Enb Ibecc Adaptaiton and Ecbc

8/12/2019 Enb Ibecc Adaptaiton and Ecbc

1/20

COMBINED EFFECT OF ENERGY EFFICIENCY MEASURES

AND THERMAL ADAPTATION ON AIR CONDITIONED

BUILDING IN WARM CLIMATIC CONDITIONS OF INDIA

by

Shivraj Dhaka, Jyotirmay Mathur, Vishal Garg

Report No: IIIT/TR/2012/-1

Centre for IT in Building ScienceInternational Institute of Information Technology

Hyderabad - 500 032, INDIASeptember 2012


2/20

1

COMBINED EFFECT OF ENERGY EFFICIENCY MEASURES ANDTHERMAL ADAPTATION ON AIR CONDITIONED BUILDING IN WARM

CLIMATIC CONDITIONS OF INDIAShivraj Dhaka 1, Jyotirmay Mathur 1*, Vishal Garg 2

1Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur,India

2Centre for IT in Building Science, International Institute of Information Technology,Hyderabad, India

AbstractThis study evaluates improvement in energy efficiency of an air conditioned building blockemploying energy conservation measures (ECMs) recommended by Indian EnergyConservation Building Code -2007 (ECBC) through prescriptive route. First part, evaluatesenergy savings by implementing five ECMs of envelope independently and two combinationsof ECMs keeping constant thermostat setting throughout the year. In second part of the studysame ECMs are considered to the subject building model allowing thermostat settings as perthermal adaptation resulting from change in outdoor temperature. Actual measurements weretaken and simulation model was finetuned. Annual energy consumption of building is used toevaluate the effect of individual ECMs and their combinations on both part of the study, i.e.fixed thermostat and adaptive thermostat settings. The simulation result shows that togetherwith combination of all ECMs recommended by ECBC, small buildings can save up to 40%energy consumption as compared to buildings built with conventionally practicedspecifications of India. Effect of thermal adaptation itself offers up to 16% energy savingopportunity in small buildings considering adaptive thermostat settings. The potential ofenergy conservation through ECMs suggested by ECBC and adaptive set point getssignificantly reduced for large size buildings having high internal heat gains.

Key words : Building Code; Energy Efficiency Measure; Energy Efficiency; ThermalAdaptation

NomenclatureECBC Energy Conservation Building Code LPD Lighting Power Density (W/m 2)ECM Energy Conservation Measure T mmo , T o Mean monthly outdoor dry bulb temperate (

oC)EPD Equipment Power Density (W/ m ) Tn Neutral/ comfort temperature, ( oC)

1. IntroductionAn efficient building envelope with appropriate design consideration can reduce energyconsumption and downsize the heating ventilation and air conditioning (HVAC) system. It isthe interface between indoor and outdoor conditions. In warm climatic conditions, preventionof heat gain through envelope is the best way to conserve energy, therefore building envelopeshould be climate responsive.

*Corresponding author: Dr.-Ing Jyotirmay Mathur, Head-Centre for Energy and Environment MNIT Jaipur,Tel: +91-141-2713211; E-mail: [email protected]


3/20

2

Energy consumption in building sector is continuously increasing all around the world;Synnefa et al. concluded that nearly 60% of the net electricity consumption in the OECD(Organisation for Economic Co-operation and Development) economies is from the buildingsector [1]. This sector represents about 33% of electricity consumption in India, with

