit actions and amendments in occupants' behavior.
The methodology introduced in the first technical report contain 112 services (99 services when the "various" domain is excluded) and divides the smart ready services into 10 distinct domains including heating, domestic hot water, cooling, controlled ventilation, lighting, dynamic building envelope, on-site renewable energy generation, demand-side management, electric vehicle charging, monitoring and control. However, during the ongoing study that have been conducted by DG Energy, there have been some changes in the domains and their subset smart services. These domains are described as follows: Heating: This domain covers all the smart services contribute to improving the performance of the heating systems in the building by optimizing the generation, distribution, storage and end-use consumption. These services introduced in the catalogue are based on the technical standard EN 15232 [28] with some amendments and are mainly related to the automation of the control of technical building systems for heating the indoor environment. The list of smart ready services in the heating domain is presented in Error! Reference source not found..

Heat control -demand side
Control of distribution fluid temperature (supply or return air flow or water flow) -Similar function can be applied to the control of direct electric heating networks -

Heat control -demand side
Intermittent control of emission and/or distribution -One controller can control different rooms/zones having same occupancy patterns Heat control -demand side Thermal Energy Storage (TES) for building heating (excluding TABS)

Heat control -demand side
Building preheating control

Control heat production facilities
Heat generator control (for combustion and district heating) -

Control heat production facilities
Heat generator control (for heat pumps) -

Control heat production facilities
Sequencing of different heat generators -

Control heat production facilities
Heat system control according to external signal (e.g. electricity tariff, gas pricing, load shedding signal etc.)

Control heat production facilities
Control of on-site waste heat recovery fed into the heating system (e.g. excess heat from data centers) Information to occupants and facility managers Report information regarding HEATING system performance -

Flexibility and grid interaction
Flexibility and grid interaction Domestic hot water: This is a domain which deals with the smarter control of hot water generation, storage and distributing hot water for the building by independent hot water systems. This domain is of the more importance for the residential buildings and similar to heating domain the technical standard of EN 15232 has been used for the smart services' definition. The list of smart ready services in the domestic hot water domain is presented in Table Error! Reference source not found.. has been used as the main source in defining these services. The list of smart ready services in the cooling domain is presented in Table 3.3.

Cooling controldemand side
Control of distribution network chilled water temperature (supply or return) -

Cooling controldemand side
Interlock between heating and cooling control of emission and/or distribution -

Control cooling production facilities
Generator control for cooling -

Control cooling production facilities
Sequencing of different cooling generators -

Information to occupants and facility managers
Report information regarding cooling system performance -

Flexibility and grid interaction Flexibility and grid interaction
Controlled Ventilation: This domain deals with the smart services that control the airflow and temperature of the indoor environment. This domain not only effective in energy consumption but also has a significant value in the indoor air quality and the health of the occupants. Similarly, technical standard EN 15232 has been used as the main source in defining these services. The list of smart ready services in the controlled ventilation domain is presented in Table 3.4. Air temperature control Heat recovery control: prevention of overheating -

Air temperature control
Supply air temperature control -

Free cooling
Free cooling with mechanical ventilation system -

MV system operation
Heat recovery control: icing protection

MV system operation
Humidity control  Table 3.5.

Windows control
Window solar shading control -

Window control
Window open/closed control, combined with HVAC system -

Window control
Changing window spectral properties

Feedback -Reporting information
Reporting information regarding performance of dynamic building envelope systems On-site energy generation: This domain includes services that using for monitoring, forecasting and optimizing the operation of local power generation and the storage or delivery of energy to the connected grid. The services have been defined based on the IEC Smart Grid Standardization Roadmap [29], however, they have been aggregated by the DG energy team to cover more practical perspectives. Some of the features in the standard have been defined for the services in the 'demand-side management' domain of SRI in the previous version of the study. The list of smart ready services in the energy generation domain is presented in Table 3.7.

DER -Generation Control
Amount of on-site renewable energy generation Feedback -Reporting information Reporting information regarding energy generation -

DER -Storage
Storage of locally generated energy -

DER-Optimization
Optimizing self-consumption of locally generated energy -

DER -Generation Control
CHP control -

DSM-Storage
Support of (micro)grid operation modes

Feedback -Reporting information
Reporting information regarding local electricity generation  Table 3.8. This domain has been removed in the new technical study.

