Economic impact of integrating PCM as passive system in buildings using Fanger comfort model

Accepted Manuscript Title: Economic impact of integrating PCM as passive system in buildings using Fanger comfort model Author: Mohammad Saffari Alvaro de Gracia Svetlana Ushak Luisa F. Cabeza PII: DOI: Reference:

S0378-7788(15)30441-2 http://dx.doi.org/doi:10.1016/j.enbuild.2015.12.006 ENB 6324

To appear in:

ENB

Received date: Revised date: Accepted date:

29-6-2015 27-11-2015 4-12-2015

Please cite this article as: M. Saffari, A. de Gracia, S. Ushak, L.F. Cabeza, Economic impact of integrating PCM as passive system in buildings using Fanger comfort model, Energy and Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.12.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

1 Highlights:

3

Fanger thermal comfort model is used in PCM-incorporated buildings.

4

Energy performance of buildings with different HVAC schedules has been studied.

5 6

Cooling and heating performance has been improved in all cases with PCM except for office profile in winter.

7

Short payback periods, below three years, have been achieved.

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Economic impact of integrating PCM as passive system in buildings using Fanger comfort model

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Mohammad Saffari1, Alvaro de Gracia2, Svetlana Ushak2,3, Luisa F. Cabeza1*

16

1GREA Innovació Concurrent, Universitat de Lleida, Pere de Cabrera s/n, 25001, Lleida, Spain.

17 18

2Center for Advanced Study of Lithium and Industrial Minerals (CELiMIN), University of Antofagasta, Av. Universidad de Antofagasta 02800, Campus Coloso, Antofagasta, Chile.

19

3Solar Energy Research Center (SERC), Av. Tupper 2007 - 4th Floor,Santiago,Chile.

20

* [email protected]

21

Abstract

22 23 24 25 26 27 28 29 30 31 32 33 34

In buildings, HVAC systems consume a high amount of energy to provide thermal comfort for occupants. A methodology is presented in this paper to control thermostat operation of the buildings considering the effects of indoor and outdoor boundary conditions and phase change material (PCM) characteristics. EnergyPlus v8.1 building energy simulation software was

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used to analyze the energy performance of the PCM incorporated building models and to implement Fanger model to control HVAC thermostat operation according to BS EN 15251:2007 thermal comfort categories. Three types of building HVAC schedule, PCM with different melting points and layer thicknesses were studied for Madrid climate zone. Moreover, the impact of occupants clothing on the energy consumption was investigated. Furthermore,

payback analysis was conducted to find out the economic benefits of PCM integration into the building envelopes. Application of PCM improved the cooling and heating energy performances except for the office model in winter (heating period). Additionally, higher energy savings and lower payback periods were observed when 1 Page 1 of 38

35 36 37

PCM with higher melting point was applied to the buildings. Eventually, energy savings in PCM incorporated models were found to improve further when occupants changed their clothing behavior in winter.

38 Keywords

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PCM in building envelopes; Fanger thermal comfort; EnergyPlus Simulation; Payback period.

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41 Introduction

43 44 45 46 47 48 49 50 51 52 53 54

The average global temperature is rising because of an increase in greenhouse gases which have been emitted from human activities [1]. The building sector is responsible of about one-third of all end use CO2 emissions [2]. In Europe, 40% of energy is consumed by buildings [3] and nearly 50% of energy consumption in buildings is due to HVAC systems [4]. Hence, reduction of space air-conditioning needs of building sector is highly important and effective to improve energy efficiency [2,5,6]. According to the 2-degrees scenario (2DS), the building sector has to reduce its total CO2 emissions by over 60% by 2050 in order to reduce global temperature rise to 2 °C [1]. This goal is achievable through advanced building materials to construct highperformance buildings or renovate inefficient existed buildings [2,7]. It is noteworthy that the quality and energy efficiency of the building envelope are the most influential factors in determining the heating and cooling energy consumptions as well as the occupants comfort level while offering the cheapest way of carbon emissions reduction [6,8].

55 56 57 58 59 60 61 62 63

Thermal energy storage (TES) is an effective way to enhance energy efficiency in buildings by increasing the heat capacity of light-weight buildings especially steel structures and adding more thermal mass to concrete and brick structures. These systems are promising solutions to cut-down energy consumption by taking advantage of materials with high energy storage capacity to store energy in terms of sensible heat and latent heat. Materials used for latent heat storage are known as Phase Change Materials (PCM) [9–14]. PCMs are distinguished because of their high latent heat capacity which permits them to store a high amount of energy in small temperature intervals resulting in a significant increase in the thermal mass of the building when incorporated into its envelope [11,15–18].

64 65 66 67 68 69

Energy performance improvement in buildings could be achieved either by passive means (building envelope development) [19] or by active means (smarter HVAC equipment) [20]. Investment in the building envelope is preferable since a good passive design could bring longterm energy efficiency and decarbonisation by help of sun; a free, clean and widely-available renewable energy source. Additionally, it will provide higher thermal comfort which leads to increase energy savings due to stabilization of indoor air temperature [8,21].

70 71 72 73 74 75 76 77 78

Over the last decade, a considerable number of reviews have been made on the PCM technologies for building applications. Many investigators have mentioned advantages of PCMs in terms of cooling and heating energy savings, peak load shifting and thermal comfort improvement when applied to buildings [16,17,22–28]. Furthermore, previous researchers have drawn attention to inherent issues addressing uncertainties and important factors affecting efficient utilization of PCM in building system such as their melting point and melting range temperature [29,30], convective heat transfer of the PCM wall [31], location and integration (condensed or dispersed) [32], climate zone (air temperature, wind velocity, solar radiation) [27], latent heat of fusion [33], and HVAC thermostat set point [34].

79 80 81 82 83 84

Building energy simulation is a cost-effective and time-efficient solution to estimate the effectiveness of energy saving adaptations applied to the building. Hereof, a significant number of researchers addressed numerical simulation methods by use of whole building dynamic simulation software such as EnergyPlus [29,33,35] , TRNSYS [36–38], ESP-r [39–41], etc. to identify the role of PCM in energy savings of buildings and to overcome exhibited problems and uncertainties. For example, findings of Alam et al. [34] & Evola et al. [15] lend support to

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111 112 113 114 115 116 117 118 119 120 121 122 123

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the claim that selection of a PCM melting range is highly dependent on the local thermostat set points as well as local climate. Moreover, expected energy savings are not achievable unless the appropriate PCM melting point temperature and thermostat comfort temperature are selected [33,34]. In addition, Soares et al. [29] investigated the annual energy saving effects of drywall PCM when applied to a light weight steel framed building model in different European climates. They indicated that the energy performance of the light steel-framed residential building model was notably improved in all considered climates when PCM drywalls were installed. Similarly, Alam et al. [34] studied the ability of PCM to reduce building HVAC demand in principal Australian cities considering various types of PCM, their quantity and location of application in the building enclosure. Based on their findings, application of PCM can decrease diurnal and nocturnal temperature fluctuations and increase thermal comfort of occupants. Along similar lines, J.S. Sage-Lauck et al. [33] described incorporation of PCM in a passive house to shorten its overheating in summer period and their results indicated significant reduction of overheating hours in a specific zone and correspondingly thermal comfort improvement when PCM applied in as a passive system. Subsequently, the effectiveness of incorporation of PCM in an eightstory research building in Seoul through dynamic whole building energy simulation was evaluated by Seong et al. [30]. Their studied building had an HVAC schedule very similar to an office HVAC profile with constant set point temperatures for heating and cooling. It was observed that utilization of PCM could improve the cooling performance; nevertheless, the use of PCM increased the energy consumption for heating because in the heating period, the low ambient temperature which was also below the PCM melting point temperature prevented the PCM to absorb heat to reach its melting point temperature and melt. Further results will be drawn in the present paper regarding the use of PCM in a building with office HVAC profile and the increase of heating energy consumption in such buildings which was not explained in the above mentioned research.

Most of the previous studies investigated the effects of PCM on the energy performance and the discomfort hours according to a fixed thermostat temperature. Although a fixed thermostat temperature control could be an option for a specific climate zone and building type as recommended by the exiting practices [42,43], it does not consider the influences of the outdoor and indoor boundary conditions neither the building characteristics. Building location, construction materials such as PCM, insulation etc. are influencing parameters for the heat gains and losses in the building , so that, it does not seem very realistic to set a fixed thermostat operation for indoor thermal comfort level regulation [44] since thermal comfort differs between climate zones. Accordingly, the residents behaviors and the building profile strongly impact the energy efficiency in buildings which should be considered in building energy simulation [30,45]. Additionally, information about the payback period when PCM is incorporated in the building could be useful to persuade householders and construction industry to adopt the PCM technology when constructing or renovating their buildings.

