Feasibility study of a social housing energy retrofit project

UNIVERSIDAD DE VALLADOLID ESCUELA DE INGENIERIAS INDUSTRIALES Grado en Ingeniería en Organización Industrial FEASIBILITY STUDY OF A SOCIAL HOUSING ENERGY RETROFIT PROJECT Autor: Teixeira Luciano, Leandro Filipe Responsable de Intercambio en la Uva: Francisco Javier Rey Martínez Universidad de Malta Valladolid, junio 2019. TFG REALIZADO EN PROGRAMA DE INTERCAMBIO TÍTULO: FEASIBILITY STUDY OF A SOCIAL HOUSING ENERGY RETROFIT PROJECT ALUMNO: Leandro Filipe Teixeira Luciano FECHA: 24/06/2019 CENTRO: University of Malta TUTOR: Charles Yousif Resumen (Abstract) El objetivo principal es identificar la combinación más adecuada de medidas pasivas de acondicionamiento para mejorar el confort térmico y el rendimiento energético en bloque de viviendas sociales (BVS) en Malta. Se modeló un BVS utilizando el software dinámico DesignBuilder-EnergyPlus. Se utilizaron los modelos de confort adaptativo EN 15251 y ASHRAE para evaluar el confort térmico en el piso superior del BVS, demostrando que tiene los peores niveles de comodidad. Los resultados mostraron que el confort térmico adaptativo no se cumple. Sin embargo, una vez que se introducen todas las medidas pasivas de acondicionamiento se alcanzan los niveles de confort térmico adaptativo. El análisis financiero y macroeconómico resultaron ser negativos. Otros beneficios sociales, como la reducción de la pobreza energética, la mejora de la comodidad y el bienestar de los ocupantes y la reducción de las cargas máximas en la central eléctrica, la viabilidad global de renovar los BVS se vuelve más atractiva. Palabras claves (Keywords): EPBD; acondicionamiento; nZEB; DesignBuilder; adaptativo FEASIBILITY STUDY OF A SOCIAL HOUSING ENERGY RETROFIT PROJECT Leandro Filipe Teixeira Luciano Institute for Sustainable Energy University of Malta June 2019 FEASIBILITY STUDY OF A SOCIAL HOUSING ENERGY RETROFIT PROJECT Leandro Filipe Teixeira Luciano A dissertation presented at the Institute for Sustainable Energy of the University of Malta, Malta in partial fulfilment of the requirements for the degree of Bachelor of Industrial Engineering at the Universidad de Valladolid, Spain, under the Erasmus Plus Student Exchange Programme 2018/19. Dedicated to my mother María, my father Manuel and my two sisters María and Daniela Declaration No portion of the work referred to in the dissertation has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning. Signature of Student Name of Student June 2019 Date Copyright Notice 1) Copyright in text of this dissertation rests with the Author. Copies (by any process) either in full, or of extracts may be made only in accordance with regulations held by the Library of the University of Malta. Details may be obtained from the Librarian. This page must form part of any such copies made. Further copies (by any process) made in accordance with such instructions may not be made without the permission (in writing) of the Author. 2) Ownership of the right over any original intellectual property which may be contained in or derived from this dissertation is vested in the University of Malta and may not be made available for use by third parties without the written permission of the University, which will prescribe the terms and conditions of any such agreement.” I Abstract Retrofitting of existing buildings have been given greater attention than new buildings in the new Energy Performance of Buildings Directive (EU) 2018/844 of July 2018. Moreover, all deep-renovated buildings have to reach nearly zero-energy status after the year 2020. Consequently, this dissertation has identified the renovation opportunity in existing social housing building stock. The main aim is therefore to identify the most suitable combination of retrofit passive measures to improve the thermal comfort and energy performance of the social housing building stock in Malta. For this scope, a typical social housing building block built in the 1990s, prior to the introduction of minimum energy performance requirement and synonymous with many existing social housing projects was modelled using DesignBuilder-EnergyPlus dynamic software. Once the EnergyPlus building model was calibrated with hourly on-site temperature measurements, the EN 15251 and ASHRAE adaptive comfort models were used to asses thermal comfort for the top-floor dwellings of the building block, which was shown to have worst comfort levels, based on occupants’ questionnaire feedback and measured temperatures. Results showed that adaptive thermal comfort does not comply with EN 15251 Category II and ASHRAE 80% thermal acceptability requirements for both the summer and winter design weeks. However, once insulation is added to the envelope, external blinds are introduced and double glazing replace single glazing, the adaptive thermal comfort levels are attained. Thus, thermal comfort is achievable for the top-floor using passive measures alone without the need for air-conditioners. Furthermore, a sensitivity analysis showed that while all passive measures introduced are required for thermal comfort to be achieved, roof insulation and external blinds have the highest impact and should thus be prioritised. A life cycle financial analysis was also carried out. It was found that from the consumer’s point of view, the most viable option would be to leave the building envelope as is and introduce air-conditioners to achieve thermal comfort, given that the cost of grid electricity is relatively low. The same results were achieved from a macroeconomic financial point of view, when accounting for the cost of carbon emissions. However, when other social benefits are considered, such as reducing energy poverty, improving the comfort and well-being of occupants and reducing the peak loads on the power station, the global viability of renovating social housing blocks becomes more attractive. This shows that future directives should also consider these social benefits in addition to the cost of carbon, to facilitate the introduction of such passive measures in Europe. VIII Figure 51: Discomfort hours percentages for ASHRAE adaptive comfort model in Winter with measures per orientation ........................................................................... 75 Figure 52: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Winter with measures per orientation ....................................................................... 75 Figure 53: Discomfort hours percentage for EN 15251 adaptive comfort model in Winter with measures per orientation ....................................................................................... 76 Figure 54: Winter design week ASHRAE and M. Vellei et al. [36] comfort analysis for Bedroom 1B when all measures are implemented facing North orientation ................ 77 Figure 55: Winter design week EN 15251 comfort analysis for Bedroom 1B when all measures are implemented facing North orientation .................................................... 78 Figure 56: Winter design week number of discomfort hours for Bedroom 1B when all measures are implemented facing North orientation .................................................... 78 Figure 57: Discomfort hours percentages for ASHRAE adaptive comfort model in Summer with measures without façade insulation and double glazing per orientation 86 Figure 58: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Summer with measures without façade insulation and double glazing per orientation ....................................................................................................................................... 86 Figure 59: Discomfort hours percentage for EN 15251 adaptive comfort model in Summer with measures without façade insulation and double glazing per orientation 87 Figure 60: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures ................................................................................ 88 Figure 61: Summer design week EN 15251 comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures ........................................................................................................................ 89 Figure 62: Summer design week number of discomfort hours for different combination of measures for the Bedroom 1A facing North orientation .......................................... 90 Figure 63: Discomfort hours percentages for ASHRAE adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation .. 91 Figure 64: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation ....................................................................................................................................... 91 Figure 65: Discomfort hours percentage for EN 15251 adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation .............. 92 Figure 66: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures ................................................................................ 93 Figure 67: Winter design week EN 15251 comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures ........................................................................................................................ 94 Figure 68: Winter design week number of discomfort hours for different combination of measures for the Bedroom 1A facing North orientation ............................................... 94 IX Figure 69: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the ASHRAE adaptive comfort model .............. 122 Figure 70: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the M. Vellei et al. [35] model .......................... 123 Figure 71: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the EN 15251 adaptive comfort model ............. 123 Figure 72: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the ASHRAE adaptive comfort model .............. 124 Figure 73: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the M. Vellei et al. [35] model .......................... 125 Figure 74: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the EN 15251 adaptive comfort model .............. 125 Figure 75: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the ASHRAE adaptive comfort model .............................................................................................. 126 Figure 76: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the M. Vellei et al. [35] model .......................................................................................................... 126 Figure 77: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the EN 15251 adaptive comfort model .............................................................................................. 127 Figure 78: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the ASHRAE adaptive comfort model ................ 127 Figure 79: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the M. Vellei et al. [35] model ............................. 128 Figure 80: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the EN 15251 adaptive comfort model ................ 128 Figure 81: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the ASHRAE adaptive comfort model ........................................................................................................................... 129 Figure 82: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the M. Vellei et al. [35] model ..................................................................................................................................... 129 Figure 83: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the EN 15251 adaptive comfort model ........................................................................................................................... 130 Figure 84: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration on the ASHRAE adaptive comfort model .............. 130 X Figure 85: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration on the M. Vellei et al. [35] model .......................... 131 Figure 86: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration on the EN 15251 adaptive comfort model ............. 131 Figure 87: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented on the ASHRAE adaptive comfort model .............................................................................................. 132 Figure 88: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented on the M. Vellei et al. [35] model ......................................................................................................... 132 Figure 89: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented on the EN 15251 adaptive comfort model .............................................................................................. 133 Figure 90: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation on the ASHRAE adaptive comfort model ................ 133 Figure 91: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation on the M. Vellei et al. [35] model ............................. 134 Figure 92: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation on the EN 15251 adaptive comfort model ................ 134 Figure 93: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the ASHRAE adaptive comfort model ........................................................................................................................... 135 Figure 94: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the M. Vellei et al. [35] model ..................................................................................................................................... 