DSM-Storage
Services for integration of renewables into the building energy portfolio

DSM-Storage
Services for integrating battery storage systems into energy portfolio

DSM-Storage
Integration of smart appliances

DSM-Grid
Power flows measurement and communications

DSM -Local Systems
Energy delivery KPI tracking and calculation

DSM-Grid
Fault location and detection

DSM-Grid
Fault prevention and risk assessment

DSM -Local Systems
Neighborhood energy efficiency calculation

DSM-Grid
Demand prediction

DSM-Grid
Information exchange on renewables generation prediction

DSM-Storage
Heat management for a multi-tenant house by aggregator

DSM -Local Systems
Flexible start and switch off of home appliances  Charging whenever needed at the charging pole of the building ("dumb charging service")

EV Charging -Market
Charging with local, building system-based control (price signalbased charging)

EV Charging -Market
Charging with aggregated control (EV responsible party as VPP balancing responsible party)

EV Charging -Market
Charging with aggregated control (EV responsible party under a balance responsible party) EV Charging -non-

Grid sensors
Grid connected heating for EV in winter time

EV Charging -Grid
Providing system services to DSO operations

Service group Smart ready service Status in the new version EV Charging -non-Grid sensors
Charging for optimization of the EV battery life-cycle

EV Charging -Grid
Charging at a commercial building site -roaming

EV Charging -Market
Charging based on DSO price tags -" local wind storage"

EV Charging -Market and Occupant
Providing the state-of-charge to home display  Table 3.10.

Lifts and elevators
Lift and elevator control and dispatching

Lifts and elevators
Lift and elevator monitoring and maintenance

Lifts and elevators
Lift and elevator energy recovery Regarding the changes in the third interim report of the second technical study, first, the domain "on-site renewable energy generation" became "electricity" because of the following reasons: First, the term "renewable energy generation" can cover centralized energy generation or renewable thermal energy in heating systems, so it cannot be considered technology-neutral as it requires to be according to the smart ready system definition. Second, it was suggested that many renewable energy sources such as solar and wind energy cannot be considered as "smart" according to SRI definition because of the lack of energy-efficient control and direct response to occupants and grids. Also, the term "generation" cannot reflect the services relating to energy storage as well. Moreover, the term "electricity" is more relevant because some services concerning renewable energy generation such as thermal solar panel are already in the heating domain. Finally, some smart services regarding electricity consumption are not already comprised in any domains.
Second, the domain "demand-side management" has been removed in the second technical report because it was suggested that most of the services introduced in this domain are strongly linked to a certain technical building service which can be directly linked to other domains such as heating, cooling or domestic hot water, and remaining services can be categorized in the "monitoring and control" domain. These changes are seen in Figure   3.5.  [26] In the catalogue, the overall number of 52 smart ready services have been defined and each service can be evaluated based on a specific functionality level ranging from 0 which indicated a non-smart service and maximum of 4 (varies for different services) which refers to maximum smartness of that service. The evaluation of the smart ready services is based on their impact on the occupants, building and the grid which can be assessed according to eight distinct criteria defined in the catalogue including energy savings on-site, flexibility for the grid and storage, self-generation, comfort, convenience, well-being and health, maintenance and fault prediction, and information available to occupants which are described as follow: Energy saving on site: This criterion demonstrates the impacts of services on energy saving in the building. This impacts not only refers to the direct effects of building services on energy saving, but also covers the contributions from all control systems on reducing the energy needs and finally saving energy.
Flexibility for grid and storage: This criterion represents the impacts of services on the energy flexibility potential of the building.

Self-generation:
Refers to the impacts of services on local renewable energy generation and distribution capabilities and the management quality of consumption and storage of the on-site generated energy regarding pick hours, loads, climate, etc. This criterion has been omitted in the new report.
Comfort: Refers to the capabilities of services to provide environment comfort for occupants including thermal comfort, acoustic comfort and visual comfort.
Convenience: Refers to the impacts of services on reducing the occupants' manual control of the technical building system and consequently the easier and more convenient life.

Well-being and health:
Refers to the impacts of services on improving health condition for living, e.g. the indoor air quality improvement.