commercial sector and residential sector accounting for 8% and 25% respectively. It isestimated that ECBC compliant buildings may consume about 40% less energy thanconventional practiced buildings in India and nationwide enforcement of the building codecould result in annual saving of 1.7 billion kWh units [2]. In the residential sector, buildingsize and its location are the key factors for energy consumption as small buildings or flatsneed less energy as there is less conditioned and transfer area, and also less occupancy. Theamount and type of energy used in building is mainly due to variation related to weather,architectural design, and envelope features such as wall, roof, and glazing. These factorsaffect energy consumption of buildings a lot. Chirarattananona et al.conducted study attropical climate of Thailand revealed that insulation of wall decrease the cooling coil loadfrom 83.0 to 44.1 kWh/m 2/yr [3] whereas similar type of study carried out at hot & humidclimate of Dubai (UAE) demonstrated 30% energy saving by wall insulation [4].Reflectivity of roof has become important factor in warm climatic conditions being easy andinexpensive measure to conserve energy as well as to improve thermal comfort conations.Synnefa et al. demonstrated that increasing roof reflectivity from 0.3 to 0.5 decreases energyconsumption by 15% to 30% in hot climate [1] whereas Bhatia et al. conducted study at amulti storey learning center of Hyderabad to examine the effect of reflective roof on coolingenergy as well as building energy consumption in composite climate of India. It revealed thatwhite coating reduce total building energy consumption by 5% [5]. Cooling and heating

requirement caused by residential roof accounts for about 4% of the whole building envelopeand 20% of the top floor in hot summer and cold winter [6-7]. Energy efficient glazing canreduce the energy consumption and CO 2 emissions by 25% and 7.1% respectively [8]. Roofis responsible for dominant heat gain and it is predicted that insulation over roof providemaximum energy savings compare to other envelope measures whereas South oriented wallgives least energy savings in warm climate [9-11]. Thus, building envelope affects heat gainand also plays important role in selection of air conditioning system. ASHRAE 90.1-2007suggested climate based envelope specification to improve energy efficiency of buildingsalthough it is not considered in this study [12]. This study is aimed to use envelopespecification of ECBC to evaluate energy efficiency in different warm climatic conditions ofthe country.Many researchers such as Humphreys, de Dear, Nicol, Brager, etc. conducted field studiesand concluded that occupants feel thermally comfortable at high elevated temperature whichis beyond the thermal comfort conditions defined by ASHRAE 55-2004 [13]. This is due to

physiological, psychological, and behavioural adaptation of occupants. Approach of adaptivethermal comfort also offers energy conservation in buildings. Field study carried out atnaturally ventilated building concluded that occupants perceive thermally comfortable up to30oC without much ventilation [14]. Mui and Chan demonstrated that with the integration ofadaptive comfort temperature (ACT) model about 7% energy could be saved in office

buildings [15]. Similar type of study carried out at Thailand demonstrated that every increasein set point by 1 oC (from 22 to 28 oC) gives a mean energy saving of about 6.14% [16].


4/20

3

Pioneers researchers Auliciems and de Dear carried out field research and proposed comforttemperature equation, T n = 0.31T o + 17.6 for conditioned and non-air-conditioned buildings[17]. Above equation is used in this study to work out neutral temperature for three warmclimatic conditions of India. Then, this monthly varying neutral temperature is used as

thermostat of the air conditioner. Based on review, it is clear that insulation of roof givesmaximum energy saving in warm climates and use of adaptive concept with this measurewould result in significant energy conservation.The purpose of study is to quantify energy saving potential considering envelope measures ofECBC initially keeping fixed set point, and then by varying it as per thermal adaptationapproach. The effect of thermal adaptation is evaluated in three representative cities locatedin hot & dry, warm & humid, and composite climatic zones of India.2. Methodology2.1. Site and building block The study has been conducted at institutes hostel building at Hyderabad (17.45 o, 78.47 o, and545m above sea level). The city has high temperature during summer, cold winter, and lowhumidity in summer but high during rain, and high solar radiation in all the seasons exceptrainy season. The summer mid day high and winter night low temperature is about 45 oC and4oC respectively. Hot as well as cold wind blows during summer and winter time, cold strongwind during rain and hazy sky occasionally. The mean monthly outdoor dry bulb temperaturevaries from 20 to 35 oC. City has been considered under composite climate of India.Top floor hostel room of w ing D of old boys hostel (OBH) has been chosen for this study.Photograph A and B of Figure 1 shows the geographic location and elevation of analyzedhostel building. The investigated part of the building was six year old and it was built with