135 Figure 95: Base scenario number of Discomfort Hours during the Winter design week for windows close configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the EN 15251 adaptive comfort model ........................................................................................................................... 136 Figure 96: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1A facing North orientation using different windows opening configurations ..................................................................................................................................... 137 Figure 97: Summer design week EN 15251 comfort analysis for Bedroom 1A facing North orientation using different windows opening configurations ........................... 138 Figure 98: Summer design week number of discomfort hours for Bedroom 1A facing North orientation using different windows opening configurations and adaptive comfort models ......................................................................................................................... 138 Figure 99: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Kitchen facing North orientation using different windows opening configurations .. 139 XI Figure 100: Summer design week EN 15251 comfort analysis for Kitchen facing North orientation using different windows opening configurations ..................................... 140 Figure 101: Summer design week number of discomfort hours for Kitchen facing North orientation using different windows opening configurations and adaptive comfort models ......................................................................................................................... 140 Figure 102: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1C facing East orientation using windows open configuration ............. 141 Figure 103: Summer design week EN 15251 comfort analysis for Bedroom 1C facing East orientation using windows open configuration using different combination of measures ...................................................................................................................... 142 Figure 105: Summer design week number of discomfort hours for different combination of measures for Bedroom 1C facing East orientation ................................................. 142 Figure 105: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Kitchen facing East orientation using windows open configuration and using different combination of measures .............................................................................. 143 Figure 106: Summer design week EN 15251 comfort analysis for Kitchen facing East direction using windows open configuration and using different combination of measures ...................................................................................................................... 144 Figure 107: Summer design week number of discomfort hours for different combination of measures for the Kitchen facing East orientation ................................................... 144 Figure 108: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Dining facing East orientation using windows open configuration and using different combination of measures ............................................................................................ 145 Figure 109: Summer design week EN 15251 comfort analysis for Dining facing East orientation using windows open configuration and using different combination of measures ...................................................................................................................... 146 Figure 110: Summer design week number of discomfort hours for different combination of measures for the Dining facing East orientation .................................................... 146 Figure 111: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1C facing North orientation using windows close configuration ............... 147 Figure 112: Winter design week EN 15251 comfort analysis for Bedroom 1C facing North orientation using windows close configuration ................................................ 148 Figure 113: Winter design week number of discomfort hours for Bedroom 1C facing North orientation using windows close configuration and different comfort models 148 Figure 114: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1C facing North orientation using windows open configuration and using different combination of measures .............................................................................. 149 Figure 115: Winter design week EN 15251 comfort analysis for Bedroom 1C facing North orientation using windows open configuration and using different combination of measures ...................................................................................................................... 150 Figure 116: Winter design week number of discomfort hours for different combination of measures for the Bedroom 1C facing North orientation ......................................... 150 XII Figure 117: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1C facing West orientation using windows open configuration and using different combination of measures .............................................................................. 151 Figure 118: Winter design week EN 15251 comfort analysis for Bedroom 1C facing West orientation using windows open configuration and using different combination of measures ...................................................................................................................... 152 Figure 119: Winter design week number of discomfort hours for different combination of measures for the Bedroom 1C facing West orientation .......................................... 152 Figure 120: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Dining facing North orientation using windows open configuration and using different combination of measures ............................................................................................ 153 Figure 121: Winter design week EN 15251 comfort analysis for Dining facing North orientation using windows open configuration and using different combination of measures ...................................................................................................................... 154 Figure 122: Winter design week number of discomfort hours for different combination of measures for the Dining facing North orientation .................................................. 154 Figure 123: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Dining facing West orientation using windows open configuration and using different combination of measures ............................................................................................ 155 Figure 124: Winter design week EN15251 comfort analysis for Dining facing West orientation using windows open configuration and using different combination of measures ...................................................................................................................... 156 Figure 125: Winter design week number of discomfort hours for different combination of measures for the Dining facing West orientation ................................................... 156 XIII List of Tables Table 1: Description of the applicability of the categories used [25] ........................... 14 Table 2: 7-Point thermal sensation scale [25] ............................................................... 15 Table 3: Recommended categories for design of mechanical heated and cooled buildings [25] ................................................................................................................................ 16 Table 4: Examples of recommended design values of the indoor temperature for design of buildings and HVAC systems [25] ........................................................................... 17 Table 5: Recommended design criteria for the humidity on occupied spaces[25] ....... 22 Table 6: Basic required ventilation rates for diluting emissions from people for different categories [25] ............................................................................................................... 23 Table 7: Basic required ventilation rates for building emissions [25] .......................... 23 Table 8: Building envelope properties and materials ................................................... 40 Table 9: Retrofit measures considered and their properties .......................................... 48 Table 10: Blind/slat properties ...................................................................................... 49 Table 11: Prices of each potential retrofit measure [63] ............................................... 54 Table 12: MLR Significant variables out of 26 observations ....................................... 57 Table 13: Discomfort - Comfort answers percentages per floor level .......................... 57 Table 14: Temperature statistical calibration indicators for the bedroom in which the data logger was installed (Bedroom 1 B) ...................................................................... 59 Table 15: Humidity statistical calibration indicators for Bedroom 1B ......................... 59 Table 16: Base Comfort analysis codification .............................................................. 59 Table 17: Base Comfort analysis and implementation of potential retrofit measures codification ................................................................................................................... 70 Table 18: Standardized Coefficients Beta for the Summer design week for the EN 15251 Category II discomfort hours ........................................................................................ 80 Table 19: Standardized Coefficients Beta for Summer design week for the ASHRAE 80% acceptability adaptive comfort model ................................................................... 81 Table 20: Standardized Coefficients Beta for Winter design week for heat loads ....... 82 Table 21: Base Comfort analysis and implementation of potential retrofit measures, all retrofit measures without façade insulation and all retrofit measures without double glazing codification ....................................................................................................... 85 Table 22: Actual Building with A/C vs Building with All measures per orientation ... 95 Table 23: Actual Building with A/C vs Building with All measures + A/C per orientation ....................................................................................................................................... 96 Table 25: Actual Building with A/C vs Building with All measures - façade insulation per orientation ............................................................................................................... 97 XIV Table 26: Actual Building with A/C vs Building with All measures + A/C - façade insulation per orientation .............................................................................................. 98 Table 27: Actual Building with A/C vs Building with All measures - façade insulation - double glazing per orientation ...................................................................................... 99 Table 28: Actual Building with A/C vs Building with All measures +A/C - façade insulation - double glazing per orientation ................................................................. 100 Table 29: Questionnaire results for block house A ..................................................... 118 Table 30: Questionnaire results for block house B ..................................................... 119 Table 31: Questionnaire results for block house C ..................................................... 120 Table 32: Questionnaire results for block house D ..................................................... 