Maintenance and fault prediction, detection and diagnosis:
It demonstrates the impacts of the services on technical building services' maintenance and operation by automatic fault detection which can consequently contribute to the energy performance improvements.
Information to occupants: Refers to the impacts of services on providing occupants with information regarding the quality of building service operation In the new report, the "self-generation" impact criterion has been removed because of the overlaps with "energy flexibility and storage" which concentrate on the benefits for energy grid and "convenience" which covers autonomy in terms of security of supply. Recent changes in the impact criteria are presented in Figure 3.6.

Calculation Methodology
The proposed SRI calculation by the European Commission is based on a multicriteria assessment to deal with multiple domains and impact criteria. The overall SRI score indicates how the building's performance is close to or far from its maximum level of smartness. This methodology can be implemented through on-site inspections by building owners or third-party external assessors. As technology develops, the assessment can be done by intelligent equipment in a less intrusive and costly way. This methodology aims to define a straightforward way to obtain a simple indicator which clearly represents the tangible information regarding the overall smartness level of technical building systems in a cost-effectively way. The ongoing calculation developments try to make the methodology flexible enough to adapt with different building type, climate, culture and even all the updates for the innovative services. To have a simple approach into the calculation methodology, it can be divided into 5 steps which are explained as follows: Step1: Relevant Service Selection In the first step, the relevant smart ready services in the building are detected through a triage process. Depending on the building type or other factors some services defined in the catalogue that are not relevant can be easily removed from the calculation procedure.
Step2: Functionality Level Assessment The functionality level is assessed for each of the applicable services in the building based on the defined impact criteria. This can be done based on information gathered from a visual inspection during a walk-through visiting of the building, an interview with the building owner or facility manager and the review of documentation of the technical building systems. Figure 3.7 illustrates the framework for the functionality level assessment.
Each functionality level for each smart service is attributed by a predefined score in the calculation tool (currently a spreadsheet) in each of the eight impact criteria. The functionality levels are defined in the spreadsheet provided by the European Commission and with the range from -4 to 4. The functionality level of each service is selected based on the description provided for each level in the spreadsheet. Table 3.12 presents an example of functionality levels together with relative impact scores provided in the spreadsheet.  domain scores. For each impact criterion, the overall score is expressed as a per cent of the maximum score that is achievable for the building type that is evaluated. Figure 3.8 shows how an impact score is calculated for a specific domain. For more clarification, an example of one impact criterion (energy saving) score calculation for heating domain regarding the scores obtained by services according to their functionality levels in relation to the maximum achievable score for the building is presented in Table 3.12.      The way that this indicator will be presented to the end-users is very important to be clear and sufficiently convey useful information regarding overall SRI, scores per domain and per impact criterion as well as aggregated scores per impact criterion. The mnemonics that are currently used (not yet officially) to simply present the SRI level are shown in Figure 3.12. The study team is still working to develop ideas for designing a way for the best visual presentation. It is important to note that the designing should be easily recognizable from current energy label. Also, the related information should communicate to users in a printed document including a certificate with the potential guidance to improve SRI as well as a physical mnemonic and logo with scores.

Weighting coefficient definition in multi-criteria assessment
As it was mentioned before, the calculated scores for domains and impact criteria need to be aggregated to cover all possible impacts of different factors regarding building type and climate conditions. For this aim, the weighting factors should be determined and apply in the SRI assessment process. Before the recent report published on 21 st of February 2020 [26], there was not any structured methodology for obtaining the weighting coefficient. Therefore, a survey was conducted as an alternative to define the weighting factors. This survey and the recent methodology developed by the study team will be described in the next sections.

Survey-based method
A possibility to obtain the weighting factors is to collect the experts' opinion in various fields through conducting a survey. The professionals can be selected from different field of studies or expertise including architecture, technical designing, manufacturing, energy supplement, economy, building facility, construction. After determining the geographical location of participants (to take into account the climate factor), they are asked to evaluate the effect of each impact score on 10 domains by scoring them ranging from 0-100 which must be divided between different domains. The average score obtaining from all participants will determine the weighting coefficient for each impact criteria. A greater number of participants from various field of expertise will lead to more precise results. The