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124 125 126 127 128 129

A methodology will be presented in this paper to set out HVAC operation according to BS EN 15251:2007 [43] thermal comfort categories and to evaluate it over three types of building models with different HVAC schedules and PCM layer thickness. When thermal comfort is retained to a high degree, energy consumption increases and this fact begs the question if PCM can alleviate the extensive energy consumption generated from the high thermal comfort 4 Page 4 of 38

expectation or not and to what extent it is achievable. Moreover, a payback period analysis will be conducted to estimate the economic benefits associated to the PCM integration in the building envelope. Furthermore, building occupants will be informed about the importance of the PCM technology and the potential energy saving gains yielding from their attitude (mainly clothing insulation) in heating season, and the corresponding results will be investigated.

135 136 137 138

To the authors best knowledge, very few publications are available in the literature that address the application of Fanger comfort control to set out calculated thermostat set point temperature [46–48] and this is the first study which regulates indoor air temperature of PCM integrated building based on the thermal comfort criteria.

139

Methodology

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Overview

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In this chapter, an overview of the numerical method and the workflow procedure is presented. The information regarding the energy simulation software and its validity is given in section 2.2. Afterwards, in order to simulate different PCMs, their enthalpy-temperature (h-T) curves were built according to the method presented in section 2.3. Then, in section 2.4, different building prototypes were classified according to their PCM melting point temperature and PCM layer thickness. Subsequently, to evaluate the effects of different HVAC schedules on the energy performance of the PCM-incorporated buildings, three HVAC schedules were considered according to section 2.5. Afterwards, Fanger PMV values were assigned to control the thermal comfort condition in the buildings. Further explanations regarding thermal comfort HVAC control is presented in section 2.6. In section 2.7, a methodology is presented to study the potential energy-saving benefits corresponding to the behavior of the occupants. Further on, a simplified payback period analysis is described in section 2.8 to analyze the payback period of PCM inclusion in different building models with various thermal comfort levels. Eventually, the whole simulation scenarios are presented in section 2.9. The whole methodology workflow can be seen in Figure 1.

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Figure 1. Methodology workflow.

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160 161

Energy simulation

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180 181

PCM characterization

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A set of numerical simulations were performed using EnergyPlus v8.1 dynamic building energy simulation. In order to simulate PCM in EnergyPlus, a Conduction Finite Difference (CondFD) solution algorithm must be used. This algorithm discretizes building enclosure such as (walls, floors and ceilings) into various nodes and numerically solves the heat transfer equations by use of a finite difference method (FDM) which could be selected between Crank-Nicholson or fully implicit [35,49,50]. EnergyPlus (CondFD) and PCM algorithms were verified and validated through analytical verification (Stefan Problem), comparative testing (against Heating 7.3) and empirical validation (DuPont Hotbox) by Tabares-Velasco et al. [51,52]. Furthermore, PCM algorithm of EnergyPlus was validated against observed data from a residential building [33] and also in another study [34] it was verified against the experimental data of Kuznik and Virgone [53], which experimentally investigated the thermal performance of a PCM copolymer composite wallboard in a lightweight building as a full scale test room. The thermal performance of the test room was analyzed for three periods of summer, mid-season and winter. Inclusion of the PCM in the wallboard showed reduction of wall surface temperature fluctuations and thermal comfort enhancement. Eventually, due to the availability of the numerical experiments in above mentioned work, it can be used as a reference building for validation of numerical simulations.

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The enthalpy method was used based on E.Feustel simplified equation (see Eq.(1)) [54,55] to construct h-T curves of the PCMs, introducing physical properties of RUBITHERM® RT organic PCMs [56].Three ideal hypothetical PCMs were chosen with 23 °C, 25 °C and 27 °C main peaks with reference temperature at -20 °C and melting range of 4 °C. Density change due to phase change was not considered since it was negligible. The specific heat capacity and enthalpy trends as function of temperature are presented in Figure 2.

h(T ) = c p ,const T +

h2 − h1   2β  × 1 + tanh  (T − Tm )   (1) 2 τ  

191 192

Where Cp= specific heat [kJ/kg.K], T= temperature [◦C], h=specific enthalpy [kJ/kg],

193

β= inclination [-], τ= width of the melting zone [K], Tm= melting temperature [◦C].

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Figure 2.h-T & T-Cp curves of hypothetical PCMs with 23 °C, 25 °C and 27 °C main peaks.

196

Building model development

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Case-600 building model prototype was selected from ANSI/ASHRAE Standard 140-2011 [57] as a basecase (BC) model in the current paper (see Figure 3). This model is a rectangular single zone (8 m wide × 6 m long × 2.7 m high) with no internal partitions and 12 m² of glazing on the south wall. The construction details of this lightweight building model are shown in Table 1 to Table 3. It should be noted that the window type in PCM-integrated model is as the same as the basecase model (see Table 4).

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Figure 3.Building model.

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Table 1. Wall construction of the basecase building. K

Element

Thickness U

(W/m.K) (m)

Int.Surface Coeff.

R

Density Cp

(W/m2.K) (m2.K/W) (kg/m3) 8.26

0.121

(J/kg.K)

Plasterboard

0.160

0.012

13.33

0.075

950

840

Fiberglass Quilt

0.040

0.066

0.61

1.650

12

840

7 Page 7 of 38

Wood Siding

0.140

0.009

15.56

0.064

Ext.SurfaceCoeff.

29.41

0.034

Overall,air-to-air

0.514

1.944

530

900

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208 209 Table 2.Roof construction of the basecase building.

8.26

0.121 0.063

Plasterboard

0.160

0.01

16.00

Fiberglass Quilt

0.040

0.1118

0.36

Roof Deck

0.140

0.019

7.37

M

Ext.Surface Coat

(J/kg.K)

950

840

2.795

12

840

0.136

530

900

29.41

0.034

0.318

3.148

d

Overall,air-to-air

Density Cp

(W/m2.K) (m2.K/W) (kg/m3)

(W/m.K) (m)

Int.Surface Coeff.

211

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Table 3.Floor construction of the basecase building.

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R

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Element

Thickness U

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K

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210

K

Element

Thickness U

(W/m.K) (m)

Int.Surface Coeff.

Density Cp

R

(W/m2.K) (m2.K/W) (kg/m3) 8.26

0.121

Timber Flooring

0.140

0.025

5.60

0.179

Insulation

0.040

1.003

0.04

25.075

0.039

25.375

Overall,air-to-air

650

(J/kg.K)

1200

214 215

Table 4.Window properties of the basecase and PCM-integrated buildings. Extinction coefficient

0.0196/mm

Number of panes

2

8 Page 8 of 38

Air-gap thickness

13 mm

Index of refraction

1.526

Normal direct-beam transmittance through one pane

0.86156

Thermal Conductivity of glass

1.06 W/mK

Conductance of each glass pane

333 W/m2K

Combined radiative and convective coefficient of air gap

6.297 W/ m2K

Exterior combined surface coefficient

21.00 W/ m2K

us 8.29 W/ m2K

Interior combined surface coefficient

3.0 W/ m2K

an

U-value from interior air to ambient air

0.9

Density of glass

2500 kg/m3

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Hemispherical infrared emittance of ordinary uncoated glass

Specific heat of glass Interior shade devices

750 J/kg.K None 0.907

Double-pane solar heat gain coefficient at normal incidence

0.789

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Double-pane shading coefficient at normal incidence

In the present work the Rubitherm CSM (Compact Storage Modules) panels (see Figure 4) [58] filled with organic RT PCM with two different thicknesses, 10 mm and 5 mm, with three melting point temperatures, 23 °C, 25 °C and 27 °C were placed in the inner part of the walls and roof construction as it is shown in Tables 5 and 6. The climate zone of Madrid was selected to carry out the present study. According to Köppen-Geiger climate classification [59] the weather of Madrid is classified as Csa (warm temperate, summer dry, hot summer) which coincides with most of the southern European areas. To find out the appropriate melting point temperatures for the Madrid climate zone , first of all the comfort temperatures for the summer and winter periods were determined using Climate Consultant v6.0 and psychrometric chart of ASHRAE 55 standard [60]. On this basis, the indoor comfort temperature varies between 20 and 24ºC in winter, and from 24 to 27 ºC in summer. The upper limit of the melting point is fixed because of two reasons, first, not to be higher than comfort during summer (otherwise during the melting period, the PCM would be heating up the room), and second is that the PCM melting temperature has to ensure the melting process during winter (storage of solar energy) as many days as possible. On the other hand, the lower limit of the melting point is fixed due to two reasons, first, because of the free cooling potential during summer period; hence melting temperature cannot be lower than outer temperature at night in order to ensure the solidification process during summer and to have the PCM charged for operating during the following day. Second, the melting temperature has to be higher than

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Pane thickness

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lower limit of comfort range in winter; otherwise the PCM is not heating the room during its solidification process. The building models were classified according to their PCM melting point temperature and PCM layer thickness with a prefix of Px-y, where x is the melting temperature and y is the PCM thickness. Hence, the studied layers correspond to PCM herein are (P23-10, P23-5, P25-10, P25-5, P27-10 and P27-5). Further information addressing CSM panels characteristics and instruction guidelines can be found in the references [58] and [61].