121 XV List of Abbreviations A/C Air Conditioner AECD Annual Electric Consumption per Dwelling ASHRAE American Society of Heating, Refrigerating and Air-Conditioning Engineers BRB Building Regulation Board CBE Center for the Built Environment CBSA Computer Based Simulation Audit CIBSE Chartered Institution of Building Services Engineers CV(RMSE) Coefficient of Variance of the Root Mean Square Error DHW Domestic Hot Water DPP Discount Payback Period ECMs Energy Conservation measures EC Energy Consumption EE Energy Efficient EED Energy Efficiency Directive EI Effectiveness Index EPBD Energy Performance of Buildings Directive EPI Energy Performance Indicator EPS Expanded Polystyrene Standard ERDF European Regional Development Fund EU European Union GDPR General Data Protection Regulation HP Heat Pumps HVAC Heating, Ventilation and Air Conditioning IAQ Indoor Air Quality IET Indoor Thermal Environment IRR Internal Rate of Return ISO International Organization for Standardization M&C Maintenance and Verification XVI MEPRS Minimum Energy Performance Requirements MLR Multiple Linear Regression NCM National Calculation Methodology NEEAP National Energy Efficiency Action Plan NMBE Normalized Mean Bias Error NPV Net Present Value NREAP National Renewable Energy Action Plan NZEB Nearly Zero Energy Building nZEH near Zero Energy Home PB Payback PL Plug Loads PMV Predicted Mean Vote PPD Predicted Percentage of Dissatisfied PV Photovoltaic System RE Renewable Energy RED Renewable Energy Directive RH Relative Humidity SA Standard Audit SPP Simple Payback Method/Period T&C Test and Commissioning VAT Value Added Tax WH Water Heater WTA Walk Through Audit 1 Introduction The building sector is responsible for the 40% of EU’s energy consumption. By 2050, the EU aims to reduce up to 90% of the greenhouse gas emissions in the building sector, but around 90% of EU’s buildings were built before 1990 and the renovation rate is still very low (1 – 2% per year) [1][2]. However, the building sector is adopting the lowcarbon economy roadmap [3]. The energy performance of building is covered by the Energy Performance of Building Directive (EPBD) [4] and the Energy Efficiency Directive (EED) [5]. According to the EPBD, all new buildings and buildings to undergo major renovation are to be nearly zero energy buildings by the end of 2020. By the end of 2020, the EED has established EU measures to achieve its 20% energy efficiency objective. Nonetheless, at present time, the EED from 2012 is been revised and the energy efficiency objective will increase from 20% in 2020 to 32.5% in 2030 [6]. The new EPBD of 2018 has shifted its focus from new buildings to deep renovation of existing buildings, together with energy use of appliances, lighting and healthy indoor climate, requiring EU member states to establish long-term renovation strategies, aiming at decarbonising the national building stocks by 2050 and reach the Nearly Zero Energy Building objective (NZEB). On the other hand, Malta has its own specific strategies, encouraging the use of renewable energy, targeting a 10% of renewable energy, and improving energy efficiency in buildings by 2020 [7][8]. Technical Document F [9][10] stipulates the minimum energy performance for buildings in Malta, setting the minimum requirements for building services through a cost-optimal analysis. However, no guidelines have been specified to successfully energy retrofit housing buildings in practice. This project aims to identify any barriers in renovating housing stocks. In this way, the project can be used by the housing sector in Malta when renovating housing stocks to improve both the energy performance of the building and thermal comfort inside the dwellings. The social housing buildings have been built prior to the existence of the LITERATURE REVIEW 8 conservation measures (ECMs) can be implemented. There are different energy audits, ranging from ‘Walk Through Audit’ (WTA), ‘Standard Audit’ (SA), and the ‘Computer Based Simulation Audit’ (CBSA). For CBSA, the building is designed on a computer-based model, which replicates the energy consumption of the real building, considering the building physical condition and orientation for its calculation. The computer-based model is retrofitted with energy conservation measures for a simulation of what is expected on the renovated building energy consumption. • Phase III: ‘Identification of Retrofit Options’. Thanks to CBSA, various retrofits can be simulated and synthesized into the ones who fit best the extension of the project, performing a compelling economic analysis and risk assessment. • Phase IV: ‘Site Implementation and Commissioning’. The retrofitting measures considered will be implemented on-site and Test and Commissioning (T&C) is then employed, ensuring that the systems operate in an optimal manner. • Phase V: ‘Validation and Verification’. The last phase validates and verifies the expected energy savings. Maintenance and Verification (M&V) [22], [23] can be used to verify energy savings. It is recommended to carry out a post occupancy survey to ascertain if the building occupants are satisfied with the overall retrofit results. Achievement of successful retrofitting in buildings depends on different key elements that have a significant impact on building retrofit (Figure 4). LITERATURE REVIEW 9 Figure 4: Key elements influencing building retrofits [21] Building retrofit technologies can be classified into three groups (Figure 5): • Supply side management: Use of renewable energy technologies, as photovoltaics or wind power systems, to generate green energy and the use of electrical systems retrofit. • Energy consumption patterns: Management and change of human factors. • Demand side management: Can be classified into two different strategies. o Heating and cooling demand reduction through retrofitting building fabric and other advanced technologies as windows shading. o Use of energy efficient equipment and low energy technologies as natural ventilation or thermal storage systems. LITERATURE REVIEW 10 Figure 5: Main building retrofit technologies [21] Different studies had been carried out for Malta on different building retrofit technologies, particularly on the supply side management and energy efficient equipment and low energy technologies due to its few energy resources and climate. Section 2.4 delves deeper into more detailed information about different retrofit technologies and energy efficiency measures used in Malta. The project goal and the client’s environment concern have an important impact on the retrofit technologies’ selection. “It can be found that retrofitting building fabric, building services systems and metering systems requires less cost investment, while providing much more environmental benefits, as compared to retrofit measures using renewable energy technologies” [21] (Figure 6). LITERATURE REVIEW 11 Figure 6: Cost versus environmental benefits (CO2 emissions reduction) of the energy hierarchy [21] Malta is a country with limited land and energy resources. That is why it is so important to consider the energy hierarchy of priorities, when improving the energy performance of buildings. The near Zero Energy Home (nZEH) strategies [24] shown in Figure 7 describe different strategies according to the type of energy resources and their use and cost. Figure 7: The nZEH strategies [24] LITERATURE REVIEW 12 • First stage: ‘Be Lean’ strategy focuses on reducing energy demand as result of an effective and efficient building design and retrofit (energy efficient equipment and low energy technologies). • Second stage: ‘Be Clean’ strategy focuses on using efficiently energy systems to reduce the energy consumption, when the measures taken in ‘Be Lean’ are not enough. • Third stage: ‘Be Green’ strategy focuses on using renewable energies fulfilling the prior stage. Renewable energies depend on location, land and natural resources. That is why Malta should only follow ‘Be Green’ strategies when the two prior stages are carried out, evaluated and implemented; that means, assuring energy efficiency and thermal comfort for occupants. 2.3 Comfort analysis for naturally ventilated buildings and ways to avoid overheating in buildings Introduction Thermal comfort, indoor air quality (IAQ), visual and acoustic comfort are the four main indoor environmental parameters (Figure 8) for design and assessment of energy performance of building addressing. The comfort criteria for these parameters are developed in EN 15251 [25]. LITERATURE REVIEW 13 Figure 8: Different indoor environmental parameters [26] The Standard EN 15251 states: “An energy declaration without a declaration related to the indoor environment makes no sense. Therefore, there is a need for specifying criteria for the indoor environment for design, energy calculations, performance and operation of buildings”. Besides environmental conditions and the build-up of the building, there are individual conditions affecting comfort, such as individual metabolic rate and the type of clothing used [27]. In order to evaluate thermal comfort, the EN ISO 7730 [28] and the CEN CR 1752 [29] form the backbone. These norms define the process to be followed to determine and interpret thermal comfort using the predicted mean vote (PMV) and the predicted percentage of dissatisfied (PPD) indices, as determined by Fanger [30]. EN 15251 helps defining and establishing the main parameters to be used in building energy calculation and long-term evaluation of the indoor thermal environment (IET). When dimensioning room conditioning systems, the thermal comfort criteria shall be used as input for heating and cooling load (EN 12831, prEN 15255) calculations, thus, the minimum room temperature in winter and the maximum room temperature in summer are key factors for the thermal comfort criteria. LITERATURE REVIEW 14 The recommended input values differ according to four different categories, shown in Table 1: Table 1: Description of the applicability of the categories used [25] Thermal Comfort Thermal Comfort has been defined as “that condition of mind that expresses satisfaction with the thermal environment and is assessed by subjective evaluation” [31]. Reaching NZEB targets is an urgency. Half of the energy used in buildings is due to heating, ventilation and air conditioning (HVAC) energy consumption [32]. For Thermal comfort EN 15251 defines two models which are the PMV/PPD model and the adaptive comfort model. The PMV/PPD model is applicable to mechanically heated and cooled spaces, while the adaptive comfort model should be used to assess comfort in buildings without mechanical cooling, that is naturally ventilated. 2.3.2.1 Mechanically cooled and heated buildings – PMV/PPD model The PMV/PDD model depends on the operative temperature, the local air speed, humidity, metabolic rate and clothing level. LITERATURE REVIEW 15 The criteria for the ITE shall be based on the thermal comfort indices: o PMV: “Predicted Mean Vote is and index that predicts the mean value of the votes of a large group of persons on the 7-point thermal sensation scale given in Table 2, based on the heat balance of the human body” [28] o PPD: “Predicted Percentage Dissatisfied is an index that establishes a quantitative prediction of the percentage of thermally dissatisfied people who feel too cool or too warm. Thermally dissatisfied people are those who will vote hot, warm, cool or cold on the 7-point thermal sensation scale given in Table 2.” [28] Table 2: 7-Point thermal sensation scale [25] Both criteria were proposed by Povl Ole Fanger [30], by which he succeeded in explaining that the sensation experienced by a person was a function of the physiological strain imposed on him/her by the environment. Relating both criteria he was able to predict what comfort vote would arise for different environmental conditions. Having the PMV value, we can calculate PPD using the equation (1) below. 𝑃𝑃𝐷=100−95∗exp⁡(−0.03353·𝑃𝑀𝑉4−0.2179·𝑃𝑀𝑉2) (1) We can see PPD as function of PMV in Figure 9. LITERATURE REVIEW 16 Figure 9: PPD/PMV Thermal Comfort Graph [28] According to the different categories we can table (Table 3) the different ranges for the PMV which complies with EN 15251. Table 3: Recommended categories for design of mechanical heated and cooled buildings [25] The PMV/PPD method provides a range of temperatures according to environmental and individual conditions and the building’s build-up. A few examples can be seen in Table 4. These temperatures can be calculated with the tool presented in Section 2.3.5. LITERATURE REVIEW 17 Table 4: Examples of recommended design values of the indoor temperature for design of buildings and HVAC systems [25] The comfort range of a building for both summer and winter based on the PMV/PPD method can be visualised via a psychometric chart. Tools such as Climate consultant can be used to show both the comfort range hourly values of climate data for a typical year on the same psychometric chart. This plot will enable architects and engineers to identify the most suitable passive and active measures to satisfy comfort for a specific climate. Figure 10 shows a psychometric climate plot for Malta and the best measures identified by Climate consultant [33] to achieve comfort. Figure 10: Psychometric chart comfort analysis (PMV/PPD Model) for Malta [34] LITERATURE REVIEW 24 complies with both EN 15251 and ASHRAE adaptive comfort models. For the EN 15251 with this tool one can select one of the methods mentioned; for PMV Method, one just needs to know the operative temperature, the local air speed, humidity, metabolic rate and clothing level (Figure 13), in the other hand, for the EN 15251 adaptive comfort model, one will need to know the operative temperature, the outdoor running mean temperature and the air speed (Figure 14). For the ASHRAE adaptive comfort model one will need to know the operative temperature and the prevailing mean outdoor temperature (Figure 15). Figure 13: CBE Thermal Comfort Tool - EN 15251 PMV method [38] LITERATURE REVIEW 25 Figure 14: CBE Thermal Comfort Tool – EN 15251 adaptive comfort method [38] Figure 15: CBE Thermal Comfort Tool - ASHRAE adaptive comfort method [38] LITERATURE REVIEW 26 Ways to avoid overheating in a building Mediterranean regions can lead to uncomfortable conditions, especially during spring and summer time, if suitable measures are not taken to improve comfort. This condition is known “as ‘overheating’, i.e. the indoor environment would become hotter than is desirable, comfortable or sometimes even tolerable” [39]. Generally, occupants want to satisfy their thermal comfort in the building establishing the optimum conditions without using any mechanical device or active energy systems. Discomfort can be understood in two ways: • Discomfort due to high thermal conditions – Overheating. • Discomfort due to air freshness – Ventilation systems. Reducing the occupants’ discomfort can be done by designing or retrofitting energy efficient buildings. The main sources of heat come from internal gains but more importantly from solar gains through the building’s fabric envelope and glazing, which increases the indoor temperature. Nevertheless, dwelling characteristics are also important. Location, orientation, ventilation, design and construction are five different factors considered when analysing thermal comfort, placing the sensors and deciding what solutions can be made to reduce discomfort or better to attain comfort. Preventive measures to existing buildings (Figures 16, 17) rather than the design of new ones [40] are: • Thermal insulation to the walls and loft. • Shading, reflection and protection. • Ventilation o Mechanical systems: fans, air conditioning, etc. o Natural ventilation (opening windows). LITERATURE REVIEW 27 Figure 16: Sources of heat gain [40] Figure 17: Potential measures to minimise heat gains [40] LITERATURE REVIEW 28 Assessing overheating “In order to assess whether an existing building is overheating or uncomfortable, the upper limit of the indoor comfort temperature needs to be known for that day” [39]. It is recognised that noticeable variations of outdoor temperatures can occur in periods of times shorter than a month. The adaptive method suggests that comfort depends on very recent thermal experience, i.e. comfort temperature depends on the daily running mean outdoor temperature (weighted average outdoor temperature over the past few days) in relation to today’s running mean outdoor temperature. According to this, a sudden warm spell is more uncomfortable when there is not a steady build-up of warmer condition. When the running mean outdoor temperature has been low for several days and a sudden warm spell occurs, the odds of feeling uncomfortable are higher (Figure 18) than when the running mean outdoor temperature has been high (Figure 19). Figure 18: Hot spell in April [39] LITERATURE REVIEW 29 Figure 19: Hot spell in July [39] Therefore, we can plot, for an existing building, the indoor comfort temperature versus the running mean outdoor temperature with the upper limit of comfort temperature band, as we can see in Figure 14. When the indoor comfort temperature of the day exceeds the upper limit of comfort temperature band, we could say that the existing building is overheated; hence the temperatures are ‘too hot’ for most people, i.e. uncomfortable. 