concrete roof and double brick wall with beam type heavy weight construction. Building wasconstructed in cross shaped (107x107m) structure to avail the effect of across ventilation toall wings of the building. Every room has one door facing to the corridor and windows on

both sides to provide cross ventilation. Transverse iron jail (X shaped) was put on corridorwall. Hostel had room size of 3.6x2.4m (room area 8.64m 2), floor to ceiling height of 3.2m(room volume 27.7m 2), window openings of 1.340.65m, window shade of 0.91x0.6m,opaque door of 1.98x1.0m, and a corridor of 1.35m wide to front side of the hostel roomswhich was used as walkway to the neighbouring rooms. Windows were quite ordinary andhad single clear glass of 0.006m thickness; each window had two glass panes and fourthermal breaks. Window glass panes were operable to outside in case of rear window andinside in case of corridor window. Iron frames were used for the construction of windows aswell as door. The U-value of glass was 5.8W/m 2-oC, and solar heat coefficient and directsolar transmission were 0.81 and 0.8 respectively. Table 1 illustrates the construction detailsof existing building block. Construction of hostel building was similar to conventionalconstruction practices of India. All the rooms had single occupancy and equipped with singlefan, a computer, and a fluorescent tube light. Internal load was not much affecting energyconsumption being less compare to ECBC compliant buildings.2.2. Temperature measurements Three parameters were recorded from the hostel room as roof inside and outside surface

temperature, and room air temperature. Minco S667 PT100/3 RTD sensors (time constant 1.3second) were installed at the centre of roof inside as well as outside to record surface


5/20

4

temperature. Campbell Scientific 108-L probe was used to record room air temperature.Photograph D and E of Figure 1 represents positioning and location of roof surfacetemperature and room air temperature probe respectively. The accuracy of the probe was0.2C over 0 to 70C temperature and time constant was 30 to 60 second at wind speed of

5m/s. This probe was suspended 1m below to the inside roof and about 0.75m away fromwall. Image C of Figure 1 shows data logger - Campbell Scienti fic CR1000 and connections.It was used to record temperature measurements at the interval of 30 second start from June26, 23:00pm to July 31, 23:00pm. Later on, measurements had been averaged out on hourly

basis to compare with the simulation outputs.

Table 1 Construction details of the building blockMaterial(Outer to inner layer)

RoofThickness (m)

Wallthickness (m)

Floorthickness (m)

Gypsum Plastering 0.0127 0.0127 0.0127

Sand and Gravel 0.0254 - 0.0254Concrete slab medium density 0.1016 - 0.1016Brick - 0.2032 -Gypsum Plastering 0.0127 0.0127 0.0127Cork tiles - - 0.06Assembly U-value (W/m / oC) 3.8 1.9 3.1

2.3. Simulation modelSimulation model of investigated part of the building was modeled in DesignBuilder (version2.100.25) by specifying all the information of actual building block such as azimuth angle,

envelope (wall, roof and glazing) properties, occupants schedule, lighting schedule, fanschedule, shading devices etc. Photograph F and G of Figure 1 shows the plan andaxonometric view of the building block. Simulation was carried out using EnergyPlus(version V4.0.0.024) building simulation program. Layer by layer construction (outside toinside) of wall as well as roof has been given in Fig.2.Actual measurements obtained from the building block were compared to simulation outputs.In order to find good congruence between measurements and corresponding simulationoutputs, a series of alterations were carried to the simulation model. Solar absorptance wasvaried from 0.1 to 0.25 in step of 0.05, thickness of sand and gravel (layer) was modifiedfrom 0.00635m to 0.0508m in step of 0.00635m and size of brick was altered from 0.23m to0.25m in step of 0.00635m. Mean bias error (MBE) and coefficient of variation root meansquare error C v(RMSE) was calculated using equation 2 to 5, during alterations to the

building model. These errors below 10% and 15 are considered as good congruence betweenmeasured and simulated parameters [5].