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Figure 4. RUBITHERM CSM PCM-Panel [56].

Table 5.Wall construction of the PCM integrated building prototypes. K

Thickness

Element (W/m-K) (m)

8.26

0.121

13.33

0.075

950

840

PCM

0.20

0.01&0.005 20.00

0.050

880

2000

Fiberglass Quilt

0.040

0.066

0.61

1.650

12

840

0.009

15.56

0.064

530

900

Ext.SurfaceCoeff.

29.41

0.034

Overall,air-to-air

0.501

1.994

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0.012

(J/kg-K)

0.160

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Density Cp

Plasterboard

Wood Siding

245

R

(W/m2-K) (m2-K/W) (kg/m3)

d

Int.Surface Coeff.

U

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235 236 237 238 239 240

0.140

Table 6.Roof construction of the PCM integrated building prototypes. K

Thickness

U

R

Density Cp

Element (W/m2-K) (m2-K/W) (kg/m3)

(W/m-K) (m) Int.Surface Coeff.

8.26

0.121

(J/kg-K)

Plasterboard

0.160

0.01

16.00

0.063

950

840

PCM

0.20

0.01&0.005 20.00

0.050

880

2000

10 Page 10 of 38

0.040

0.1118

0.36

2.795

12

840

Roof Deck

0.140

0.019

7.37

0.136

530

900

Ext.Surface Coat

29.41

0.034

Overall,air-to-air

0.313

3.198

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Fiberglass Quilt

247 248

HVAC system

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249

Since this is a comparative study, the ideal load air system was used instead of any specific HVAC system to model the mechanical system because the main objective of the research is to investigate energy savings due to incorporation of PCM and implementation of new HVAC control strategies. This system supplies an ideal hot and cold air and it is a 100% convective air system with an efficiency ratio equal to 100% without capacity limitation in order to meet the specified controls. The supplied air flow rate varies from zero to maximum in order to supply appropriate amount of heating or cooling air to the zone to provide zone conditioned air needs [49,62,63]. Additionally, for dehumidification and humidification a constant supply humidity ratio control was considered which fixes the limits of maximum and minimum humidity ratio both for heating and cooling, respectively [49]. Furthermore, different HVAC schedules will be examined numerically considering a constant internal equipment gain of 200 Watts [57]. Table 7 and Table 8 show the hourly and monthly HVAC operations, respectively.

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Table 7. Hourly HVAC schedule.

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Occupancy schedule

Hours HVAC system is on

Office

8:00-16:00

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250 251 252 253 254 255 256 257 258 259 260 261

Residential

00:00-8:00 & 16:00-24:00

24-Hours

00:00-24:00

Table 8.Monthly HVAC control. Month

J F M A M J J A S O N D

HVAC

Single Cooling Single Heating Free Floating

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Thermal Comfort

265 266 267

Thermal comfort is that condition of mind that expresses satisfaction with the thermal environment [42]. Thermal comfort can be measured by different methods such as: 11 Page 11 of 38

268 Adaptive thermal comfort theory (ADT), which was developed to mention that the ambient weather conditions affect indoor comfort conditions and occupants can adapt themselves to a higher or lower inside temperature [42,43,47,64].

272 273

Operative temperature (TOperative), which can be calculated with the mean value of air temperature and mean radiant temperature with special conditions [42].

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Fanger Predicted Mean Vote (PMV) model (see Figure 5), which applies heat balance principles to correlate four physical factors (air temperature, mean radiant temperature, air velocity, and air humidity), and two personal factors (clothing insulation and metabolic rates of daily activities) to predict thermal comfort on the basis of ASHRAE thermal sensation scales (see Table 9) [65,66].

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269 270 271

280 281 282

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Figure 5. Thermal comfort factors of Fanger PMV model.

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This model was developed by Fanger [67] to predict the average thermal perception for a large group of people based on their thermal sensation (how cold or hot they feel) so that, even if the thermal comfort in a zone is kept according to PMV model, there will be some unsatisfied occupants [43,68,69]. The comfort model of Fanger is based upon an energy analysis that takes into account all the modes of energy loss from the body, including the convection and radiant heat loss from the outer surface of the clothing, the heat loss by water vapor diffusion through the skin, the heat loss by evaporation of sweat from the skin surface, the latent and dry respiration heat loss and the heat transfer from the skin to the outer surface of the clothing [62].

291 292

In addition, another index is also developed by Fanger which is called Predicted Percentage Dissatisfied (PPD) which could be calculated through PMV, and expresses the expected

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293 294

percentage of people who are thermally uncomfortable in the subjected environment. The relationship between PPD and PMV is shown in Figure 6.

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Table 9.ASHRAE thermal sensation scales (PMV) [42,65].

-2

-1

0

1

2

3

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Cold Cool Slightly cool Neutral Slightly warm Warm Hot

M

PPD = 100–95 × exp (- 0.03353× PMV4– 0.2179 × PMV2)

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Figure 6.PPD as function of PMV [42,65].

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Recommended PMV-PPD criteria for the thermal well-being for mechanically heated and cooled buildings are illustrated in Tables 10 & 11.

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Table 10.Recommended categories and PPD for mechanically conditioned buildings [43,65].

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Category Thermal state of the body as a whole PPD % Predicted Mean Vote

I

<6

-0.2 < PMV < +0.2

II

< 10

-0.5 < PMV < +0.5

III

< 15

-0.7 < PMV < +0.7

IV

> 15

PMV < -0.7 ; or +0.7 < PMV

304 305 306 307

Table 11.Description of the applicability of the (BS EN 15251, 2007) thermal comfort categories [43].

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Explanation

I

High level of expectation and is recommended for spaces occupied by very sensitive and fragile persons with special requirements like handicapped, sick, very young children and elderly persons

II

Normal level of expectation and should be used for new buildings and renovations

III

An acceptable, moderate level of expectation and may be used for existing buildings

IV

Values outside the criteria for the above categories. This category should only be accepted for a limited part of the year

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Category

308

328 329

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To control the HVAC operation according to the Fanger model, the PMV values were selected according to the thermal comfort requirements for heating and cooling periods (Cat.I, Cat.II, Cat.III and Cat.IV) to govern the indoor thermal environment instead of setting a fixed thermostat temperature. EnergyPlus Fanger algorithm reads hourly input PMV values to calculate a dry bulb temperature set point according to the selected thermal comfort model [49]. Thermostat set points could be computed as function of desired PMV (see Table 12),

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assuming the clothing values of 0.5 (Clo) and 1 (Clo) for summer and winter period (except for the models with variable clothing), respectively, air velocity (ν) of 0.15 (m/s), activity level (metabolic rate) of 1.2 met coupled with relative humidity (Rh) and mean radiant temperature (Tr) from EnergyPlus simulation [46,47,65]. These values were set as recommended by the ANSI/ASHRAE 55-2013 [42] and BS EN 15251-2007 [43]. In addition, EnergyPlus thermal comfort model allows users to introduce maximum and minimum dry bulb temperature limit to override PMV control. It should be noted that, the user defined temperature limits need to have an ample enough range to make sure that the PMV control is not overridden by these upper and lower temperature limits [48]. Furthermore, the energy-

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related consequences resulting from the PCM incorporation is taken into account since its existence influences the indoor air temperature and the mean radiant temperature (see Figure 7).

Table 12.Monthly PMV schedules. Months

Jan Feb Mar Apr May June July

Aug

Sept

Oct

Nov

Dec PPD[%]

Comfort Category

I

0.2

0.2

-0.2

0.2

-0.2

+0.2 +0.2 +0.2 +0.2 +0.2 +0.2 -0.2

5

II

0.5

0.5

-0.5

0.5

-0.5

+0.5 +0.5 +0.5 +0.5 +0.5 +0.5 -0.5

7

14 Page 14 of 38

III

0.7

IV -1

0.7

-0.7

0.7

-0.7

+0.7 +0.7 +0.7 +0.7 +0.7 +0.7 -0.7

10

-1

-1

-1

-1

+1

25

+1

+1

+1

+1

+1

-1

330

an

us

cr

ip t

331

333

M

332

Figure 7.Thermostat set point calculation scheme.