Proposed method in the technical study
This methodology for the definition of the weighting factors was proposed in the recent report by the study team and it was tested by several stakeholders with the positive feedback. However, there were some arguments to give more weight towards some impact criterion. As it is shown in Figure 3.14, three types of weighting factors are defined in this methodology: fixed weights, equal weights and energy balance weights.
Step 1 considers 20% weighting for the domain "monitoring and control" for all impact criteria, 5% weighting for the domain "dynamic envelope" for energy savings, maintenance and fault prediction and energy demand flexibility impact criteria. If no service exists for a certain domain, it is considered as zero. In step 2, the impact criteria "comfort", "convenience", "information to occupants" and "health and well-being" have the equal weighting coefficients which are obtained by dividing the remaining scores (excluding fixed weight) by the number of relevant domains in the given impact criterion. In setp3, for the impact criteria "energy savings", "maintenance and fault prediction" and "energy demand flexibility" the energy balance weights are assigned based on the building type (residential and non-residential) and the climate zones. Proposed approach for weighting factors [26] This value is obtained by multiplying the remaining weight for the given impact criterion (excluding fixed weights) by the relative importance of the domain in the energy balance defined by the study team for different building types and climate zones (Table   3.14). A building-specific energy balance should be defined based on the primary energy uses for space heating, domestic hot water, space cooling, controlled ventilation, lighting and production of on-site renewable electricity [26]. The correction factor for each domain is calculated by dividing the primary energy use of the given domain by the sum of the six primary energy consumption which can be obtained from EPC calculations.
Considering these steps, the final weighting matrix for different building types and climate zones are provided in [26]. Table 3.16Table 3.15 represents an example of these matrices for a non-residential building in southern Europe climate zone. Also, the suggested climate zones for European countries is shown in Table 3.16 in which Portugal is located in the southern Europe climate zone.

Conclusion
The SRI calculation framework proposed in the first and second technical studies by DG energy was presented and analyzed in this chapter. In the latest study, the DSM domain and the self-generation impact criterion was omitted. Therefore, the number of domains reduced to nine and the number of impact criteria reduced to seven. Also, for all domains, some smart services were removed, and some new services were added.
Furthermore, the methodology to obtain weighting coefficient was unclear in the previous technical studies which it was developed and introduced with more details considering the building type and climate zones in the recent study. Besides, an aggregation was conducted to calculate the overall SRI based on the weighted average of the relevant impact criteria.
This methodology will be examined in the case study buildings in the next chapter.

Introduction
After introducing the SRI calculation methodology in the previous chapters, this method will be implemented in two case study buildings (non-residential buildings) which are located in the same climate zone. So, it provides the opportunity to compare the SRI and its effect on the energy performance and thermal comfort in two similar buildings with different services. To assess the possible impacts, a sort of IEQ measurements and energy simulation will be done and the results will be analyzed in this chapter.

Climatic data of the study area
The case study buildings are located in the city of Coimbra

Project data
Building Name Itecons1 Type Service Year

Project data
Building name Itecons2 Type Service Year of construction 2015 Energy Class C

External walls
North and south orientation: 15

Methodology application in the case building
The first step to take in order to start calculating the indicator is to study the building and its characteristics well in order to be able to choose the services present in it.
With the consultation of the technical sheets and a subsequent inspection of the building, it was possible to select the services present in it from those proposed in the catalogue attached to the European project document.
As it was described in the chapter3, in order to find weighting coefficient for the case study building a survey was conducted and experts from different area of interest and expertise were asked to evaluate the effects of each impact criterion on 10 proposed domains according to their knowledge and experience. The results of the survey conducted in Coimbra, Portugal for a service building is shown in Table 4.1.

SRI calculation for Itecons1
In the triage process, some domains have been eliminated according to certain directives given in the European project and the building characteristics. The domains not taken into account in the calculation of the Itecons1 indicator are identified in bellow: • Controlled ventilation • Electrical vehicle charging • On-site generation The services considered for the evaluation of SRI are resumed in the Table 4.2 in which it is possible to find the functionality level assigned and the changes in the recent study.