2.4 Housing authority buildings retrofit measures and case studies Similar local study Yousif et al. [41] analysed the economic viability of the different energy efficient (EE) and renewable energy (RE) installations proposed on the first energy efficient housing project in Malta, base year 2010. The different measures proposed were double-glazing, louvered windows and door, roof insulation, solar water heating, solar photovoltaic systems, shading features and underground second-class rainwater reservoir. An average price for energy efficient options was calculated based on quotations from local suppliers. The study was able to evaluate the carbon footprint, the Net Present Value (NPV) and the Discounted Payback Period (DPP). Three energy efficiency measures LITERATURE REVIEW 30 stood out from the others; the solar water heating resulted to have the best NPV (42,920 €) and a payback period of 4 years; the second best NPV rated (33,593 €) was the roof insulation with a payback period of 2 years and the third best NPV rated (19,637 €) was the double glazing with a payback period of 3 years. It is important to mention that a photovoltaic system (PV) had the fourth best NPV but the payback (PB) period is 20 years in 2010. Naturally, for this last measure, the prices of solar photovoltaics have dropped significantly, and this implies that installing solar photovoltaics could have a very attractive rate of return in 2019/2020, when compared to 10 years ago. There were also different measures with a negative NPV after 20 years, such as louvred windows, due to the high cost of the louvred window itself. In this study, the energy saving of the new building block was estimated, given that no energy consumption data existed. Nevertheless, given that the electricity tariffs today are much cheaper than those in 2010 (by a factor of 1.5), it is imperative that the payback periods for all energy efficiency measures could be different from those in 2010. Housing retrofit studies in Mediterranean climate Lizana et al. [42] performed a multi-criteria assessment to derive on an energy Effectiveness Index (EI) for each measure or package of measures that considers the environmental, economic and social variables for all the stakeholders, which include the user, the public promotor and the private promotor. Therefore, this assessment considers more criteria for decision making than the EPBD cost-optimal method, which is only concerned with primary energy savings and life-cycle costings. The different measures were applied on a southern Spanish building from the 1950s. It was found that heat pumps have the potential of reducing up to 45% of the building’s CO2 emissions with a payback period of 6 years. Most passive retrofit measures, including shading elements and installation of high efficiency windows, were found to have a resulting high payback period of 15 years or more .The paper also provides a detailed literature review of the different assessment measures adopted by other studies, to identify the effectiveness of the other energy efficiency retrofit measures. Suárez et al. [43], performed an energy assessment using DesignBuilder [44], whose simulation engine is Energy Plus [45]. The different retrofit measures analysed were natural ventilation at night during the summer period, energy conservation measures LITERATURE REVIEW 31 improving insulation on external framework and double glazing, solar radiation and solar control using sliding, folding and fixed slat systems, movable shading devices and thermal envelope insulation with ceramic or metal finish. Not only energy consumption and savings were analysed, but thermal comfort was also taken into account using the adaptive models defined by Auliciems and Szokolay [46]. Thermal comfort was improved by reducing the gap between the indoor temperature and the comfort temperature band, mainly through the improvement in U-values of each building envelope element. Santamaría et al. [47], performed an energy and economic assessment of dwellings in Mediterranean climates also using Design Builder. The different retrofit measures studied included a façade restored by inner cladding, internal roof and ground insulation, double-glazed windows and insulated aluminium frames and an efficient use of terraces as solar collectors. As in Yousif et al. [41], NPV is also analysed for each measure. Finally, the best comparative results were found to be an insulation system on the external envelope with a payback period of 19 years and an insulation system for the internal side of the building with a payback period of 15 years. These settings get the highest energy and economic savings and when giving a more detailed analysis, the inner insulation is more profitable than those on the external side of the envelope due to the lower cost that this entails. This study also highlights that installation of solar protection in that specific building is not profitable due to the lower percentage of façades with south and west components. Escandón et al. [48], also featured an energy assessment of three different case studies in South Spain using DesignBuilder. Escandón distinguished between real and estimated consumption in the housing stock and behaviour. Thus, monitoring the case studies with long-term measurements was the method used to evaluate energy efficiency and thermal behaviour of the building and its comfort levels following the adaptive model established by standard EN 15251. Specific retrofit measures are not mentioned, although general insulation is named. This study highlights the importance of different user profiles and location for retrofitting decisions and how important the financial constraints are for users when using their heating systems. Therefore, improving thermal comfort must be done with efficient heating systems that do not affect users economically and with passive retrofit measures as much as possible. LITERATURE REVIEW 32 Desogus et al. [49], studied the feasibility of heavy thermal upgrades on different buildings in the Mediterranean climate, proving that different energy efficiency retrofit measures are not completely cost-effective as far as payback time is concerned, unless national subsidy policies are implemented to improve the economic return on the investment. For this, Desogus et al. propounded two different scenarios and assessed the different NPV obtained with and without national subsidy policies. Blázquez et al. [50], focused their study on how important calibration is on simulations of building energy models, to allow a better approach to the current environmental conditions and to predict and optimise the different energy retrofit measures to implement. In order to implement the information recorded in situ, software such as DesignBuilder allows the energy model to be supplemented with a complete description of the internal loads and user’s profile. For this, reducing the number of uncertain parameters improves the precision of the calibration. More information is developed in Section 2.6. More local studies Manz et al. [35], performed an energy simulation with the computer program WUFI®Plus. The study analysed the thermal comfort of different passive energy retrofit measures in the Maltese archipelago following the adaptive thermal comfort model from the European standard EN 15251. The U-value of different building elements was considered. The study concluded that in an energy efficient well-designed building, that is equipped with double glazing, decent insulation, different shading devices and natural night ventilation, natural night ventilation in summer could be the most effective strategy, although it has its limitations such as the low temperature difference between outdoor temperatures and indoor temperature, as well as the low speed of wind in summer and the level of humidity, which depends on the wind direction. For the case of low wind speed, the paper proposes to assist natural ventilation by adding mechanical ventilation Damien Gatt and Charles Yousif [51] studied a new boutique hotel building in Malta to reduce its CO2 emissions approaching the NZEB objectives from the EPBD. The modelling was carried out using EnergyPlus modelling in the computer program DesignBuilder. The analysis highlighted that it was possible to reduce more than 75% LITERATURE REVIEW 33 of CO2 emissions with a payback period of approximately 9 years. Most of the CO2 savings were achieved from the main energy consumer, Domestic Hot Water. Therefore, using renewable energies for producing hot water should be considered such as solar heating, heat pumps or ground source heat pumps. The study also noted that using liquified petroleum gas for cooking instead of electricity can already result in a significant reduction in CO2 emissions, despite no reduction in site energy demand. Another study from Gatt and Yousif [52] on a primary school building in Malta was modelled in DesignBuilder in order to meet the Minimum Energy Performance Requirements (MEPRS) defined by the EPBD, using the Net Present Value point of view. Achieving comfort using the EN 15251 adaptive thermal comfort was also considered in their conclusions. Different retrofit technologies were carried out; convective heaters were replaced with infra-red radiative panel heaters, photovoltaic solar modules were installed, the swimming pool’s energy was reduced with an automated pool cover and air to water heat pumps coupled with a solar thermal heating system, while electrical storage water heaters were replaced by instant water heaters in the bathrooms. Other measures such as wall insulation and light dimming using photocells were installed although they had lower economic impact, as reflected in their NPV results but these were applied to compare their actual performance with the Energy Plus simulation results. 2.5 Housing authority and ERDF priority axis 4 Malta’s Priority Axis 4 section 4c, which sources its funding from the European Regional Development Fund (ERDF) and Cohesion Fund, promotes the use of renewable energy sources and energy efficient systems through financial incentives in the housing sector. “Moving towards resource-efficiency, low-carbon economy and sustainable growth is one of the central objectives of the Europe 2020 Strategy and remains one of Malta’s top priorities for the 2014-2020 period” [53]. To meet the objectives, it is important to invest in more environmentally friendly measures and exploit natural resources in a sustainable way. Malta is carrying out different national strategies such as the National Renewable Energy Action Plan and the National Energy Efficiency Action Plan. Malta has also published the draft National Energy and Climate Plan for 2030, which proposes the way forward with regards to Malta’s commitments towards climate change and renewable energy [54]. Households, enterprises and the METHODOLOGY 40 Building fabric (U-Values) The building has the following envelope properties (table 8). The U-values were calculated using the standard methodology of ISO 6946:2017 [60] Table 8: Building envelope properties and materials Original building envelope U-Value (W/m2K) External Wall (façade), made up of double limestone block with an air gap 1.58 External Wall (interior courtyard), made up of single limestone block 2.8 Interior Walls, made up of single limestone 2.1 Glazing, single clear glazing with aluminium frame (6mm) 5.78 Roof (uninsulated) 2.0 Floor (uninsulated) 1.57 3.2 Data Collection Questionnaires In order to know the occupants and their actual electricity consumption and comfort, information was collected from a total of 31 dwellings (out of 40 dwellings). Nine dwellings could not be reached to conduct the questionnaires. Data validation and analysis was performed to identify which variables showed the biggest impact on the energy performance of the building. Twelve variables (floor level, orientation, number of occupants, number of heat pumps, type of heater, water heater