337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354

te

336

Occupants clothing

Energy use is highly dependent on how occupants behave to maintain their comfort [8,70]. Buildings Performance Institute Europe (BPIE) published a report in 2011 regarding energy performance of buildings in Europe by different countries [6]. Based on this report, awareness of energy-efficient technologies needs to be improved since there is still a lack of understanding of how much a new technology (such as PCM) can reduce carbon emissions, energy consumption and cost [6]. Moreover, some researchers stated that when HVAC is controlled based on the Fanger PMV algorithm a fixed clothing insulation for the cooling and

Ac ce p

335

d

334

heating period, may result in inaccurate energy consumption estimation and operative temperature [45]. On this basis, to present energy savings benefits of the residents behavior, they were informed about PCM technology and the importance of suitable clothing in winter. Afterwards, new scheduled clothing insulations were chosen instead of a constant (1 Clo) value, for the winter period. To simulate the new assumption, the clothing insulation for the winter period slightly increased in some hours which could be achieved by wearing warmer clothes (see Table 13). The new values of Clo were derived from Table 5.2.2.2 A of ASHRAE 55-2013 by selection of new sets of clothing [42]. It should be mentioned that in the present study only the occupants clothing behavior in the residential building for a unique comfort category (Cat.II) is studied since it is intended to inform the occupants of the residential buildings about the benefits of their behavior toward energy saving.

15 Page 15 of 38

355 356 Table 13.Clothing schedule-Residential Cat.II. Clothing [Clo]

24:00 to 07:00

1.14

07:00 to 08:00

1.00

08:00 to 16:00

Unoccupied

16:00 to 20:00

1.00

20:00 to 21:00

1.04

Payback period

cr us

te

359

1.10

d

358

an

21:00 to 24:00

ip t

Time [hour]

M

357

360

An economic analysis was performed to calculate the simple payback period for the PCM integrated building models. The simple payback is calculated for the energy savings measures in aggregate by dividing the total incremental cost of the measures (PCM panels and installation costs) by the energy savings in euros. The cost of the installation of PCM is approximated as 4.36 €/m2, according to ITeC [71] and the PCM cost per kg is 0.62 €/kg based on our previous purchase. The installation cost is the same per square meters when installing panels of 5 mm and panels of 10 mm. Moreover, the simple installation of the PCM panels inside the constructive system makes the maintenance cost negligible during the lifetime period, as other constructive components such as bricks, insulation layers, pre-fabricated concrete etc. Energy savings in euros can be calculated by using the Spanish national natural gas rate [72] and the national electric rate [73]. In addition, the costs of the PCM panels were obtained from RUBITHERM® [53]. The equation that describes the simple payback, in years, is determined by (Eq. (2)) [74,75]:

374

tp =

375 376

where tP = simple payback in years, CC0 = initial capital cost and Ces = annual energy cost savings.

Ac ce p

361 362 363 364 365 366 367 368 369 370 371 372 373

CC0 Ces

(2)

16 Page 16 of 38

377 378

Simulated scenarios

379 The simulation scenarios are categorized on the basis of the HVAC schedule, building prototypes and the thermal comfort categories. The last six scenarios correspond to the residential HVAC operation with variable clothing insulations values. A summary of the different simulation scenarios is presented in Table 14.

ip t

380 381 382 383

cr

384 385

Table 14.Simulation scenarios.

Clothing

Category I-II-III-IV

Fixed for summer & winter

P23-10

Category I-II-III-IV

Fixed for summer & winter

P25-10

Category I-II-III-IV

Fixed for summer & winter

P27-10

Category I-II-III-IV

Fixed for summer & winter

P23-5

Category I-II-III-IV

M

BC

d

24 -hour

an

Prototypes Thermal comfort

Fixed for summer & winter

Category I-II-III-IV

Fixed for summer & winter

Category I-II-III-IV

Fixed for summer & winter

BC

Category I-II-III-IV

Fixed for summer & winter

P23-10

Category I-II-III-IV

Fixed for summer & winter

P25-10

Category I-II-III-IV

Fixed for summer & winter

P27-10

Category I-II-III-IV

Fixed for summer & winter

P23-5

Category I-II-III-IV

Fixed for summer & winter

P25-5

Category I-II-III-IV

Fixed for summer & winter

P27-5

Category I-II-III-IV

Fixed for summer & winter

BC

Category I-II-III-IV

Fixed for summer & winter

P23-10

Category I-II-III-IV

Fixed for summer & winter

P25-10

Category I-II-III-IV

Fixed for summer & winter

P25-5 P27-5

te

HVAC schedule

Office

Ac ce p

387

us

386

Residential

17 Page 17 of 38

Fixed for summer & winter

P23-5

Category I-II-III-IV

Fixed for summer & winter

P25-5

Category I-II-III-IV

Fixed for summer & winter

P27-5

Category I-II-III-IV

Fixed for summer & winter

P23-10

Category II

Variable for winter & fixed summer

P25-10

Category II

Variable for winter & fixed summer

P27-10

Category II

Variable for winter & fixed summer

P23-5

Category II

Variable for winter & fixed summer

P25-5

Category II

P27-5

Category II

390

392

Overview

cr

us

an

Ac ce p

391

Variable for winter & fixed summer

te

Results and discussion

Variable for winter & fixed summer

d

388 389

ip t

Category I-II-III-IV

M

Residential

(variable clothing)

P27-10

393 394 395 396 397 398

In this chapter the simulation results are presented and discussed. First of all, the computed thermostat set points based on the presented methodology are presented for different scenarios in section 3.2. Afterwards, the energy savings results and the payback periods corresponding to each HVAC schedule are given in sections 3.3 (24 h), 3.4 (office) and 3.5 (residential), respectively. Subsequently, section 3.6 represents the energy savings and economic benefits due to the occupants clothing in winter season for the residential HVAC operation.

399

Thermostat set points

400 401 402 403 404 405 406

The calculated thermostat cooling and heating set points of the 24-hour (24 h) HVAC schedule for the P23-10, P25-10 and P27-10 models are illustrated in Figure 8 and Figure 9, respectively. The results corresponding to the models with 5 mm PCM thickness are not shown since the same trends as the models with 10 mm thickness PCM were existed among them. In the cooling period (see Figure 8), it was shown that during the sunshine period in all models with PCM, particularly P27-10 model, the solar radiation was absorbed by the PCM which prevented the 18 Page 18 of 38

overheating of the zone and it could be seen that thermostat set points in all PCM integrated models especially P27-10 model are higher in comparison to basecase model because less cooling was needed in the building prototypes with PCM. This fact finally led to high cooling energy savings in summer. On the other hand, at night when the outdoor temperature substantially reduced, thermostat cooling set points were increased in basecase model because the zone temperature was lower than the comfort temperature. By the way, this thermostat set point temperature rise in all cases with PCM and especially in P27-10 model was considerably lower in comparison to the basecase model.

415 416 417 418 419 420 421 422 423 424 425 426

Furthermore, in heating season (see Figure 9), all prototypes with 10 mm layer thickness of PCM showed energy savings as a result of thermostat set point improvement, however, the highest energy improvement was recorded for P23-10 prototype. From Figure 9, it could be derived that during the sunshine period, especially around 14:00 h (on the 7th of August), the zone temperature was increased due to the solar radiation and higher outdoor temperature, which caused reduction in thermostat set points. It has to be highlighted that in P23-10 model the calculated thermostat set points were higher than those in basecase, P25-10 and P27-10 models (from 09:00 to 17:00) because generally, in winter, the melting process can take place easier in PCMs with lower melting point due to the lower outdoor temperature. Consequently, it can be seen that in the evening and at night-time, the stored heat in P23-10 model was discharged and heating was provided for the zone; for that reason, lower heating set point temperatures were calculated for P23-10 prototype (from 18:00 to 07:00).

427 428 429 430 431 432 433 434 435

Very similar trends were observed for residential cooling and heating thermostat set points as well as office thermostat cooling operation; nevertheless, no specific improvement was observed for the heating period of the prototypes with office HVAC schedule in response to the various PCM solutions. For this reason further explanations will be given to analyze this result. Thermostat temperature analysis of office profile in Figure 10 shows that during the occupancy period and when the HVAC system was on; all cases with PCM had higher heating set point temperatures in comparison to basecase model. However, in the evening and over the night period (out of HVAC and occupancy schedule) thermostat set point improvement was shown in PCM integrated models. This behavior will be explained in details in section 3.4.

cr

us

an

M

d

te

Ac ce p

436

ip t

407 408 409 410 411 412 413 414

437 19 Page 19 of 38

438

Figure 8.Effects of PCM on thermostat operation in 2 summer days, 24 h schedule Cat.I.

an

us

cr

ip t

439

440 441

Figure 9.Effects of PCM on thermostat operation in 2 winter days, 24h schedule Cat.I.