SRI calculation for Itecons2
In the building Itecons2, the domains can be excluded from calculation is just "electric vehicle charging" domain and the other defined domains are involved in the calculation process. The services considered for the evaluation of SRI are presented in Table   4.5 in which it is possible to find the functionality level assigned.  According to the methodology provided in the first technical study that was described in chapter3, the overall SRI for this building is 34%. Considering the calculation methodology introduced in the second technical study, the overall scores obtained in two different ways.
It is equal to 33% if the SRI obtained by simple averaging the impact scores or it is 26% when the aggregated factors considered for each impact criterion (as it was explained in chapter 3).  As it was mentioned before, an approach to present the calculation outcomes is to show the relative scores of the impact criteria compare with the ideal scores of the building which indicate how far is the building from its ideal point and what are the strengths and weaknesses of the building in terms of smartness. Figure 4.5 shows the relative scores of impact criteria for Itecons1 and Itecons 2. From this chart, it can be seen that the relative scores of all impact criteria for Itecons2 are higher than that of for Itecons1 owing to employing smarter control system in heating and cooling systems and utilizing ventilation system and electricity generation. However, this difference is much higher for the "Information to occupants" impact criterion which is mainly because of employing a system in the building providing real-time and historical information regarding indoor air quality.
This system uses and presents the data from the sensors which are installed in both buildings, but as this service is introduced in the controlled ventilation domain, which is not applicable for Itecons1 building, this building is excluded from the scores related to this service that could be one of the weak points of this methodology which should be solved in the next studies. The other point is that in both buildings there is a severe lack of services which manage the flexibility for grid and storage. Therefore, one of the main possible improvement of smartness in the buildings would be utilizing storage for the energy generation, management and optimization energy supply and consumption.