(equation 2)

Where: M is the measured value during the time interval, S is the simulated during the sametime interval. Root mean square error was calculated using equation 3.

(equation 3)

Here, N is the number of time intervals (720 hours) during monitoring period. The mean of


6/20

5

the measured data for the period is defined in equation 4.

(equation 4)

Following equation 5 was used to compute coefficient of variation root mean square error.Once the simulation model shows errors within permissible limits, this ensures further use ofsimulation model.

(equation 5)

2.4. Final simulation modelLater on, simulation model was changed from naturally ventilated building block into airconditioned building block model by specifying HVAC related inputs, infiltration, fanschedule etc. Simulation model was having a packaged type air conditioner unit of COP 3.1(average performance), a value recommended by ECBC. This simulation model was used asthe basic subject building model to examine the effect of envelope measures on energyconsumption firstly by keeping fixed thermostat and then adaptive thermostat settings.Energy consumption of this model was taken as the reference for calculation of energy savingwhich is referred by as is case in this study.

2.4.1. Control type Part 1: fixed thermostat controlThe thermostat setting of air conditioner was kept at 24 oC constant throughout the year, sinceit is a prevailing practice in India and then, seven envelope measures were used to evaluateenergy conservation in three warm climatic conditions.Part 2: monthly variable thermostat control (adaptive thermostat control settings) Under this part of the study thermostat of air conditioner was varied based on monthly

variation of outdoor temperature. The temperature at which occupants feel thermallycomfortable is a function of outdoor temperature and therefore thermostat of air conditionerwas varied as per the monthly varying neutral temperature reflecting thermal adaptation. Itwas calculated using Equation-1 as suggested by Auliciems and de Dear [17].Tn = 0.31T o + 17.6 (equation 1)Where-T n is the neutral/comfort temperature. Neutral temperature or comfortable temperatureis worked out through regression analysis of occupant s thermal sensation vote. Regressionline that intersect at neutral condition (0 condition) on thermal sensation scale is defined asneutral temperature and at this temperature majority of occupants feel thermal comfortable.

2.4.2. Energy conservation measuresThis study considers seven envelope measures to evaluate the energy efficiency of airconditioned building block. Five measures are recommended by ECBC and rest of the twomeasures have been chosen based on their performance such as combination ofECBC Glass + ECBC Roof, and ECBC case. Table 2 exhibits the details of recommendedmeasures by building code (ECBC) such as U-value for wall, roof, and glazing and SHGC ofglass, and reflectivity of roof in warm climates [18]. Table 3 shows the nomenclature ofenvelope measures used in this study. Envelope measure 7 is also termed as ECBC case andit follows all envelope measure recommended by ECBC.


7/20

6

Table 2 Recommended energy conservation measuresCool

Roof reflectance

Wall U-value(W/m 2-oC)

Roof U-value(W/m 2-oC)

Glass U-value(W/m 2-oC)

Solar Heat GainCoefficient (SHGC)

0.70 0.440 0.261 3.30 0.25

Similar analysis was carried out in three different warm climatic zones of India namelycomposite zone, hot & dry zone, and warm & humid zone represented by Hyderabad,Ahmedabad, and Chennai respectively.

Table 3 Nomenclature of recommended energy conservation measuresMeasures Nomenclature Name of energy conservation measureAs is case As is case Actual buildings case or existing case

ECM1 C R Cool RoofECM2 W ECBC wall

ECM 3 R ECBC RoofECM4 G S ECBC Glass SHGCECM5 G U ECBC Glass U-valueECM6 R S ECBC Glass SHGC + ECBC RoofECM7 E all ECBC Case (1+2+3+4+5)