continuously being used, age of the fridge-freeze, age of the freezer, type of oven, number of electric equipment in the kitchen, age of the washing machine and other plug loads) were determined, to analyse energy performance in terms of equipment and building operation. It must be noted that only 26 dwellings had valid electricity and water bills (based on actual figures) data for research purposes (out of the 31 dwellings visited). METHODOLOGY 41 Electricity and water bills The data collected from the electricity and water bills were inputted on a spreadsheet for analysis. The collection of raw data is shown in Appendix 1. Installation of Sensors A total of 15 HOBO MX Temp/RH Data Loggers (MX1101) [61] (Figure 24),were used to gather relative humidity and temperature every 10 minutes. These sensors were primarily located in the bedrooms of the dwellings under study. Figure 24: HOBO MX Temp/RH Data Logger (MX1101) Due to the limitation of time, only one month of data was used to calibrate the software DesignBuilder simulation software based on hourly temperature readings (see Section 2.6). However, this was enough to attain an acceptable level of confidence in the modelling results. Statistical analysis and identification of the baseline energy consumption The annual energy consumption can be divided into three main sources of significant energy consumption: heating and cooling energy consumption, domestic hot water (DHW) energy consumption and others (lighting, plug loads, appliances). The annual energy consumption was calculated by adding the energy consumption of each dwelling for one year. For missing data, an average energy consumption per occupant was calculated. The DHW energy consumption is calculated in the same way as the annual energy consumption, with a 20 litres/day per occupant [62]. For the heating METHODOLOGY 42 and cooling energy consumption, questionnaire data is used to quantify the number of dwellings using air-conditioners and therefore estimate their energy consumption. The “others” (lighting, plug loads and appliance) energy consumption were automatically derived by subtracting the space heating, cooling and DHW energy consumption from the total consumption. The annual DHW energy consumption (EC) was calculated following the equation: 𝐷𝐻𝑊⁡𝐸𝐶=𝑁º𝑂𝑐𝑐𝑢𝑝𝑎𝑛𝑡𝑠·𝐷𝐻𝑊⁡𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑⁡𝑝𝑒𝑟⁡𝑜𝑐𝑐𝑢𝑝𝑎𝑛𝑡·(𝑇𝑓−𝑇𝑖)·𝑁º⁡𝑑𝑎𝑦𝑠·∁·𝛼 𝐷𝐻𝑊⁡𝑠𝑦𝑠𝑡𝑒𝑚⁡𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 (21) 𝑇𝑓=𝐴𝑣𝑒𝑟𝑎𝑔𝑒⁡𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒⁡𝑎𝑓𝑡𝑒𝑟⁡ℎ𝑒𝑎𝑡𝑖𝑛𝑔⁡≈60°𝐶 𝑇𝑖=𝐴𝑣𝑒𝑟𝑎𝑔𝑒⁡𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒⁡𝑏𝑒𝑓𝑜𝑟𝑒⁡ℎ𝑒𝑎𝑡𝑖𝑛𝑔⁡≈20°𝐶 ∁⁡=𝑊𝑎𝑡𝑒𝑟⁡ℎ𝑒𝑎𝑡⁡𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦⁡(𝐽𝑜𝑢𝑙𝑒𝑠/𝑘𝑔) 𝛼=𝑐𝑜𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛⁡𝑓𝑎𝑐𝑡𝑜𝑟⁡𝑓𝑟𝑜𝑚⁡𝐽𝑜𝑢𝑙𝑒𝑠⁡𝑡𝑜⁡𝑘𝑊ℎ=2,77778·10−7⁡ 3.3 Building Energy modelling of base (actual building) scenario Use of software and why it was chosen The software used for the simulation was DesignBuilder version 6.1.0.006. DesignBuilder is a dynamic software [55] that facilitates graphical inputs into the interface energy simulation engine of EnergyPlus. EnergyPlus is a simulation program based on Building Loads Analysis and Systems Thermodynamics. This program allows a whole building energy simulation used to model energy consumption for heating, cooling, ventilation, lightning and plug and process loads. It enables simultaneous interaction of the geometric model of the building with the outdoor conditions, occupancy and usage of building systems in order to predict heating and cooling loads arising in the building on an hourly basis. Therefore, being able to evaluate the energy performance on an hourly basis makes this program the ideal tool for the objectives of this dissertation. This is complimented by the fact that the engine also considers the METHODOLOGY 43 thermophysical properties of materials, occupancy, subjective data and the performance of systems influenced by the internal and external environmental conditions. Use of questionnaires to understand typical equipment inside building Questionnaires were used to understand which variables tend to be similar or different between dwellings. Twelve variables were determined to analyse energy performance in terms of equipment and building operation. Questionnaires were also used to see how comfortable the occupants were during summer and winter periods. Questionnaires led to the conclusion that approximately half of the dwellings have an air conditioner (A/C) that could only improve comfort in the room where it is located. Questionnaire analysis In order to assess the questionnaires and see what variables are the most significant, a Multiple Linear Regression (MLR) with the annual consumption as dependent variable was analysed in the program STATGRAPHICS Centurion 18 (Version 18.1.06, 64-bits). The Homogeneity of Variance Hypothesis, the Normality Hypothesis and the Independence Hypothesis were tested. Floor choice level for analysis The comfort feedback from the questionnaires was analysed to determine which floor (top, middle, or ground/bottom) has the highest discomfort among the occupants and which requires to be prioritised for this study. Top floor resulted to have a 100% of discomfort among the occupants. Thus, this floor was given priority and analysed for this study. Hourly calibration of simulated temperatures with actual logged data From the data loggers, relative humidity and dry-bulb room temperature were gathered for a period of at least 1 month. Ideally data would have been gathered for at least one year. However, this was one of the main limitations of this study, given that the project was initiated in March 2019, and therefore only one month of actual measured comfort METHODOLOGY 44 data was available for the study. According to Section 2.6, to gain confidence of the suitability in the analysis method proposed when undertaking an energy retrofit project, the building energy model should be calibrated with actual measured data. The measured temperature data was compared to hourly simulated data. Calibration was validated on an hourly resolution using NMBE and CV(RMSE) criteria explained in the ASHRAE Handbook [59]. According to ASHRAE when undertaking hourly calibration if the resulting NMBE < 10% and CV(RMSE) < 30%, the model can be considered calibrated. For calibration, the actual outdoor weather data for the period analyzed was considered. Comfort analysis and comfort analysis approaches The comfort assessment is divided in two general scenarios, according to the seasons simulated. The assessment was carried out for the most extreme typical week of winter and summer, called design week 2 . These weeks were automatically determined by EnergyPlus for a typical meteorological year for Malta. It is assumed, that if comfort is satisfied during these weeks, the building will also be comfortable throughout the whole year. As reviewed in the literature, the adaptive comfort versus the PMV/PPD comfort model was used for analysis, as the aim of this study was achieving thermal comfort using no mechanical means for heating, cooling or ventilation. In order to assess thermal comfort with the considered adaptive model standards (EN 15251, ASHRAE and M. Vellei et al. [36] model) simulations were carried out using no mechanical means for heating, cooling or ventilation both for the summer and winter design weeks. In the Summer period, occupants tend to open windows in order to improve their comfort. When running the building simulation for Summer design week, two approaches were considered, to identify the sensitivity of opening windows in summer. For the first approach, the “Summer design week with Windows Closed” considered that all windows remain closed independent of the temperatures outside and inside the dwelling. In the second approach, the “Summer design week with Windows Open”, 2 Simulated summer design week: 13/07/2002 - 20/07/2002. Simulated winter design week: 20/01/2002 - 27/02/2002. METHODOLOGY 45 windows were opened when the temperature outside is lower than the temperature inside the dwelling´s room and the operation schedule of the room allows it. For winter, only the approach with windows closed was considered given that occupants ensure that heat losses to the outside air is minimised. Comfort assessment of the base (as is) building The building has been modelled in DesignBuilder (Figure 25). Figure 25: Building model on DesignBuilder As mentioned, in Section 3.3.4, the simulation analysis is done for the top floor (Figure 26). In order to perform a quicker and more specific analysis and thanks to the fact that the building is symmetrical, one dwelling per cardinal orientation was simulated for the top floor. Thus, the comfort study considered each orientation for the top floor. METHODOLOGY 46 Figure 26: Simplified top floor model on DesignBuilder and top floor plan showing dwellings’ configuration All dwellings have 3 bedrooms, 2 bathrooms, 1 dining room, 1 kitchen and 1 indoor corridor as seen in Figure 27. Figure 27: Dwellings and zones for each orientation For the simulations carried out, different aspects have been considered: the occupancy schedule per room is based on the default setting by DesignBuilder that utilises the UK national calculation methodology (NCM). For the summer period, for the simulations with windows opened, the windows were scheduled to open 50 % of the glazing area when the temperature inside the room is METHODOLOGY 47 higher than the outside and when the room is occupied. The building does not make use of mechanical ventilation for air changes. The dwelling floor is considered adiabatic, to improve simulation computation time. This assumption was validated given that the floor is internal and therefore the heat gains and heat losses from the apartments below operating with the same schedule can be neglected. When collecting the simulated data, all rooms were analysed except for the indoor corridor, as displayed in Figure 27. The rooms analysed are Bedroom 1A, Bedroom 1B, Bedroom 1C, Bathroom 1A, Bathroom 1B, Kitchen and Dining. Hourly data is collected for each design week. The data collected is the zone operative temperature, the zone air relative humidity, the zone thermal comfort ASHRAE 55 adaptive model, running average outdoor air temperature and the zone thermal comfort EN 15251 adaptive model temperature. This data was plotted to analyse comfort for both the EN 15251 and ASHRAE adaptive comfort models. All EN 15251 categories were considered while ASHRAE 80% acceptability model was used. Another model, M. Vellei et al. [36], that also considers the impact of relative humidity on ASHRAE adaptive comfort was also used, given the high relative humidity levels found in Malta. Once the comfort analysis was done, potential retrofit measures were considered to improve comfort. 3.4 Identification of retrofit measures Identification of potential retrofit measures In order to improve comfort and reduce energy consumption, different retrofit measures were considered for analysis. In order to identify potential measures, previous energy retrofit studies of Maltese buildings were first consulted. Furthermore, EnergyPlus was used to show and quantify the main sources of heat loss and heat gain on a monthly METHODOLOGY 48 resolution for each part the building envelope (roof, glazing, walls) allowing one to identify potential measures to be prioritised (see Table 9). Table 9: Retrofit measures considered and their properties Retrofit measure number Details 1 Addition of 5 cm of Expanded Polystyrene Standard (EPS) (Figure 28) to improve U-Value of the external wall façade from U=1.57 W/m2K to U=0.57 W/m2K 2 Addition of 5 cm of Expanded Polystyrene Standard (EPS) to improve U-Value of the external wall from the interior courtyard from U=2.81 W/m2K to U=0.62 W/m2K 3 (Figures 29,30) Blinds as specified in Table 10 4 Double glazing (6mm/6mm) use instead of single glazing (6mm) with aluminium frame to improve U-Value from U=5.58 W/m2K to U=3.1 W/m2K 5 Addition of 8 cm of Expanded Polystyrene Standard (EPS) to improve roof U-Value from U=2 W/m2K to U=0.41 W/m2K METHODOLOGY 49 Figure 28: EPS Insulation proposed Table 10: Blind/slat properties Blind-to-glass distance (m) 0.05 Slat orientation Horizontal Slat width (m) 0.025 Slat separation (m) 0.01875 Slat thickness (m) 0.001 Slat conductivity (W/m·K) 0.9 Slat angle (°) 45 Minimum slat angle (°) 0 Maximum slat angle (°) 180 RESULTS 56 Figure 31: Annual Breakdown of energy consumption (kWh) 4.3 Questionnaires statistical analysis and calibration Questionnaires statistical analysis An MLR analysis was used to assess the questionnaires answers using the annual consumption per dwelling as the dependent variable. The Homogeneity of Variance Hypothesis, the Normality Hypothesis and the Independence Hypothesis were tested and met. Three variables out of twelve proved to have a significant impact on energy consumption (p<0.05), namely the number of air-to-air reversible heat pumps (Nº HP), if the water heater is continuously switched on (WH Cont. ON) and the number of plug loads and appliances being used (Nº PL), as seen in Table 12.. The backward MLR equation obtained for annual electric consumption per dwelling (AECD) is: 𝐴𝐸𝐶𝐷=1501.76+610.284·𝑁º⁡𝐻𝑃+1126.34·𝑊𝐻⁡𝐶𝑜𝑛𝑡.