Potential actions for SRI improvement
One of the positive points of the methodological approach for SRI calculation proposed by DG Energy is that in each study, a specific building is compares with its ideal situation. This idea assists to recognize the potential improvements to make the level of smartness of a building as close as possible to its maximum smartness level. Table 4.8 and   Table 4.9 show the relative scores for the impact criteria for each relevant domain in Itecons1 and Itecons2 buildings respectively. From these tables, the following points can be considered: Although there are services to supply hot water in both buildings, the lack of control systems for storage charging and systems for report hot water generation performance to occupants causes this domain obtains no score in any impact criterion.
Therefore, one possible action for SRI improvement could be installing controllers for automated storage charging based on external signals (temperature, demand...) and controllers for performance evaluation, predictive management and fault prediction.
However, regarding the type of buildings, investment in this domain seems irrational. Scores in heating and cooling domains are relatively low for both buildings, even for the one with implemented retrofit actions, which shows that the applied measures were not supposed to improve smartness. The role of the smart services in these two domains is mainly to improve energy savings, comfort and convenience in the building. The scores of these domains can be improved by using sensors for occupancy detection for demand-side management, advanced central temperature control, manage the distribution parts by installing variable speed pump control, variable control of heat pumps' capacity depending on the load and external signals from the grid, systems to report the information regarding performance evaluation of heating and cooling systems and predictive management and fault predictions controllers.  flow control using air quality sensors, advanced modulate heat recovery control which controls multiple rooms and using outside air to minimize mechanical cooling. This domain is already being of high scores in "Maintenance and fault prediction" and "Information to occupants" owing to the existing advanced monitoring system for real-time and historical information regarding IAQ.
Although there is already the motorized operation for solar shading control in Itecons2 building, a possibility is to link this system with the HVAC control based on the data collected from temperature sensors. Also, using automated operable windows to help HVAC systems, e.g. to control free natural night cooling is an option to improve SRI.
Another potential is to strengthen the control operation of the electricity generation system in Itecons2 by providing a storage system for locally generated electricity, consumption optimization by using systems to predict the electricity needs in the building.
This system with the combination of the current forecast system of solar electricity generation could effectively enhance the score of this domain.           including thermal comfort, lighting, acoustic and indoor air quality. For acoustic and lighting is difficult to apply these categories as it depends on the building's type. The other measured parameter to assess IEQ is the amount of VOCs in the air.
Many elements used in everyday life emit VOCs for example perfumes, cleanser, paints and also some building materials or elements that contain glues. The most effective way to reduce the negative impacts of pollutants in the indoor air is using ventilation system or it would be better to reduce or avoid the emissions [35]. The level of VOCs can be assessed using air quality index (AQI) which is presented in Table 4.11. The measurement taken in both days chosen for this research gave values of VOCs between 33 and 43 for the room in Itecns1 and between 30 and 40 for the room in Itecons2. The range between 0 and 50 corresponds to the green color and it means that the AQI is "good" or "healthy". This category certifies that the pollution detected does not create risks, or in case they are small ones [36]. The information related to the lights is all contained in the European Standard UNI EN 12464-1 [37], in which all the minimum illuminance requires for indoor workplaces to guarantee the visual comfort are defined. The minimum lux required for offices for the normal works writing, typing, reading, data processing is 500. In the last day chosen, the 16 of Jan the average of lux data was 1013 for the room in Itecons1 and while for the room in Itecons2 it was 382. These high difference between values are only related to natural light difference transmitted from the larger glazing area.      Selection among the retrofit technologies is not an easy task and needed to be in line with energy efficiency, indoor environment quality and global environment improvement in a cost-effective way. In other words, the main objective of a retrofit project is to implement a set of optimum solutions for energy demands and CO2 emissions minimization, while maximization of the economic efficiency and indoor environmental quality. It is also important to consider the tradeoff between different goals that can be achieved by implementing different retrofit actions and beyond that, optimizing one of the achievements can subsequently compromise other goals which can be optimized by using a multi-objective strategy [39]. More specifically, technologies are utilized in building retrofitting in order to reduce heating and cooling loads, annual energy consumption, annual emission effective on global warming, life-cycle environmental impact, water consumption, while increase the thermal sensation, visual comfort, indoor air quality, and acoustic comfort [40]. In terms of financial objectives, the direct and initial costs, the ongoing cost, life cycle costs (LCC) and the energy-saving cost need to be evaluated during a building retrofit strategy.
According to European commission [41]  The most outstanding difference of building behavior in the Mediterranean region compared to the rest of Europe is the higher cooling demand of buildings in the hot and long summers of Mediterranean climate. Therefore, one of the main concentrations of building retrofitting in the Mediterranean area seems to be implementing effective technologies to reduce the cooling demand, improve indoor air quality and provide thermal comfort for occupants. Moreover, utilizing of passive cooling opportunities such as natural ventilation, effective shading and high thermal mass building envelope material, is also applicable in the Mediterranean building which can effectively contribute to reducing energy consumption in the cooling seasons.
As it was mentioned before, a sort of energy-efficient technologies has been implemented in one of the case study buildings (Itecons2) which leads to a better energy performance compared with the other one. Since both buildings are located in the same location and have almost same architectural characteristics, the energy-efficient technologies applied in the Itecons2 can be considered as the retrofitted actions that can be implemented in the same building (Itecons1). Therefore, these technologies will be introduced in this section and their actual effects on energy performance and SRI improvements will be described in the next sections.
To reduce the energy dependence to the grid, the photovoltaic solar system is used for mini energy production, installed in building roof, composed of 92 Open PQ60 collectors (240 Wp power class) along in two lines, with a nominal power of 22.08 kW. The system is installed on the roof, in the south orientation and with an inclination of 30º. Air renewal system installed in the building roof guarantees the indoor air quality and reducing energy consumption through heat recovery. It is equipped with a ventilation module with plug-fun fans, a filter module, a rotary heat recovery unit and a direct expansion battery for heating and cooling (thermal correction) of the outside air. The supply power and the extraction power are 3 kW and 2.2 kW respectively. The motorized window shading which is categorized as the dynamic building envelope system enables the building facade to adjust the solar lighting transmitting into the indoor space based on the information it receives from inside sensors. As this technology applied to the south orientation windows, it would be an effective way to reduce the energy demand of both heating and cooling.

Energy performance simulation
Building simulation is an effective tool to model the energy behavior and estimate the heating and cooling of a building. Energy simulation provides an overview of the quality of energy performance in a building. For this purpose, Design builder software was used to model the internal gains, thermal comfort and heating and cooling loads in two monitored room in Itescons1 (area=75.4 m 2 ) and Itecons2 (area=104 m 2 ) buildings. The glazing area for the monitored room in Itecons 1 is equal to 45.8 m 2 and for the room in Itecons 2 is equal to 9.3 m 2 . For better comparison, the glazing area for the room in Itecons1 was reduced in the software's input to be equal to the glazing area for the room in Itecons2.     The annual amount of the internal gains in the monitored rooms of the case study buildings shows that using the motorized shading for windows in the room in Itecons2 able to adjust the solar gains transmitting into the indoor space in summer and assist in reducing cooling loads (Figure 4.27). It is also shown that the main energy consumer in both buildings is electrical appliances and lighting system.