2.5. Sensitivity analysis of buildings blockEffect of a particular envelope measure also depends upon building type, building envelope,internal load, occupancy schedule, type of air conditioning system, and operating conditionsetc, therefore it is required to carry out sensitivity analysis of employed ECMs. It has beencarried out considering large building area (square foot print of the building) and variation ininternal loads. It was carried out for the ECBC case only.The effect of adaptive set point has therefore, been examined for different cases of LightingPower Densities (LPD), and Equipment Power Densities (EPD), as presented in Table 9. Inorder to consider the variation in building size, that governs the role of building envelope inthe total cooling requirement, the analysis is further carried out in two parts; in the first part,only the building size was changed to observe the impact of change in the exposed surfacearea of building with respect to its volume. Size of the building block was increased from3.6x2.4 m (8.6m 2) to 40x40m (1600m 2). In the next variation, higher values of LPD and EPD

have been taken into consideration. The LPD was increased from 4W/m2 to 12 W/m

2 (as

suggested by ECBC for office buildings). The EPD was increased from 5W/m 2 to 20W/m 2 (asfound in IT offices).


8/20

7

Fig.1. Geographic location of hostel building (A), elevation of hostel building (B),positioning of sensor at roof surface (C), suspended room air temperature probe (D),CR 1000 data logger and connections of sensors (E), plan of simulation model (F), andaxonometric view of simulation model (G)

Fig.2. Layer by layer construction of roof and wall


9/20

8

3. Results 3.1. Temperature measurementsThe average temperature difference between measured and simulated roof inside surfacetemperature was observed 1.2 oC whereas this difference for room air was found 1.1 oC. It was

observed that simulation roof inside surface temperature and room air temperatures werefound in good congruence with the onsite measurements, this ensured to proceed for furtheranalysis. Fig.3 and Fig.4 shows the variation of simulated and measured temperatures.

Fig.3. Variation of simulated and measured room air temperature

Fig.4. Variation of simulated and measured roof inside surface temperature

3.2. Validation of simulation modelBased on hourly simulation outputs such as room air temperature and roof inside surfacetemperature, percentage Mean Bias Error (MBE) and Coefficient of Variation Root MeanSquare Error C V(RMSE) were calculated. These errors for roof inside surface temperatureand room air temperature were found less than 10% and 15 as shown in Table 4. Then, this


10/20

9

simulation model is called validated simulation model.

Table 4 MBE (%) and C v (RMSE), prior and post comparison of temperatureInside roof surface Temp Room air tempPriorcomparison

Postcomparison

Priorcomparison

Postcomparison

MBE (%) +14.09 + 4.06 +14.26 + 3.01CV(RMSE) 22.52 13.94 18.20 7.55

3.3. Energy efficiency in representative climatesEnergy efficiency of building block was improved by employing ECBC measuresconsidering fixed and adaptive control of thermostat. International Weather EnergyCalculation (IWEC) files were used to perform year round simulation of building block forAhmedabad and Chennai climatic locations. Indian Society of refrigerating and airconditioning engineers (ISHRAE) weather file was used for Hyderabad because ofunavailability of IWEC file for this city. Weather files had hourly data of solar radiation,outdoor temperature, relative humidity, wind velocity, sky conditions etc. Weather files werenot modified in this study. Table 5 shows the monthly variation of outdoor dry bulbtemperature and corresponding variation in neutral temperature in the representative cities ofwarm climatic conditions. The maximum neutral temperature was noted down as 28 oC in hotand dry climate. The maximum thermostat temperature difference was observed 4 oC in hotand dry climate and this difference could lead to significant energy savings.

Table 5 Monthly outdoor dry bulb temperature and neutral temperature

Month Hot and dry(Ahmedabad)

Warm andhumid (Chennai)

Composite(Hyderabad)

Tmmo Tn Tmmo Tn Tmmo Tn Jan 19.91 23.77 24.47 25.19 22.79 24.67Feb 22.33 24.52 26.02 25.67 25.19 25.41Mar 28.11 26.31 27.84 26.23 29.19 26.65Apr 31.48 27.36 30.05 26.92 31.71 27.43May 33.62 28.02 32.08 27.55 32.91 27.80Jun 33.17 27.88 31.01 27.21 28.59 26.46Jul 29.58 26.77 30.25 26.98 26.78 25.90