𝑂𝑁+431.665·⁡𝑁º⁡𝑃𝐿 (24) 26% 39% 35% ANNUAL BREAKDOWN OF ENERGY CONSUMPTION (KWH) Space heating and cooling consumption DHW Others RESULTS 57 The derived MLR equation was able to explain 54% of the variability in annual electric energy consumption (R-squared = 54%). This means that there are also other latent variables that influence the annual consumption per dwelling, but these could not be determined due to the limitation of the questionnaires (e.g. tenants’ financial situation, time of use of the dwelling). Even though some dwellings just have one, two, three or no air to air heat pumps (air-conditioners), these significantly impact the annual energy consumption. Table 12: MLR Significant variables out of 26 observations Parameter Estimate Standard Error T Statistic P-Value CONSTANT 1501.76 536.698 2.79814 0.0105 Nº of Heat Pumps 610.284 272.392 2.24046 0.0355 WH Continuously ON 1126.34 479.744 2.34779 0.0283 Nº of Other Plug Loads 431.665 137.029 3.15018 0.0046 From the questionnaires, it can be seen (Table 13) that the occupants of the Top floor have 100% of discomfort during both summer and winter period. Table 13: Discomfort - Comfort answers percentages per floor level Winter Summer Bottom Floor Discomfort 60% 40% Comfort 40% 60% Middle Floor Discomfort 26% 32% Comfort 74% 68% Top Floor Discomfort 100% 100% Comfort 0% 0% Therefore, the top floor was chosen to be the specific case study for this dissertation. Furthermore, from the actual temperature data logger metering it was shown that the top floor had a more variable temperature, which follows the variations with the external air temperatures, as shown in Figure 32. RESULTS 58 Figure 32: Maximum temperature achieved with the data loggers per floor level The main aim of the dissertation is to identify the best retrofit measures for a typical housing block in Malta to improve the energy performance of such buildings while improving the thermal comfort of the occupants. The focus of this study was carried out for the top floor level of the building given that it was identified via feedback from occupants’ questionnaires that the highest level of discomfort is on this floor. Furthermore, sub-hourly temperature monitoring in the housing block confirmed that the indoor temperature in this level has the most variability when compared to the other floors, according to changes in outside temperatures. The MLR analysis that was used to assess the questionnaires, highlighted that the air-to-air reversible heat pumps, the number of plug loads being used and the management of the electric water heater are the variables having the biggest impact on electrical energy consumption. Thus, more education is required to inform occupants to switch on the electric water heaters only prior to being used. Furthermore, these findings suggest that reducing or eliminating the use of air-to-air heat pumps via passive solutions to improve thermal comfort can play an important role to improve the energy performance of such building stocks. 16 16,5 17 17,5 18 18,5 19 19,5 20 20,5 21 21,5 22 22,5 23 23,5 24 Temperature °C Maximum Temperature achieved per floor level MAX TEMP Bottom MAX TEMP Middle MAX TEMP Top RESULTS 59 Hourly temperature Calibration Calibration between simulated inside temperatures and actual metered temperature was validated on an hourly resolution using NMBE and CV(RMSE) criteria explained in ASHRAE Handbook [59]. According to ASHRAE when undertaking hourly calibration, if the resulting NMBE < 10% and CV(RMSE) < 30%, then the model can be considered calibrated. For calibration, the actual outdoor weather data for the period analyzed was considered for the simulations. Table 14: Temperature statistical calibration indicators for the bedroom in which the data logger was installed (Bedroom 1B) NMBE 7.79% CV(RMSE) 6.25% Table 15: Humidity statistical calibration indicators for Bedroom 1B NMBE 7.19% CV(RMSE) 3.36% As NMBE < 10% and CV(RMSE) < 30% the model was considered calibrated for hourly data. 4.4 Comfort plots for the current building envelope with no mechanical heating and cooling The comfort assessment is divided in two general scenarios, according to the seasons simulated. The assessment was carried out for the most extreme week of winter and summer, known ss the design week. These weeks were automatically determined by EnergyPlus for the weather file for Malta. It is assumed, that if comfort is satisfied during these weeks, the building will also be comfortable throughout the whole year. The coding used to analyse the base building can be seen in Table 13. Table 16: Base Comfort analysis codification Nomenclature Abbreviation Summer design week with Windows Closed S + WC Summer design week with Windows Open S + WO Winter design week W RESULTS 60 In order to assess thermal comfort with the considered adaptive model standards (EN 15251, ASHRAE and M. Vellei et al. [36] model) simulations were carried out using no mechanical means for heating, cooling or ventilation both for the summer and winter design weeks. The rooms analysed are Bedroom 1A, Bedroom 1B, Bedroom 1C, Bathroom 1A, Bathroom 1B, Kitchen and Dining. Simulated hourly data were collected for each design week and plotted for the three adaptive comfort models used in these studies: • ASHRAE adaptive comfort model with an 80% of acceptability range. • M. Vellei et al. [36] model. • EN 15251 adaptive comfort model Category I, II and III. and plotted as seen in Appendix 2 One can see that the amount of discomfort hours drops when windows are opened. Therefore, all subsequent analysis for summer period was considered for “windows open” status (see Figures 33, 34, 35). Figure 33: Discomfort hours percentages for ASHRAE adaptive comfort model in Summer per orientation for the base scenario S + WC S + WO North 100% 95% East 100% 96% South 100% 96% West 100% 97% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Summer Design Week ASHRAE Adaptive Comfort Model RESULTS 61 Figure 34: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Summer per orientation Figure 35: Discomfort hours percentages for EN 15251 adaptive comfort model in Summer per orientation The plotted comfort results, per orientation and room, for summer and winter design weeks, can be seen in the Appendix 2 Section A2.2; these plotted comfort results follow the same trend. Thus, Bedroom 1B was chosen to represent the rest of the rooms in this Section. In Figure 36, for Bedroom 1B facing North orientation, the plotted ASHRAE adaptive comfort model results are compared with the M. Vellei et al. [36] adaptive comfort model results for the summer design week. S + WC S + WO North 93% 73% East 96% 76% South 93% 72% West 96% 77% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Summer Design Week RH influence in ASHRAE Adaptive Comfort Model S + WC S + WO North 97% 79% East 99% 82% South 97% 79% West 98% 83% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Summer Design Week EN 15251 Adaptive Comfort Model RESULTS 62 In addition, in Figure 37, the results for the EN 15251 adaptive comfort model are also plotted for the same bedroom for the summer design week. For the same room, Figure 38 summarises the number of discomfort hours resulting from the different comfort models under analysis for the summer design week. Figure 36: Summer design week ASHRAE and M. Vellei et al. [36] comfort analysis for Bedroom 1B using different windows opening configurations facing North orientation 20 22 24 26 28 30 32 34 36 38 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinOpen The Operative Temperature UPPER LIMIT (relative humidity involved) WinOpen The Operative Temperature LOWER LIMIT (relative humidity involved) WinOpen [1] Zone Operative Temperature © WinClosed The Operative Temperature UPPER LIMIT (relative humidity involved) WinCLosed The Operative Temperature LOWER LIMIT (relative humidity involved) WinClosed The Operative Temperature UPPER LIMIT (80% ASHRAE 55) Summer The Operative Temperature LOWER LIMIT (80% ASHRAE 55) Summer RESULTS 63 The RH is influenced by the windows opening configuration, this is, RH will change if windows are open or closed. Figure 37: Summer design week EN 15251 comfort analysis for Bedroom 1B using different windows opening configurations facing North orientation 20 22 24 26 28 30 32 34 36 38 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinOpen [1] Zone Operative Temperature © WinClosed The Operative Temperature UPPER LIMIT (CAT l) The Operative Temperature UPPER LIMIT (CAT ll) The Operative Temperature UPPER LIMIT (CAT lll) The Operative Temperature LOWER LIMIT (CAT l) The Operative Temperature LOWER LIMIT (CAT ll) The Operative Temperature LOWER LIMIT (CAT lll) RESULTS 64 Figure 38: Summer design week number of discomfort hours for Bedroom 1B using different windows opening configurations and adaptive comfort models facing North orientation From Figures 33, 34, 35 it was observed for each orientation on the top floor, that natural ventilation via the opening of windows showed an improvement in comfort via a reduction of indoor temperature by up to 2 °C during the summer design week. Relative humidity also falls when fresh air enters the building, thus allowing a further improvement in thermal comfort during the summer months. Thus, natural ventilation in summer could prove to be an effective measure to improve occupants’ thermal comfort, even if the windows are only opened during the occupancy schedule. However, with the building envelope as is, natural ventilation alone (irrespective of building orientation) is insufficient to allow the building to achieve thermal comfort that complies with EN 15251 Category II or ASHRAE 80% thermal acceptability criteria. Therefore, other passive measures are required to be added to improve thermal comfort during a summer design week. 168 160 168 159 125 132 80% ASHRAE 55 RH EN 15251 CAT ll Bedroom 1B Closed Open RESULTS 65 Figure 39: Discomfort hours percentages for ASHRAE adaptive comfort model in Winter per orientation Figure 40: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Winter per orientation W North 100% East 100% South 100% West 100% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week ASHRAE Adaptive Comfort Model W North 99% East 99% South 99% West 100% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week RH influence in ASHRAE Adaptive Comfort Model RESULTS 72 More plotted comfort results, per orientation and room, can be seen in the Appendix 2 Section A2.2; these plotted comfort results follow the same trend, thus, Bedroom 1B was chosen to represent the rest of the rooms in this Section. In Figure 48, for Bedroom 1B facing North orientation, the plotted ASHRAE adaptive comfort model comfort results are compared with the M. Vellei et al. [36] adaptive comfort model results for the winter design week when all retrofit measures are implemented. In addition, in Figure 49, the results for the EN 15251 adaptive comfort model are also plotted for the same bedroom for the summer design week. For the same room, Figure 50 summarises the number of discomfort hours resulting from the different comfort models under analysis for the summer design week. RESULTS 73 Figure 48: Summer design week ASHRAE and M. Vellei et al. [36] comfort analysis for Bedroom 1B when all measures are implemented facing North orientation 21 23 25 27 29 31 33 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinOpen The Operative Temperature UPPER LIMIT (relative humidity involved) WinOpen The Operative Temperature LOWER LIMIT (relative humidity involved) WinOpen The Operative Temperature UPPER LIMIT (80% ASHRAE 55) Summer The Operative Temperature LOWER LIMIT (80% ASHRAE 55) Summer RESULTS 74 Figure 49: Summer design week EN 15251 comfort analysis for Bedroom 1B when all measures are implemented facing North orientation Figure 50: Summer design week number of discomfort hours for Bedroom 1B when all measures are implemented facing North orientation 21 23 25 27 29 31 33 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinOpen + RM The Operative Temperature UPPER LIMIT (CAT l) The Operative Temperature UPPER LIMIT (CAT ll) The Operative Temperature UPPER LIMIT (CAT lll) The Operative Temperature LOWER LIMIT (CAT l) The Operative Temperature LOWER LIMIT (CAT ll) The Operative Temperature LOWER LIMIT (CAT lll) 44 27 0 Bedroom 1B Overheating ASHRAE WinOpen Overheating RH WinOpen Overheated compared to CAT ll WinClosed RESULTS 75 For winter design week, the number of discomfort hours were reduced once the potential retrofit measures were implemented (Figures 51, 52, 53). One can see the percentage of discomfort hours is slightly high for the EN 15251 Adaptive Comfort model (Figure 53). This is because the Category II comfort limits were used to derive the discomfort hours. If Category III comfort criteria (suitable for an existing building) are considered, one can see in Appendix 2 Section A2.2.3 and in Figure 110, that the number of discomfort hours plotted are reduced. Thus, the building can be seen to comply with Category III adaptive comfort limits. EN 15251 Category III comfort level should be enough for the building under study. Figure 51: Discomfort hours percentages for ASHRAE adaptive comfort model in Winter with measures per orientation Figure 52: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Winter with measures per orientation W W + RM North 100% 07% East 100% 05% South 100% 00% West 100% 02% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week ASHRAE Adaptive Comfort Model W W + RM North 99% 00% East 99% 00% South 99% 00% West 100% 00% 00% 20% 40% 60% 80% 100% % DIscomfort Hours Percentage Discomfort Hours Winter Design Week RH influence in ASHRAE Adaptive Comfort Model RESULTS 76 Figure 53: Discomfort hours percentage for EN 15251 adaptive comfort model in Winter with measures per orientation In Figure 54, for Bedroom 1B facing North orientation, the plotted ASHRAE adaptive comfort model comfort results are compared with the M. Vellei et al. [36] adaptive comfort model results for the winter design week when all measures are implemented. In addition, in