443 444

Ac ce p

te

d

M

442

Figure 10.Effects of PCM on thermostat operation in 2 winter days, office schedule. Cat.I.

445 446

24-hour schedule

447 448 449 450

Comparisons of the cooling energy savings of the PCM integrated building models for a 24 h HVAC operation are shown in Table 15. The results indicate that the incorporation of PCM reduced cooling consumption in all cases, specifically in P27-10 models. Hence, it can be said 20 Page 20 of 38

451 452 453 454

that the highest the quantity and melting range of PCM, the highest the cooling energy savings. As an example, cooling peak load reduction, load shifting, and average inside surface temperature stabilization of P27-10 prototype in comparison to basecase model is demonstrated in Figure 11.

455

ip t

456 457

cr

458 459

Table 15.Cooling savings of 24 h schedule categorized by comfort categories and PCM solutions.

us

460 461

27%

22%

Cat.II

5497

29%

23%

Cat.III 4928

31%

Cat.IV 4138

34%

41%

37%

47%

42%

46%

40%

57%

52%

M

6420

48%

42%

63%

57%

26%

51%

44%

69%

62%

d

24%

Ac ce p

te

462

Cat.I

an

BC(kWh) P23-10 P23-5 P25-10 P25-5 P27-10 P27-5

463 464 465

Figure 11.Cooling performance analysis of PCM integrated model with 24 h schedule & Cat.I thermal comfort.

466 21 Page 21 of 38

ip t

For the heating period, all cases with PCM showed 3 to 8% energy savings, however, the prototypes with 23 °C melting point PCM showed better heating energy savings when compared to other models (see Table 16). A possible explanation for this result is that the investigated city (Madrid) has a heating dominant climate and in this period the outdoor temperature is lower than PCMs melting range which leads them to stay in their solid state. As a result, in the afternoon due to higher solar radiation, PCM with lower melting point (23 °C) reaches its melting range and charges the heat coming from the sun which could be used at nighttime when outdoor temperature reduces (see Figure 12). This process eventually improves the heating energy performance. Annual energy performance results showed that P27-10 models obtained the best heating and cooling energy savings in all thermal comfort categories (see Table 17).

te

d

M

an

us

cr

467 468 469 470 471 472 473 474 475 476

477

480 481 482

Figure 12. Heating performance analysis of P23-10 model with 24 h schedule & thermal comfort Cat.II.

Ac ce p

478 479

Table 16.Heating savings of 24 h schedule categorized by comfort categories and PCM solutions. BC(kWh) P23-10 P23-5 P25-10 P25-5 P27-10 P27-5

Cat.I

29516

4%

4%

4%

4%

3%

3%

Cat.II

26009

6%

5%

5%

4%

3%

3%

Cat.III 23707

7%

6%

5%

4%

4%

3%

Cat.IV 20336

8%

7%

5%

4%

4%

3%

483 484

22 Page 22 of 38

485 486

Table 17.Annual total energy savings of 24 h schedule categorized by comfort categories and PCM solutions. BC(kWh) P23-10 P23-5 P25-10 P25-5 P27-10 P27-5 35935

8%

7%

10%

9%

11%

10%

Cat.II

31506

10%

9%

12%

10%

13%

11%

Cat.III 28636

11%

9%

12%

11%

14%

12%

Cat.IV 24474

12%

10%

13%

11%

15%

13%

cr

487

Additionally, P27-5 prototypes showed lower payback period than P27-10 models (see Table 18).

us

488 489

an

490 491 492

ip t

Cat.I

Table 18.Payback period of 24 h schedule categorized by comfort categories and PCM solutions.

2.70

2.24

Cat.II

2.57

494 495 496 497 498 499 500 501 502 503 504 505

2.16

1.73

2.17

2.22

1.81

2.08

1.69

2.20

2.32

1.93

2.11

1.74

2.55

2.18

2.25

1.90

2.37

Ac ce p

Cat.IV 2.70 493

1.75

te

Cat.III 2.58

2.19

d

Cat.I

M

[years] P23-10 P23-5 P25-10 P25-5 P27-10 P27-5

Office schedule

Table 19 presents the annual cooling consumption for an office prototype when PCM with three different melting point temperatures are integrated to maintain the thermal comfort. It can be seen that the cooling energy consumption dropped in all building prototypes with PCM incorporation. Additionally, it could be noted that in thermal comfort categories I and II, building models containing PCM with 25 °C melting point, yeilded the highest energy savings but in categories III and IV, PCM with melting point temperature of 27 °C consumed less energy than other building models. From Table 19 and Figure 13, it could be derived that despite noticeable effect of PCM on the cooling energy savings, an increase on the heating energy consumption under an office profile was registered in each case with PCM, which coincides with the results discussed by other researchers [30].

506 507 23 Page 23 of 38

508 509

Table 19.Cooling savings of office schedule categorized by comfort categories and PCM solutions. BC(kWh) P23-10 P23-5 P25-10 P25-5 P27-10 P27-5 2819

51%

45%

59%

58%

54%

54%

Cat.II

2440

55%

47%

67%

64%

66%

66%

Cat.III 2203

57%

49%

71%

67%

74%

73%

Cat.IV 1870

60%

51%

75%

70%

82%

81%

cr

ip t

Cat.I

M

an

us

510

511

515 516 517 518 519 520 521 522 523 524 525 526

d te

514

Figure 13.Heating savings graph of office schedule categorized by comfort categories and PCM solutions.

A detailed analysis of the indoor air temperature and average inside surface temperature of all walls and roof of P23-10 model is presented for two winter days in Figure 14. According to this graph, before the system was turned on at 8 o'clock, the average PCM temperature in all walls and roof was below 7 °C and an indoor air temperature around 5 °C was registered because of cold outdoor temperature; and in that respect, when the HVAC system was turned on to condition the zone, high amounts of energy was required to warm up the zone air at occupants comfort level, which was set to 27 °C. On the other hand, a considerable amount of heat generated by the HVAC system was absorbed by the solidified PCM as latent heat which additionally imposes high heating demand. It can be seen that the energy that was stored in the PCM, especially when solar radiation was at its maximum, was discharged for heating purposes when the HVAC system was turned off (see Figure 15).

Ac ce p

512 513

24 Page 24 of 38

ip t cr us Figure 14.Average surface temperatures of all vertical walls & roof in P23-10 model, office schedule, Cat.I.

M

528 529

an

527

531 532 533

Ac ce p

te

d

530

Figure 15.Heat storage comparison of different PCMs for thermal comfort Cat.I (10th of January).

534 535 536 537 538 539 540

The same trends existed for PCMs with 25 °C and 27 °C melting temperature; however, they showed lower energy demand in comparison to PCM with 23 °C melting temperature because their melting point temperature was closer to Fanger control thermostat set points. Also, it was found that when the thickness of PCM layer was reduced, annual energy performance in all cases was improved because during the heating season, when sunshine period is shorter, heat penetration into PCM layer increases by decrease of the PCM mass which correspondingly 25 Page 25 of 38

541 542 543

increases the melting process [76]. Eventually, the highest annual energy savings were achieved when PCM with 27 °C melting point and 5 mm thickness was incorporated, (see Table 20) which subsequently led to payback periods as shown in Table 21.

544 Table 20.Annual total energy savings of office schedule categorized by comfort categories and PCM solutions.

ip t

545 546

BC(kWh) P23-10 P23-5 P25-10 P25-5 P27-10 P27-5 9079

-3%

0%

3%

8%

3%

9%

Cat.II

7893

0%

4%

6%

12%

6%

13%

Cat.III 7137

2%

6%

7%

12%

8%

14%

Cat.IV 6067

3%

7%

8%

13%

10%

16%

M

[year P23s] 10

P23- P255 10

Cat.I -

-

51.54 8.71

64.41 8.02

26.3 2

21.98 7.08

22.43 6.47

Cat.I 132.3 17.5 II 9 1

20.56 7.27

17.99 6.21

Cat.I 16.1 64.91 V 9

21.05 8.23

16.04 6.38

551 552 553 554 555 556 557

Ac ce p

te

Cat.I I

550

us

Table 21.Payback period of office schedule categorized by comfort categories and PCM solutions. P25- P275 10

d

548 549

an

547

cr

Cat.I

P275

Residential schedule

Table 22 presents the cooling energy savings of the PCM incorporated models for a generic residential model. As follows from the results, in all building models, PCMs yielded savings for cooling energy consumption especially in P27-10 models. This is justified because PCM with higher melting point temperature can properly absorb the outdoor high temperature and reduce the indoor air temperature fluctuations.