Conclusion
In this chapter, the SRI calculation methodology was analyzed and implemented in the case study buildings. Also, the relation between building smartness, thermal comfort and energy consumption was evaluated using IEQ and thermal comfort assessment and energy simulation. The effects of retrofit actions on thermal comfort, energy-saving and SRI improvement are summarized in Table 4.12. The main retrofitting actions and their effects on thermal comfort, energy-saving and SRI are as follows: • Heating domain: Multi-stage control of heat generator capacity depending on load or demand which mainly contribute to SRI, thermal comfort and energy-saving improvement in Itecons2.
• Cooling domain: Variable control of cooling production capacity depending on load or demand which effectively contribute to SRI, energy-saving and thermal comfort improvements.
• Ventilation domain: Using ventilation system together with real-time monitoring and historical data of IAQ in the Itecons2 not only improves the thermal comfort and IEQ in the spaces but also enhances SRI and contribute to energy-saving.
• Building envelope domain: Using motorized control of window shading in Itecons2 which is mainly effective on reducing cooling loads and consequently energy consumption for cooling.
• Electricity generation domain: Photovoltaic panels in the Itecons2 with reporting information services with the ability to performance evaluation and forecasting which mainly contribute to SRI improvement through increased interaction with occupants.

CONCLUSION AND FUTURE WORKS
The main focus of this work was presenting, analyzing and implementing the smart readiness indicator (SRI) which has been recently introduced by the revised EPBD.
The methodological framework for SRI calculation is still under development by DG Energy using the active and ongoing feedback from stakeholders and the Member States. Then, the proposed SRI calculation methodology was analyzed and implemented in two case study buildings in Portugal. Also, in one of the buildings a sort of retrofit actions was implemented so because of the similar structure of the buildings it was possible to evaluate the effects of some common building retrofitting actions on the level of smartness specifically in the Mediterranean climate region.
To summarize, some issues have been observed during the analysis calculation methodology which needs more studies and investigations. First, identifying the functionality levels of the smart ready services needs a group of experts who have access to the technical documents of the building services. However, even in some cases the functionality levels should be more clarified to minimize the personal judgment on the selection and scoring the services. Second, in some buildings, such as service buildings, the same services are assigned for different functionality levels in different zones. For example, manual or automatic control of lighting system in rooms or common areas of a nonresidential building. In these cases, it was not clarified how the overall functionality level for that service can be calculated. The other issue is that in some cases a building cannot receive scores for a certain service because it is defined in a domain that does not exist in the building. For instance, although one of the case study buildings in this work has a monitoring service to receive IAQ data, it cannot be scored by this because this service was defined in the "ventilation" domain category which does not exist in the building. The other issue which needs to be analyzed is that the existence of some services is not of importance in some types of buildings, such as DHW services in the office or services buildings. So, as these services are not used frequently, their level of smartness is not effective and the investments will be with low payback. On the other hand, the relative scores of these services are usually too low or equal to zero which negatively affects the overall SRI score of the building. Finally, it should be noted that to have an optimal outcome of digitalization the technical building services, it is more effective to use of all smart services with the maximum functionality level in all domains to minimize the occupants' interference as much as it is possible. For example, if the windows operate manually, not automatically integrated with an HVAC system, in a room in which the heat emission controlled with the maximum functionality level, the occupants' choice in opening or closing the window will reduce the effectiveness of the heating control system.
Regarding the effects of possible retrofit actions, it can be concluded that if the retrofit actions are selected not only based on the building retrofitting objectives but also based on the functionality level enhancement of smart services, they would also contribute to SRI improvement. However, this improvement would be related to responding to occupants' needs but is not necessarily effective to adapt in response to the building operation and energy grid.
Thus, the introduced methodological framework of SRI needs more studies and development to consider all possible aspects and resolve the current issues. Furthermore, regarding building retrofitting, SRI improvement can be considered as one of the retrofitting objectives besides energy saving, thermal comfort, environmental impacts and cost.
Therefore, by developing a multi-objective selection approach, the possible building retrofit actions will be chosen based on their effectiveness on SRI together with the other improvements.