Aug 28.21 26.34 29.30 26.68 25.69 25.56Sept 28.86 26.55 29.02 26.59 26.19 25.72Oct 27.19 26.03 27.72 26.19 26.11 25.69

Nov 23.53 24.89 26.07 25.68 23.71 24.95Dec 20.56 23.97 24.80 25.29 21.74 24.34

3.3.1. Energy efficiency in composite climateHyderabad was chosen as representative city for composite climate while analyzing the effectof thermal adaptation, the cooling set point is varied on monthly basis as per the neutraltemperature that changes from 26.6 oC during March to 27.8 oC during the month of May. It isobserved that neutral temperature has significant difference with constant thermostat (24 oC)


11/20

10

as shown in Fig.5. The variation of temperature in this climate ranges from 4 to 43 oC andrelative humidity varies from 20 to 95% (dry period to wet period).

Fig.5. Monthly variation of neutral temperature and mean monthly outdoor dry bulbtemperature (Composite climate, Hyderabad)

Table 6 shows the annual energy consumption considering seven measures using fixed andadaptive set point for the HVAC system. Following assertions are noted from the results:

With ECM 7, i.e. combination of all individual ECMs termed as ECBC case, 40%energy could be saved over the common p ractice case i.e. the as is case.

Further, additional energy savings by about 15 to 19% could be achieved (maximumof 30kWh/m 2/yr) by using adaptive set point conditions.

The energy savings with various ECMs with adaptive set point approach are of thesame order as compared to the cases with fixed set point approach. This is evidentfrom comparison of Figure 6 and 7. This indicates that with adaptive set pointapproach, the suggested ECMs have nearly the same importance.

From Figure 6 & 7, it can be observed that in the ECBC case and with adaptiveapproach, the monthly variation of energy consumption reduces significantly, whereasin case of fixed set point conditions peak is very high as compared to rest of the

period.Fig.6 and Fig. 7 revealed that adaptive approach has large energy savings opportunities incomposite climate throughout the year. It is also evident that the maximum energy saving is

possible from March to June. ECBC case (ECM_all) shows the lowest energy consumptioncompare to other envelope measures.


12/20

11

Fig.6. Energy consumption in Hyderabad considering fixed set point conditions

Fig.7. Energy consumption in Hyderabad considering adaptive set point conditions

Table 6 Energy consumption at both set points conditions in composite climateAnnual Energy Saving in Case of Hyderabad

cases EnergyconsumptionFixed Set point

(kWh/m 2yr)

Energy consumptionAdaptive Set point(kWh/m 2yr)

Actual EnergySaving(kWh/m 2yr)

Percentagesaving(%)

As is case 177.89 149.34 28.54 16.04ECM_1 164.23 135.63 28.59 17.41ECM_2 142.52 117.12 25.39 17.82ECM_3 141.09 115.83 25.25 17.90ECM_4 156.01 125.99 30.01 19.24ECM_5 184.78 155.27 29.52 15.97

ECM_6 141.37 116.39 24.99 17.67ECBC case 105.69 89.20 16.49 15.60


13/20

12

3.3.2. Energy efficiency in hot and dry climateFor hot and dry climate, Ahmedabad was chosen as representative city. While analyzing theeffect of thermal adaptation, the cooling set point is varied on monthly basis as per neutraltemperature that changes from 26.3 oC during March to 28.02 oC during the month of May.

Figure 8 shows the variation of adaptive thermostat and constant thermostat. The variation ofmean monthly outdoor dry bulb temperature is large (20 to 38 oC) in this climate and relativehumidity varies from 25 to 40%.

Fig.8. Monthly variation of neutral temperature and mean monthly outdoor dry bulbtemperature (hot and dry climate, Ahmedabad)

It is observed that there is a significant difference between neutral temperature and constantthermostat compare to composite climate because of harsh summers and winters conditions.Table 7 shows the annual energy consumption per unit area considering each ECM usingfixed and adaptive set point for the HVAC system. Following conclusions are noted downfrom the results:

With ECM 7, i.e. combination of all individual ECMs (ECBC case), 43.1% energycould be saved over the common practice case i.e. the as is case.