558

26 Page 26 of 38

Table 22.Cooling savings of residential sch categorized by comfort categories and PCM solutions. P23- P255 10

P25- P275 10

P275

Cat.I 4200

15%

12% 33%

28% 43%

36%

Cat.I 3592 I

18%

13% 37%

31% 54%

46%

Cat.I 3218 II

21%

14% 39%

32% 59%

50%

Cat.I 2697 V

24%

16% 42%

34% 66%

55%

574 575 576

cr

M

d

te

573

Furthermore, it can be noticed that the energy savings increase by thermal comfort decrease, hence, the thermal comfort level should always be selected based on the building profile and occupants need. For the heating energy consumption, a similar trend as for the 24 h models was observed for all PCM incorporated models and in all comfort stages. The payback period of the building models with residential schedule are listed in Table 23. Simulation results indicated that PCM with 27 °C melting point and 10 mm thickness could properly save energy, nevertheless, a better payback period was observed for models with 24 h thermostat operation than those with residential thermostat operation. This fact was for the sake of a greater energy savings in 24 h schedule, because in residential schedule, HVAC energy-saving benefits due to the incorporation of PCM was not considered from 8:00 h to 16:00 h (during sunshine period) since the air-conditioning system was turned off during that period.

Ac ce p

562 563 564 565 566 567 568 569 570 571 572

an

561

ip t

P2310

BC(kWh)

us

559 560

Table 23.Payback period of residential schedule categorized by comfort categories and PCM solutions. [year P23s] 10

P23- P255 10

P25- P275 10

P275

Cat.I 5.92

4.28

3.94

3.13

3.55

2.96

Cat.I 4.65 I

3.70

3.78

3.10

3.25

2.76

Cat.I 4.35 II

3.59

3.81

3.21

3.22

2.79

Cat.I 4.20 V

3.66

3.97

3.52

3.32

2.99

27 Page 27 of 38

577 578

Impacts of occupants clothing on the energy performance

579

ip t

Energy savings resulting from the occupants behavior are shown in Table 24. Comparison of annual energy consumption for the residential building models with fixed and variable clothing insulation in winter showed 4 to 6 % energy savings and about 170 to 180 Euros energy cost savings. It should be noted that only the energy savings resulting from occupants clothing in winter was accounted in the annual energy performance, and the clothing habitude for summer was maintained constant (0.5 Clo).

cr

580 581 582 583 584 585

Table 24.Annual energy performance due to occupants clothing–Residential schedule Cat.II. Energy savings [kWh/year]

Energy savings [%/year]

Saving bill [€]

P23-10

1296.7

5.4%

182.4

P25-10

1293.1

P27-10

1295.7

P23-5

1256.8

P25-5

1258.7

589 590 591 592 593 594 595

M d

1260.2

5.5%

181.9

5.6%

182.3

5.2%

176.8

5.3%

177.0

5.3%

177.3

Ac ce p

P27-5

an

Building models

te

587 588

us

586

Summary

In summary, a methodology based on the Fanger thermal comfort control was applied to control the HVAC operation of the PCM incorporated buildings. Furthermore, the consequences of different HVAC operation on the effectiveness of PCM for energy savings and the resulted payback period were studied. Additionally, the impacts of the occupants clothing behavior on

the energy savings were investigated.

596 597 598 599 600 601 602

In this regard, when 24 h HVAC schedule applied, in all thermal comfort categories PCM with melting temperature at 27°C achieved the highest annual energy savings, around 10-15%, while these savings were limited to 10-13% and 8-10% for PCMs with 25 °C and 23 °C melting point, respectively. In addition, higher energy savings and lower payback periods were achieved for cases with 10 mm PCM layer. Moreover, the use of PCM under this operational schedule provided benefits during both winter and summer periods.

603 28 Page 28 of 38

604 605 606

It is noteworthy that, the energy performance data obtained from the residential profile was broadly consistent with the major trends already mentioned in the case of 24 h HVAC schedule. However, the annual energy savings for the 24 h cases were higher than the residential building.

607

ip t

Summing up the results from the office schedule, it could be concluded that the application of PCM had a significant effect on the cooling energy savings in all cases with PCM. The authors want to highlight that during the heating period, the energy consumption increased when PCM applied to the basecase model. In all thermal comfort categories, adding PCM resulted in an increase in the energy consumption of building models which was considerable in prototypes with PCM of 23 °C melting point.

cr

608 609 610 611 612 613

Moreover, as expected, higher thermal comfort requirement led to higher energy consumption, nonetheless, it was shown that integration of PCM could effectively reduce the extensive energy consumption resulted in from high comfort expectation.

an

615 616 617

us

614

618

This paper also includes a payback cost analysis when PCM is incorporated into the building envelopes as a passive system. The PCM with higher melting point showed better payback periods in years.

M

619 620 621

627

te

Also, it is of interest to note that the payback periods in all cases of 24-hour and residential schedules are very short and they are less than 2 years for the 24-hour and shorter than 3 years for the residential profile. In the case of office schedule however, the best payback period corresponds to P27-5 and P25-5 models with 6 to 8 years of payback period.

Ac ce p

623 624 625 626

d

622

628 629 630

In addition, the effect of occupants clothing on the annual energy savings was investigated. Energy savings and economic benefits were improved further when the occupants wore warmer clothes in the evening and at night-time in winter.

631

Conclusions

632 633 634 635 636 637 638

Integration of PCM under 24 h and residential operational schedules provided energy savings during both winter and summer periods. Additionally, in all thermal comfort categories PCM with 27 °C melting point temperature achieved the highest annual energy savings. In addition, greater energy savings and payback periods were recorded when PCM with 10 mm layer thickness was used. Furthermore, annual energy savings for 24 h schedule were higher than residential schedule.

639

29 Page 29 of 38

640 641 642 643

In office operational schedule remarkable cooling energy savings were observed in all cases with PCM, however, during the heating period, the energy consumption increased when PCM was applied to the basecase model. Moreover, for this building profile the best annual energy savings corresponded to the models with 5 mm layer of 27 °C melting point PCM.

644 In Madrid climate zone, PCM with 27 ºC achieved higher energy savings in summer (cooling period) whereas PCM with 23 ºC was most effective in winter (heating period).

ip t

645 646

Short payback periods in years achieved for 24 h and residential profiles with less than 2 and 3 years, respectively, and about 6 years for the office profile.

us

648 649

cr

647

650

Simulating the occupants clothing behavior, it was shown that when the occupants of a residential building change their clothing habitude by wearing slightly warmer clothes in winter period the energy savings and the payback period were improved.

an

651 652 653 654

Acknowledgements

656 657 658 659 660 661 662 663

The work partially funded by the Spanish government (ENE2011-22722). The authors would like to thank the Catalan Government for the quality accreditation given to their research group (2014 SGR 123). The research leading to these results has received funding from the European Union's Seventh Framework Program (FP7/2007-2013) under grant agreement n° PIRSES-GA-2013-610692 (INNOSTORAGE). Alvaro de Gracia would like to thank Education Ministry of Chile for Grant PMI ANT 1201.

665

d

te

Svetlana Ushak acknowledges to CONICYT/FONDAP Nº 15110019 SERC-Chile, and PMI ANT 1201 for the financial support.

Ac ce p

664

M

655

666

References

667 668

[1] The European Union, Climate action, Eur. Union Explain. Clim. Action. (2013). doi:10.2775/84713.

669 670 671

[2] IEA, Energy Technology Perspectives 2012 Pathways to a Clean Energy System, 2012. doi:10.1787/energy_tech-2012-en.

672

30 Page 30 of 38

673 674 675

[3] Directive 2010/30/EU of the European Parliament and of the Council on the indication by labelling and standard product information of the consumption of energy and other resources by energy-related products, 2010.

676 [4] International Energy Agency, Energy Technology Perspectives 2012 Pathways to a Clean Energy System, n.d. doi:10.1787/energy_tech-2012-en.

ip t

677 678 679

[5] The European Union explained: Energy, Sustainable, secure and affordable energy for Europeans, Eur. Comm. Energy. (2014). doi:10.2775/65322.

cr

680 681

[6] I. Nolte, D. Strong, Europe’s buildings under the microscope-A country-by-country review of the energy performance of buildings, Buildings Performance Institute Europe (BPIE) Copyright, 2011.

an

683 684 685

us

682

686

[7] International Energy Agency, Tracking Clean Energy Progress 2014, (2014) 84. http://www.iea.org/publications/freepublications/publication/Tracking_clean_energy_progress_ 2014.pdf.