Figure 55, the results for the EN 15251 adaptive comfort model are also plotted for the same bedroom for the winter design week. For the same room, Figure 56 summarises the number of discomfort hours resulting from the different comfort models under analysis for the winter design week. W W + RM North 100% 47% East 100% 38% South 100% 24% West 100% 26% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week EN 15251 Adaptive Comfort Model RESULTS 77 Figure 54: Winter design week ASHRAE and M. Vellei et al. [36] comfort analysis for Bedroom 1B when all measures are implemented facing North orientation 16 18 20 22 24 26 28 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinClosed The Operative Temperature UPPER LIMIT (relative humidity involved) WinCLosed The Operative Temperature LOWER LIMIT (relative humidity involved) WinClosed The Operative Temperature UPPER LIMIT (80% ASHRAE 55) WinCLosed The Operative Temperature LOWER LIMIT (80% ASHRAE 55) WinClosed RESULTS 78 Figure 55: Winter design week EN 15251 comfort analysis for Bedroom 1B when all measures are implemented facing North orientation Figure 56: Winter design week number of discomfort hours for Bedroom 1B when all measures are implemented facing North orientation 18 19 20 21 22 23 24 25 26 27 28 Temperature °C Bedroom 1B [1] Zone Operative Temperature © WinClosed The Operative Temperature UPPER LIMIT (CAT l) The Operative Temperature UPPER LIMIT (CAT ll) The Operative Temperature UPPER LIMIT (CAT lll) The Operative Temperature LOWER LIMIT (CAT l) The Operative Temperature LOWER LIMIT (CAT ll) The Operative Temperature LOWER LIMIT (CAT lll) 4037 Bedroom 1B Uncomfort ASHRAE WinClosed Uncomfort RH WinClosed Uncomfort compared to CAT ll WinClosed RESULTS 79 Discussion for the scenario with all passive retrofit measures implemented For the summer design week, with all the above measures implemented, thermal comfort was achieved for the EN 15251 Category II adaptive comfort model for all orientations and zones. In contrast, for the standard ASHRAE 80% thermal acceptability adaptive comfort model, while the discomfort hours were reduced when compared to the base scenario, some hourly indoor temperatures exceeded the upper comfort limit, especially for the kitchen that has high heat gains. The M. Vellei et al. [36] model provides a balance between the comfort performance of the EN 15251 Category II and the standard ASHRAE 80% thermal acceptability adaptive comfort models. Thus, the standard ASHRAE 80% thermal acceptability is the most difficult model to comply to for Summer, while the EN 15251 Category II model is the least strict model. In contrast, for the winter design week, when all the passive retrofit measures were introduced, comfort was only achieved for the ASHRAE 80% thermal acceptability adaptive comfort model and the M. Vellei et al. [36] model, but not for the EN 15251 Category II model. Thus, for summer comfort, the EN 15251 Category II is the most difficult model to comply to for winter thermal comfort. In addition, unlike the summer design week, the kitchen was the zone with lowest number of discomfort hours due to the high internal heat gains in winter. One can also see that the North and East orientations show the highest number of discomfort hours, when compared to the dwellings facing the South and West orientations due to higher solar radiation penetrating the glazing at lower solar elevations. This contrasts with the summer design week, where similar peak temperatures result in dwellings having different orientations. Given that no dwelling is perfectly south oriented, the shading offered by the balconies has the same impact on the orientations studied. 4.6 Global sensitivity analysis A global sensitivity analysis was carried out analysing each potential retrofit measure and orientation in order to see which affect the most in the ASHRAE adaptive comfort model and in the EN 15251 adaptive comfort model on a summer and winter design week. This was carried out to identify whether all considered potential measures require to be implemented to satisfy the required comfort levels. RESULTS 80 An MLR was carried out for both seasons. This allowed one to identify the variables with most significant impact on comfort. For summer, doing a Backward Stepwise selection (this is, step by step elimination of the non-significant parameters) ranked the parameters in terms of impact on the EN 15251 adaptive comfort hours as follows (starting from the parameter having most impact): roof insulation, external blinds, external wall insulation (interior courtyard) and the orientation of the building. The resulting variables with no significant impact are the external wall façade insulation and the glazing type as seen in Table 18. Table 18: Standardized Coefficients Beta for the Summer design week for the EN 15251 Category II discomfort hours Backward Stepwise Selection Step 0 Standardized Coefficient Beta External Wall Insulation (façade) -0.034 External Wall Insulation (courtyard) -0.139 Roof Insulation -0.655 Double Glazing -0.104 External Blinds -0.203 Orientation -0.123 Step 1 Standardized Coefficient Beta External Wall Insulation (courtyard) -0.138 Roof Insulation -0.654 Double Glazing -0.103 External Blinds -0.203 Orientation -0.125 Step 2 Standardized Coefficient Beta External Wall Insulation (courtyard) -0.138 Roof Insulation -0.655 External Blinds -0.201 Orientation -0.129 RESULTS 81 All parameters are negatively correlated with number of summer discomfort hours. This means that the application of all measures acts favourable in reducing the number of discomfort hours. For the ASHRAE adaptive comfort model, in terms of impact, the most important parameters can be ranked as follows (starting from the one having the largest impact): roof insulation, external blinds, the orientation of the building, the glazing type and the external wall insulation (interior courtyard). The only parameter that resulted statistically not significant is the external wall insulation (façade) as can be seen in Table 19. One is to note that the façade is a double walled faced and no single wall. Table 19: Standardized Coefficients Beta for Summer design week for the ASHRAE 80% acceptability adaptive comfort model Backward Stepwise Selection Step 0 Standardized Coefficient Beta External Wall Insulation (façade) -0.009 External Wall Insulation (courtyard) -0.042 Roof Insulation -0.927 Double Glazing -0.046 External Blinds -0.236 Orientation -0.092 Step 1 Standardized Coefficient Beta External Wall Insulation (courtyard) -0.042 Roof Insulation -0.927 Double Glazing -0.046 External Blinds -0.236 Orientation -0.093 RESULTS 88 Figure 60: Summer design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures 21 23 25 27 29 31 33 Temperature °C Bedroom 1A [1] Zone Operative Temperature © WinOpen + RM (Summer) [1] Zone Operative Temperature © WinOpen + RM - FI (Summer) [1] Zone Operative Temperature © WinOpen + RM - FI - DG (Summer) The Operative Temperature UPPER LIMIT (80% ASHRAE 55) Summer The Operative Temperature LOWER LIMIT (80% ASHRAE 55) Summer The Operative Temperature UPPER LIMIT (RH involved) WinOpen + RM (Summer) The Operative Temperature LOWER LIMIT (RH involved) WinOpen + RM (Summer) The Operative Temperature UPPER LIMIT (RH involved) WinOpen + RM - FI (Summer) The Operative Temperature LOWER LIMIT (RH involved) WinOpen + RM - FI (Summer) The Operative Temperature UPPER LIMIT (RH involved) WinOpen + RM - FI - DG (Summer) The Operative Temperature LOWER LIMIT (RH involved) WinOpen + RM - FI - DG (Summer) RESULTS 89 Figure 61: Summer design week EN 15251 comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures 21 23 25 27 29 31 33 Temperature °C Bedroom 1A [1] Zone Operative Temperature © WinOpen + RM (Summer) [1] Zone Operative Temperature © WinOpen + RM - FI (Summer) [1] Zone Operative Temperature © WinOpen + RM - FI - DG (Summer) The Operative Temperature UPPER LIMIT (CAT l) (Summer) The Operative Temperature UPPER LIMIT (CAT ll) (Summer) The Operative Temperature UPPER LIMIT (CAT lll) (Summer) The Operative Temperature LOWER LIMIT (CAT l) (Summer) The Operative Temperature LOWER LIMIT (CAT ll) (Summer) The Operative Temperature LOWER LIMIT (CAT lll) (Summer) RESULTS 90 Figure 62: Summer design week number of discomfort hours for different combination of measures for the Bedroom 1A facing North orientation The number of discomfort hours are, for winter design week, reduced once the potential retrofit measures were implemented. As the sensitivity analysis showed, all potential retrofit measures are statistically significant for the space heating demand. Therefore, discomfort hours get significantly increased as measure are eliminated. However, for South and West cardinal orientations, discomfort hours do not increase at the same rate as the bedrooms facing the North and East cardinal orientations, due to higher solar radiation gain from these orientations during winter period as seen in Figures 63, 64, 65. Once again, the comfort Category II limits were used for discomfort hours analysis. The building however complies with Category III comfort limits. S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG ASHRAE ASHRAE + RH EN 15251 Bedroom 1A 25 44 47 21 21 22 0 0 0 0 5 10 15 20 25 30 35 40 45 50 Discomfort Hours Bedroom 1A RESULTS 91 Figure 63: Discomfort hours percentages for ASHRAE adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation Figure 64: Discomfort hours percentage for M. Vellei et al. [36] adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation W W + RM W + RM - FI W + RM - FI - DG North 100% 07% 48% 58% East 100% 05% 35% 45% South 100% 00% 05% 05% West 100% 02% 19% 21% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Winter Design Week ASHRAE Adaptive Comfort Model W W + RM W + RM - FI W + RM - FI - DG North 99% 00% 16% 31% East 99% 00% 13% 21% South 99% 00% 00% 00% West 100% 00% 00% 00% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week RH influence in ASHRAE Adaptive Comfort Model RESULTS 92 Figure 65: Discomfort hours percentage for EN 15251 adaptive comfort model in Winter with measures without façade insulation and double glazing per orientation In Figure 66, for Bedroom 1A facing North orientation, the plotted ASHRAE adaptive comfort model comfort results are compared with the M. Vellei et al. [36] adaptive comfort model results for the winter design week when all retrofit measures are implemented, when all retrofit measures are implemented except for the external wall façade insulation and when all retrofit measures are implemented except for the external wall façade insulation and double glazing. In addition, in Figure 67, the results for the EN 15251 adaptive comfort model are also plotted for the same bedroom for the winter design week. For the same room, Figure 68 summarises the number of discomfort hours resulting from the different comfort models under analysis for the winter design week. W W + RM W + RM - FI W + RM - FI - DG North 100% 47% 70% 76% East 100% 38% 76% 81% South 100% 24% 49% 51% West 100% 26% 67% 70% 00% 20% 40% 60% 80% 100% % Discomfort Hours Percentage Discomfort Hours Winter Design Week EN 15251 Adaptive Comfort Model RESULTS 93 Figure 66: Winter design week ASHRAE and M. Vellei et al. [35] comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures 16 18 20 22 24 26 28 Temperature °C Bedroom 1A [1] Zone Operative Temperature © WinClose + RM (Winter) [1] Zone Operative Temperature © WinClose + RM - FI (Winter) [1] Zone Operative Temperature © WinClose + RM - FI - DG (Winter) The Operative Temperature UPPER LIMIT (80% ASHRAE 55) Winter The Operative Temperature LOWER LIMIT (80% ASHRAE 55) Winter The Operative Temperature UPPER LIMIT (RH involved) WinClose + RM (Winter) The Operative Temperature LOWER LIMIT (RH involved) WinClose + RM (Winter) The Operative Temperature UPPER LIMIT (RH involved) WinClose + RM - FI (Winter) The Operative Temperature LOWER LIMIT (RH involved) WinClose + RM - FI (Winter) The Operative Temperature UPPER LIMIT (RH involved) WinClose + RM - FI - DG (Winter) The Operative Temperature LOWER LIMIT (RH involved) WinClose + RM - FI - DG (Winter) RESULTS 94 Figure 67: Winter design week EN 15251 comfort analysis for Bedroom 1A facing North orientation using windows open configuration and using different combination of measures Figure 68: Winter design week number of discomfort hours for different combination of measures for the Bedroom 1A facing North orientation 16 18 20 22 24 26 28 Temperature °C Bedroom 1A [1] Zone Operative Temperature © WinClose + RM (Winter) [1] Zone Operative Temperature © WinClose + RM - FI (Winter) [1] Zone Operative Temperature © WinClose + RM - FI - DG (Winter) The Operative Temperature UPPER LIMIT (CAT l) (Winter) The Operative Temperature UPPER LIMIT (CAT ll) (Winter) The Operative Temperature UPPER LIMIT (CAT lll) (Winter) The Operative Temperature LOWER LIMIT (CAT l) (Winter) The Operative Temperature LOWER LIMIT (CAT ll) (Winter) The Operative Temperature LOWER LIMIT (CAT lll) (Winter) S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG S + WO + RM S + WO + RM - FI S + WO + RM - DI -DG ASHRAE ASHRAE + RH EN 15251 Bedroom 1A 0 138 160 0 21 98 126 168 168 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Bedroom 1A RESULTS 95 4.8 Financial and Macroeconomic analysis results The financial analysis has been carried out by: 1) Comparing the base envelope scenario using air to air heat pumps to achieve comfort versus the scenario with all measures implemented. In this scenario, adaptive thermal comfort has been taken to be achieved when all potential measures are considered and therefore the use of air to air heat pumps is not required. The analysis was carried out for each building orientation. The results are summarised in Table 22. 