M

687 688 689

694 695 696 697 698 699 700 701 702 703

te

693

[8] International Energy Agency, Technology Roadmap:Energy efficient building envelopes, Oecd. (2013).

Ac ce p

691 692

d

690

[9] C. Barreneche, M.E. Navarro, a. I. Fernández, L.F. Cabeza, Improvement of the thermal inertia of building materials incorporating PCM. Evaluation in the macroscale, Appl. Energy. 109 (2013) 428–432. doi:10.1016/j.apenergy.2012.12.055.

[10] L.F. Cabeza, I. Martorell, L. Miró, A.I. Fernández, C. Barreneche, Introduction to thermal energy storage (TES) systems, in: L.F. Cabeza (Ed.), Adv. Therm. Energy Storage Syst., Elsevier, 2015: pp. 1–28. doi:10.1533/9781782420965.1.

[11] K. Pielichowska, K. Pielichowski, Phase change materials for thermal energy storage, Prog. Mater. Sci. 65 (2014) 67–123. doi:10.1016/j.pmatsci.2014.03.005.

704 705 706 707

[12] P. Tatsidjodoung, N. Le Pierrès, L. Luo, A review of potential materials for thermal energy storage in building applications, Renew. Sustain. Energy Rev. 18 (2013) 327–349. doi:10.1016/j.rser.2012.10.025. 31 Page 31 of 38

708 709 710 711

[13] P. Arce, M. Medrano, A. Gil, E. Oró, L.F. Cabeza, Overview of thermal energy storage (TES) potential energy savings and climate change mitigation in Spain and Europe, Appl. Energy. 88 (2011) 2764–2774. doi:10.1016/j.apenergy.2011.01.067.

713 714

ip t

712 [14] S. Wu, Materials for Energy Efficiency and Thermal Comfort in Buildings, Elsevier, 2010. doi:10.1533/9781845699277.1.101.

[15] G. Evola, L. Marletta, F. Sicurella, A methodology for investigating the effectiveness of PCM wallboards for summer thermal comfort in buildings, Build. Environ. 59 (2013) 517–527. doi:10.1016/j.buildenv.2012.09.021.

us

716 717 718

cr

715

719

[16] A.M. Khudhair, M.M. Farid, A review on energy conservation in building applications with thermal storage by latent heat using phase change materials, Energy Convers. Manag. 45 (2004) 263–275. doi:10.1016/S0196-8904(03)00131-6.

an

720 721 722

728 729 730 731 732 733 734 735 736

d

te

727

[17] L.F. Cabeza, a. Castell, C. Barreneche, a. de Gracia, a. I. Fernández, Materials used as PCM in thermal energy storage in buildings: A review, Renew. Sustain. Energy Rev. 15 (2011) 1675–1695. doi:10.1016/j.rser.2010.11.018.

[18] M.M. Farid, A. Sherrif, Materials for Energy Efficiency and Thermal Comfort in Buildings, Elsevier, 2010. doi:10.1533/9781845699277.2.384.

Ac ce p

724 725 726

M

723

[19] R. Vicente, T. Silva, Brick masonry walls with PCM macrocapsules: An experimental approach, Appl. Therm. Eng. 67 (2014) 24–34. doi:10.1016/j.applthermaleng.2014.02.069.

[20] P. Moreno, C. Solé, A. Castell, L.F. Cabeza, The use of phase change materials in domestic heat pump and air-conditioning systems for short term storage: A review, Renew. Sustain. Energy Rev. 39 (2014) 1–13. doi:10.1016/j.rser.2014.07.062.

737 738 739 740

[21] L.F. Cabeza, A. Castell, C. Barreneche, A. De Gracia, A.I. Fernández, Materials used as PCM in thermal energy storage in buildings: A review, Renew. Sustain. Energy Rev. 15 (2011) 1675–1695. doi:10.1016/j.rser.2010.11.018.

741

32 Page 32 of 38

742 743 744

[22] B. Zalba, J.M. Marın, L.F. Cabeza, H. Mehling, Review on thermal energy storage with phase change: materials, heat transfer analysis and applications, 2003. doi:10.1016/S13594311(02)00192-8.

745 [23] V.V. Tyagi, D. Buddhi, PCM thermal storage in buildings: A state of art, Renew. Sustain. Energy Rev. 11 (2007) 1146–1166. doi:10.1016/j.rser.2005.10.002.

ip t

746 747 748

cr

[24] R. Baetens, B.P. Jelle, A. Gustavsen, Phase change materials for building applications: A state-of-the-art review, Energy Build. 42 (2010) 1361–1368. doi:10.1016/j.enbuild.2010.03.026.

us

749 750 751 752

[25] F. Kuznik, D. David, K. Johannes, J.-J. Roux, A review on phase change materials integrated in building walls, Renew. Sustain. Energy Rev. 15 (2011) 379–391. doi:10.1016/j.rser.2010.08.019.

an

753 754 755 756

764 765 766 767 768 769 770

M

d

761 762 763

[27] N. Soares, J.J. Costa, a. R. Gaspar, P. Santos, Review of passive PCM latent heat thermal energy storage systems towards buildings’ energy efficiency, Energy Build. 59 (2013) 82–103. doi:10.1016/j.enbuild.2012.12.042.

te

760

[26] M. Pomianowski, P. Heiselberg, Y. Zhang, Review of thermal energy storage technologies based on PCM application in buildings, Energy Build. 67 (2013) 56–69. doi:10.1016/j.enbuild.2013.08.006.

Ac ce p

757 758 759

[28] S.A. Memon, Phase change materials integrated in building walls: A state of the art review, Renew. Sustain. Energy Rev. 31 (2014) 870–906. doi:10.1016/j.rser.2013.12.042.

[29] N. Soares, a. R. Gaspar, P. Santos, J.J. Costa, Multi-dimensional optimization of the incorporation of PCM-drywalls in lightweight steel-framed residential buildings in different climates, Energy Build. 70 (2014) 411–421. doi:10.1016/j.enbuild.2013.11.072.

771 772 773

[30] Y.-B. Seong, J.-H. Lim, Energy Saving Potentials of Phase Change Materials Applied to Lightweight Building Envelopes, Energies. 6 (2013) 5219–5230. doi:10.3390/en6105219.

774

33 Page 33 of 38

775 776 777

[31] G. Evola, L. Marletta, F. Sicurella, Simulation of a ventilated cavity to enhance the effectiveness of PCM wallboards for summer thermal comfort in buildings, Energy Build. 70 (2014) 480–489. doi:10.1016/j.enbuild.2013.11.089.

778 [32] J. Kośny, A. Fallahi, N. Shukla, E. Kossecka, R. Ahbari, Thermal load mitigation and passive cooling in residential attics containing PCM-enhanced insulations, Sol. Energy. 108 (2014) 164–177. doi:10.1016/j.solener.2014.05.007.

ip t

779 780 781

[33] J.S. Sage-Lauck, D.J. Sailor, Evaluation of phase change materials for improving thermal comfort in a super-insulated residential building, Energy Build. 79 (2014) 32–40. doi:10.1016/j.enbuild.2014.04.028.

us

783 784 785

cr

782

786

[34] M. Alam, H. Jamil, J. Sanjayan, J. Wilson, Energy saving potential of phase change materials in major Australian cities, Energy Build. 78 (2014) 192–201. doi:10.1016/j.enbuild.2014.04.027.

an

787 788 789

795 796 797 798 799 800 801 802 803

d te

794

[35] US Department of Energy, EnergyPlus, Energy Effic. Renew. Energy. (2014). http://apps1.eere.energy.gov/buildings/energyplus/energyplus_about.cfm (accessed November 4, 2014).

[36] D. Bradley, M. Kummert, New evolutions in TRNSYS – A selection of version 16 features, in: Ninth Int. IBPSA Conf., 2005: pp. 107–114.

Ac ce p

791 792 793

M

790

[37] U. Stritih, Heat transfer enhancement in latent heat thermal storage system for buildings, Energy Build. 35 (2003) 1097–1104. doi:10.1016/j.enbuild.2003.07.001.

[38] F. Kuznik, J. Virgone, K. Johannes, Development and validation of a new TRNSYS type for the simulation of external building walls containing PCM, Energy Build. 42 (2010) 1004–1009. doi:10.1016/j.enbuild.2010.01.012.

804 805 806

[39] D. Heim, J. a Clarke, Numerical modelling and thermal simulation of PCM–gypsum composites with ESP-r, Energy Build. 36 (2004) 795–805. doi:10.1016/j.enbuild.2004.01.004.