2) Comparing the base envelope scenario using air to air heat pumps to achieve comfort versus the scenario with all measures implemented also with heat pumps. This analysis was carried out to directly make a comparison between two scenarios attaining the same level of comfort. The analysis was carried out for each building orientation. The results are summarised in Table 23. Table 22: Actual Building with A/C vs Building with All measures per orientation Financial Feasibility Macroeconomic financial analysis Orientation NPV - € IRR SPP (Years) NPV - € North -5.251,83 € -1% 36 -4.609,10 € East -4.857,86 € -1% 34 -4.284,97 € West -5.463,52 € -1% 37 -4.783,25 € South -4.866,68 € -1% 34 -4.292,23 € Actual Building with A/C Building with all measures Orientation Global Cost - € Global Cost Macroeconomic - € Global Cost - € Global Cost Macroeconomic - € North 6.400,52 € 6.925,69 € 11.652,36 € 11.312,97 € East 6.794,49 € 7.351,99 € 11.652,36 € 11.312,97 € West 6.188,84 € 6.696,64 € 11.652,36 € 11.312,97 € South 6.785,67 € 7.342,44 € 11.652,36 € 11.312,97 € RESULTS 96 Table 23: Actual Building with A/C vs Building with All measures + A/C per orientation Financial Feasibility Macroeconomic financial analysis Orientation NPV - € IRR SPP (Years) NPV - € North -11.483,19 € -5% 79 -9.824,79 € East -11.371,47 € -5% 77 -9.732,88 € West -11.394,99 € -5% 78 -9.752,23 € South -11.286,21 € -5% 75 -9.662,73 € Actual Building with A/C Building with all measures + A/C Orientation Global Cost - € Global Cost Macroeconomic - € Global Cost - € Global Cost Macroeconomic - € North 6.400,52 € 6.925,69 € 17.883,71 € 17.655,38 € East 6.794,49 € 7.351,99 € 18.165,96 € 17.960,78 € West 6.188,84 € 6.696,64 € 17.583,83 € 17.330,88 € South 6.785,67 € 7.342,44 € 18.071,88 € 17.858,98 € RESULTS 97 For the scenario where all measures are implemented except for the external wall façade insulation (given that it has the lowest impact on thermal comfort) the financial analysis described previously was also carried out (Tables 25, 26). 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Fabricwalls Have (insulation) upgrades been carried out to the external and/or courtyard wall construction? (Yes: 0 || No: 1) _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ 3b. Fabricglazing/shading APPENDIX 1 111 Have door/ window glazing been upgraded? (For example, to double glazing, UPVC frames, films installed etc.) (Yes: 0 || No: 1) Is use made of internal blinds? _____________________________________________________________________ _____________________________________________________________________ 3c. Balconies Have any modifications to the balconies been carried out? (Yes: 0 || No: 1) _____________________________________________________________________ _____________________________________________________________________ ____________________________________________________________________ 4. Equipment a. Lighting type Dining room: % LEDs ____ % fluorescent ____ % incandescent____ Bathrooms: % LEDs ____ % fluorescent ____ % incandescent____ Bedrooms: % LEDs ____ % fluorescent ____ % incandescent____ Kitchen: % LEDs ____ % fluorescent ____ % incandescent____ Others: % LEDs ____ % fluorescent ____ % incandescent____ APPENDIX 1 112 b. Space cooling and heating: - List of zones with split-unit heat pump/s _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ - Age of heat pump equipment (are heat pumps inverter driven?): _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ - List of zones using heaters, state heating duration and type including fuel used for heaters _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ c. Domestic Hot Water (DHW) No. and capacity of storage heaters: - Storage heater 1: Capacity: ______ Distribution: ______________ - Storage heater 2: Capacity: ______ Distribution: ______________ - Are storage heater always switched on (0) or only prior to usage (1)? : ________ - Use of DHW heat pumps (Yes: 0 || No: 1): __________ d. Refrigeration - Refrigerator 1: APPENDIX 1 113 Class ___ Model ___ - Refrigerator 2: Class ___ Model ___ e. Cooking - Is use made of electrical hobs or electric kettles? (Yes: 0 || No: 1) _______________________________________________________________ ____ - Is use made of microwave/ electric equipment for cooking? (Yes: 0 || No: 1) _______________________________________________________________ ____ _______________________________________________________________ ____ f. Water - Are aerators connected to faucets? (Yes: 0 || No: 1) _______________________________________________________________ ____ - Is water pressurised? (Yes: 0 || No: 1) ___________________________________________________________________ g. Plug loads: - Use of dishwasher (Yes: 0 || No: 1): - Other loads (for example PCs/ TV etc.): 120 Table 30: Questionnaire results for block house C Entr ance N° Fl at N ° N° of occup ants Qua ntity Heat Pum ps Heater s Gas_he a / Electri c_hea / None_ hea Water heater Continu ously On Yes / No Fridgefreezer Age New_d ge / MidAg e_dge / Old_dg e / More_ dge Freeze r Age New_z er / MidAg e_zer / Old_ze r / None_z er Oven Gas_o v / Electri c_ov Quant ity Electri c Equip ment for Cooki ng Washin g Machin e Age New_w m / MidAg e_wm / Old_w m / More_ wm Ot her Plu g Lo ads Total Consu mption 17 kWh Uncomfort able_W/ Comfortabl e_W Winter Uncomfor table_S / Comforta ble_S Summer C 1 5 0 Gas_he a Yes Old_dg e None_z er Electri c_ov 0 More_ wm 0 Uncomforta ble_W Comfortab le_S C 2 3 0 None_h ea Yes MidAg e_dge MidAg e_zer Gas_o v 2 New_w m 1 365 Comfortabl e_W Uncomfort able_S C 4 3 1 Gas_he a Yes Old_dg e MidAg e_zer Gas_o v 2 New_w m 3 1095 Comfortabl e_W Uncomfort able_S C 5 2 0 Gas_he a No Old_dg e None_z er Gas_o v 2 New_w m 2 730 Comfortabl e_W Comfortab le_S C 6 3 0 None_h ea Yes MidAg e_dge None_z er Gas_o v 1 New_w m 3 Comfortabl e_W Comfortab le_S C 7 3 0 Electric _hea Yes MidAg e_dge None_z er Gas_o v 1 New_w m 5 1825 Comfortabl e_W Comfortab le_S C 8 4-5 2 None_h ea Yes Old_dg e None_z er Gas_o v 1 New_w m 0 0 Comfortabl e_W Comfortab le_S C 9 4 2 None_h ea No MidAg e_dge New_z er Electri c_ov 1 New_w m 6 2190 Uncomforta ble_W Uncomfort able_S C 10 5 2 Gas_he a No MidAg e_dge New_z er Electri c_ov 0 New_w m 6 2190 Uncomforta ble_W Uncomfort able_S 121 Table 31: Questionnaire results for block house D Entr ance N° Fl at N ° N° of occup ants Qua ntity Heat Pum ps Heater s Gas_he a / Electri c_hea / None_ hea Water heater Continu ously On Yes / No Fridgefreezer Age New_d ge / MidAg e_dge / Old_dg e / More_ dge Freeze r Age New_z er / MidAg e_zer / Old_ze r / None_z er Oven Gas_o v / Electri c_ov Quant ity Electri c Equip ment for Cooki ng Washin g Machin e Age New_w m / MidAg e_wm / Old_w m / More_ wm Ot her Plu g Lo ads Total Consu mption 17 kWh Uncomfort able_W/ Comfortabl e_W Winter Uncomfor table_S / Comforta ble_S Summer D 3 2 2 None_h ea No MidAg e_dge None_z er Electri c_ov 1 MidAge _wm 2 730 Comfortabl e_W Uncomfort able_S D 4 2 0 Electric _hea Yes New_d ge None_z er Electri c_ov 0 New_w m 1 365 Comfortabl e_W Comfortab le_S D 5 2 1 None_h ea Yes Old_dg e Old_zer Gas_o v 2 New_w m 2 730 Comfortabl e_W Uncomfort able_S D 6 6 0 Gas_he a No New_d ge None_z er Gas_o v 1 New_w m 0 0 Uncomforta ble_W Uncomfort able_S D 7 3 1 None_h ea Yes Old_dg e None_z er Gas_o v 1 MidAge _wm 3 1095 Comfortabl e_W Uncomfort able_S D 8 4 0 Electric _hea Yes Old_dg e Old_zer Gas_o v 2 MidAge _wm 3 1095 Comfortabl e_W Comfortab le_S D 9 2 0 Electric _hea Yes Old_dg e None_z er Gas_o v 0 Old_w m 1 Uncomforta ble_W Uncomfort able_S D 10 3 2 None_h ea Yes MidAg e_dge None_z er Gas_o v 1 New_w m 3 1095 Uncomforta ble_W Uncomfort able_S 122 Appendix 2 A2.1 Discomfort hours analysis A2.1.1 Summer design week - Base building scenario Windows close Figure 69: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the ASHRAE adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 164 168 168 168 168 168 168 East 168 168 168 168 168 168 168 South 164 168 168 168 168 168 168 West 168 168 168 168 168 168 168 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Closed ASHRAE Adaptive Comfort Model - Base Model APPENDIX 2 123 Figure 70: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the M. Vellei et al. [35] model Figure 71: Base scenario number of Discomfort Hours during the Summer design week for windows close configuration on the EN 15251 adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 135 160 161 163 165 168 147 East 143 161 166 168 164 165 161 South 136 155 160 162 164 168 148 West 138 164 165 168 167 167 158 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Closed M. Vellei et al Adaptive Comfort Model - Base Model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 138 168 168 168 168 168 167 East 151 168 168 168 168 168 168 South 138 168 168 168 168 168 167 West 149 168 168 168 168 168 168 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Closed EN 15251 Adaptive Comfort Model - Base Model APPENDIX 2 124 Windows open Figure 72: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the ASHRAE adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 153 159 161 168 166 168 148 East 165 156 168 168 153 157 166 South 155 164 164 168 164 162 152 West 155 168 159 168 168 168 150 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open ASHRAE Adaptive Comfort Model - Base Model APPENDIX 2 125 Figure 73: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the M. Vellei et al. [35] model Figure 74: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration on the EN 15251 adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 115 125 121 118 127 146 105 East 137 114 139 138 111 124 130 South 120 118 131 118 126 134 103 West 119 135 126 124 139 148 113 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open M. Vellei et al Adaptive Comfort Model - Base Model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 115 132 132 152 138 156 103 East 141 118 156 168 117 128 139 South 123 127 135 152 140 140 107 West 121 148 134 149 156 160 112 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open EN 15251 Adaptive Comfort Model - Base Model APPENDIX 2 126 A2.1.2 Summer design week - Building with all retrofit measures Figure 75: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the ASHRAE adaptive comfort model Figure 76: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the M. Vellei et al. [35] model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 25 44 31 572 126 23 East 51 42 72 37 51 90 55 South 11 20 27 339 84 14 West 38 58 45 13 88 122 38 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open ASHRAE Adaptive Comfort Model + Retrofit measures implemented Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 21 27 22 23 31 41 20 East 25 20 36 37 20 24 26 South 22 22 27 722 28 20 West 19 29 20 22 39 40 24 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open M. Vellei et al Adaptive Comfort Model + Retrofit measures implemented APPENDIX 2 127 Figure 77: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented on the EN 15251 adaptive comfort model A2.1.3 Summer design weekBuilding with all retrofit measures except for the external wall façade Figure 78: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the ASHRAE adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 0000019 0 East 0000040 South 0000040 West 0000216 0 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open EN 15251 Adaptive Comfort Model + Retrofit measures implemented Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 44 54 62 40 78 133 50 East 91 51 116 65 58 95 108 South 51 36 68 42 63 104 61 West 68 85 82 50 111 136 72 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open ASHRAE Adaptive Comfort Model + Retrofit measures implemented - ext.wall façade APPENDIX 2 128 Figure 79: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the M. Vellei et al. [35] model Figure 80: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation on the EN 15251 adaptive comfort model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 21 27 32 36 34 38 24 East 37 21 38 38 21 26 38 South 28 22 35 36 31 31 28 West 25 36 30 33 37 42 25 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open M. Vellei et al Adaptive Comfort Model + Retrofit measures implemented - ext.wall façade Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 0000023 0 East 4070055 South 0000060 West 0030428 0 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open EN 15251 Adaptive Comfort Model + Retrofit measures implemented - ext.wall façade APPENDIX 2 129 A2.1.4 Summer design week - Building with all retrofit measures except for the external wall façade and double glazing Figure 81: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the ASHRAE adaptive comfort model Figure 82: Base scenario number of Discomfort Hours during the Summer design week for windows open configuration and all retrofit measures implemented except for the external wall façade insulation and double glazing on the M. Vellei et al. [35] model Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 47 57 66 42 86 134 55 East 104 54 123 71 64 96 114 South 54 42 74 44 66 105 64 West 79 107 100 66 129 151 82 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open ASHRAE Adaptive Comfort Model + Retrofit measures implemented - ext.wall façade - glazing Bedroom 1A Bedroom 1B Bedroom 1C Bathroom 1A Bathroom 1B Kitchen Dining North 22 28 34 36 33 38 25 East 33 21 37 39 21 25 38 South 27 22 33 36 32 32 29 West 23 37 30 35 36 55 28 0 20 40 60 80 100 120 140 160 180 Discomfort Hours Discomfort Hours Design Week Summer Windows Open M. Vellei et al Adaptive Comfort Model + Retrofit measures implemented - ext.wall façade - glazing