807

34 Page 34 of 38

808 809 810

[40] P. Schossig, H.M. Henning, S. Gschwander, T. Haussmann, Micro-encapsulated phasechange materials integrated into construction materials, in: Sol. Energy Mater. Sol. Cells, 2005: pp. 297–306. doi:10.1016/j.solmat.2005.01.017.

812 813

[41] ESP-r, Multi-platform Building Energy Software Tool, (2015). http://www.esru.strath.ac.uk/ (accessed March 30, 2015).

814

[42] ANSI/ASHRAE Standard 55-2013, ANSI/ASHRAE Standard 55-2013 Thermal Environmental Conditions for Human Occupancy, 2013. www.ashrae.org.

cr

815 816

us

817

[43] BS EN 15251:2007, Indoor environmental input parameters for design and assessment of energy performance of buildings- addressing indoor air quality , thermal environment , lighting and acoustics Contents, (2007) 1–52.

an

818 819 820 821

[44] B. Urban, C. Gomez, A Case for Thermostat User Models, in: 13th Conf. Int. Build. Perform. Simul. Assoc., Chambéry, 2013: pp. 1483–1490. http://www.ibpsa.org/proceedings/BS2013/p_2337.pdf.

M

822 823 824

830 831 832 833 834 835 836

te

[45] K. Lee, S. Schiavon, Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort, Energies. 7 (2014) 1917–1934. doi:10.3390/en7041917.

Ac ce p

829

d

825 826 827 828

ip t

811

[46] D.H. Kang, P.H. Mo, D.H. Choi, S.Y. Song, M.S. Yeo, K.W. Kim, Effect of MRT variation on the energy consumption in a PMV-controlled office, Build. Environ. 45 (2010) 1914–1922. doi:10.1016/j.buildenv.2010.02.020.

[47] R.-L. Hwang, S.-Y. Shu, Building envelope regulations on thermal comfort in glass facade buildings and energy-saving potential for PMV-based comfort control, Build. Environ. 46 (2011) 824–834. doi:10.1016/j.buildenv.2010.10.009.

837 838 839 840

[48] X. Fang, M. V Bianchi, C. Christensen, Monetization of Thermal Comfort in Residential Buildings Comfort Model Description, Natl. Renew. Energy Laboraory. (2012) 64– 75.

841

35 Page 35 of 38

842 843

[49] EnergyPlus Input Output Reference: The Encyclopedic Reference to EnergyPlus Input and Output, (2014).

844 [50] P.C. Tabares-velasco, C. Christensen, M. Bianchi, C. Booten, Verification and Validation of EnergyPlus Conduction Finite Difference and Phase Change Material Models for Opaque Wall Assemblies, (2012).

ip t

845 846 847 848

cr

[51] P.C. Tabares-Velasco, C. Christensen, M. Bianchi, Verification and validation of EnergyPlus phase change material model for opaque wall assemblies, Build. Environ. 54 (2012) 186–196. doi:10.1016/j.buildenv.2012.02.019.

us

849 850 851 852

[52] M. Tabares-Velasco, P.C Christensen, C Bianchi, Validation Methodology to Allow Simulated Peak Reduction and Energy Performance Analysis of Residential Building Envelope with Phase Change Materials, in: 2012 ASHRAE Annu. Conf. June 23-27, National Renewable Energy Laboratory, San Antonio, Texas, 2012. http://www.ntis.gov/help/ordermethods.aspx.

an

853 854 855 856

864 865 866 867 868 869 870

d

861 862 863

[54] P.W. Egolf, H. Manz, Theory and modeling of phase change materials with and without mushy regions, Int. J. Heat Mass Transf. 37 (1994) 2917–2924. doi:10.1016/00179310(94)90346-8.

te

860

[53] F. Kuznik, J. Virgone, Experimental assessment of a phase change material for wall building use, Appl. Energy. 86 (2009) 2038–2046. doi:10.1016/j.apenergy.2009.01.004.

Ac ce p

858 859

M

857

[55] Helmut E.Feustel, Simplified Numerical Description of Latent Storage Characteristics for Phase Change Wallboard, Indoor Environment Program,Energy and Environment Division,Lawrence Berkeley Laboratory,University of California, California, 1995.

[56] RUBITHERM, Rubitherm Technologies GmbH, (2014). http://www.rubitherm.de/ (accessed October 1, 2014).

871 872 873

[57] ASHRAE, ANSI/ASHRAE Standard 140-2011 Standard Method of Testing for the Evaluation of Building Energy Analysis Computer Programs, 2011.

874

36 Page 36 of 38

875 876 877

[58] RUBITHERM GmbH - CSM modules, (n.d.). http://www.rubitherm.de/english/pages/02h_air_heating_systems.htm (accessed September 16, 2015).

878 [59] M. Kottek, J. Grieser, C. Beck, B. Rudolf, F. Rubel, World map of the Köppen-Geiger climate classification updated, Meteorol. Zeitschrift. 15 (2006) 259–263. doi:10.1127/09412948/2006/0130.

ip t

879 880 881

[60] Climate Consultant, (2015). http://www.energy-design-tools.aud.ucla.edu/climateconsultant/request-climate-consultant.php (accessed October 2, 2015).

us

883 884

cr

882

885

[61] Instruction guidelines for RUBITHERM CSM panels, (n.d.). http://www.rubitherm.de/english/download/Bedienungsanleitung CSM_130517.pdf (accessed September 16, 2015).

an

886 887 888 889

[62] EnergyPlus Engineering Reference, EnergyPlus Engineering Reference: The Reference to EnergyPlus Calculations, US Dep. Energy. (2014) 1444.

M

890 891

896 897 898 899 900 901 902 903 904 905

te

895

[63] EnergyPlus Testing Suite, EnergyPlus Testing with Building Thermal Envelope and Fabric Load Tests from ANSI / ASHRAE Standard 140-2011, (2013).

Ac ce p

893 894

d

892

[64] Levermore.G.J, Building Energy Management Systems: An Application to Heating, Natural Ventilation, Lighting and Occupant Satisfaction, 2nd ed., Taylor & Francis, 2000.

[65] EN ISO 7730, ISO 7730: Ergonomics of the thermal environment Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria, Management. 3 (2005) 605–615. doi:10.1016/j.soildyn.2004.11.005.

[66] K. E. Charles, Fanger ’ s Thermal Comfort and Draught Models IRC Research Report RR-162, 2003.

906 907 908

[67] P.O. Fanger, Thermal comfort: Analysis and applications in environmental engineering, Copenhagen,Denmark, 1970.

909 37 Page 37 of 38

910 911

[68] G. Fanger, P. O., & Langklide, Interindividual differences in ambient temperatures preferred by seated persons, ASHRAE Trans. (1975) 140–147.

912 [69] D. Clements-Croome, Creating the Productive Workplace, E&FN Spon, Taylor Fr. Group,London/New York. (2006).

ip t

913 914 915

[70] T. Hong, H. Lin, Occupant Behavior : Impact on Energy Use of Private Offices, Asim IBSPA Asia Conf. (2012).

cr

916 917 918

[71] ITeC - Instituto de Tecnología de la Construcción de Cataluña-Construction Technology Institute of Catalunya, (2015). www.itec.es (accessed October 1, 2015).

us

919 920

922 923

an

921

[72] Gas Natural Fenosa, (2015). http://www.gasnaturalfenosa.es/es/1285340339971/hogar.html (accessed April 1, 2015).

932 933 934 935 936 937 938 939 940

d

928 929 930 931

[74] M. Leach, C. Lobato, A. Hirsch, S. Pless, P. Torcellini, Technical Support Document : Strategies for 50 % Energy Savings in Large Office Buildings Technical Support Document : Strategies for 50 % Energy Savings in Large Office Buildings, National Renewable Energy Laboratory,NREL/TP-550-49213, 2010.

te

927

[73] Luz, gas y servicios energéticos-Endesa Online, (2015). http://www.endesaonline.com/ES/Hogares/ (accessed April 1, 2015).

Ac ce p

925 926

M

924

[75] B.A. Thornton, W. Wang, M.D. Lane, M.I. Rosenberg, B. Liu, Technical Support Document : 50 % Energy Savings Design Technology Packages for Medium Office Buildings, Richland, WA:Pacific Northwest National Laboratory, 2009.

[76] F. Ascione, N. Bianco, R.F. De Masi, F. de’ Rossi, G.P. Vanoli, Energy refurbishment of existing buildings through the use of phase change materials: Energy savings and indoor comfort in the cooling season, Appl. Energy. 113 (2014) 990–1007. doi:10.1016/j.apenergy.2013.08.045.

941

38 Page 38 of 38