Further, additional energy saving by about 15 to 19% could be achieved (maximum of

33kWh/m2/yr) by using adaptive set point condition. The effect of ECMs with adaptive set point approach is similar as compared to thefixed set point approach. This is evident from comparison of Figure 9 and 10.

From Figure 9 & 10, it can be observed that in ECBC case and with the adaptiveapproach, the monthly variation of energy consumption reduces significantly, whereasin case of fixed set point conditions, peak is very high as compared to the rest of the

period.


14/20

13

Fig.9. Energy consumption in Ahmedabad considering fixed set point conditions

Fig.10. Energy consumption in Ahmedabad considering adaptive set point conditions

It is observed form Fig.9 and Fig. 10 that roof and wall insulation shows large energy savings potential considering fixed and adaptive set point conditions. The peak specific energy

consumption of ECBC case has also reduced to a great extent in case of adaptive approach.

Table 7 Energy consumption at both set point conditions in hot and dry climateAnnual Energy Saving in case of Ahmedabad

cases Energy consumptionFixed Set point

(kWh/m 2yr)

Energy consumptionAdaptive Set point

(kWh/m 2yr)

Actual EnergySaving

(kWh/m 2yr)

Percentagesaving

(%)As is case 196.29 164.52 31.77 16.18ECM_1 181.49 149.79 31.71 17.47ECM_2 161.53 136.41 25.12 15.55

ECM_3 156.50 129.15 27.35 17.48ECM_4 179.45 146.37 33.07 18.43


15/20

14

ECM_5 200.95 168.24 32.71 16.28ECM_6 155.46 128.26 27.20 17.50

ECBC Case 111.69 93.24 18.44 16.51

3.3.3. Energy efficiency in warm and humid climateChennai is chosen as representative city for warm and humid climate. While analysing theeffect of thermal adaptation, the cooling set point is varied on monthly basis as per the neutraltemperature that changes form 26.2 oC during March to 27.5 oC during the month of May.Figure 11 shows that there is not much difference between neutral temperature and constantthermostat line due to less variation in climatic conditions round the year. The variation ofdry bulb temperature ranges from 20 to 35 oC whereas relative humidity is all-time high suchas 70 to 90%.

Fig.11. Monthly variation of neutral temperature and mean monthly outdoor dry bulbtemperature (warm and humid climate, Chennai)

Table 8 demonstrates the annual energy consumption per unit area considering each ECMusing fixed and adaptive set point for the HVAC system. Following observations are noteddown such as:

With ECM_7, i.e. combination of all individual ECMs (ECBC case), 39% energycould be saved over the common practice case i.e. the as is case.

Further, additional energy saving by about 15 to 19% could be achieved (or maximumof 36.6kWh/m 2/yr) by using adaptive set point condition.

The effect of ECMs with adaptive set point approach is similar as compared to thefixed set point approach. This is clear from comparison of Fig. 12 and Fig. 13.

From Fig. 12 & 13, it can be revealed that when all the ECMs applied with adaptiveapproach, the monthly variation of energy consumption reduces by a large extent,whereas in case of fixed set point conditions peak is very high compared to rest of the

period.


16/20

15

Fig.12. Energy consumption considering fixed set point conditions in Chennai

Fig.13. Energy consumption considering adaptive set point conditions

Figure 12 and 13 shows that there is a large potential of energy savings between fixed andadaptive set points conditions. There is less variation in weather conditions in the chosen

climate, specific energy consumption of ECBC case is more than other climates and themaximum saving is possible during May only.

Table 8 Energy consumption at both set points conditions in warm and humid climate Annual Energy Saving in case of Chennai

cases Energy consumptionFixed Set point

(kWh/m 2yr)


(kWh/m 2yr)

Actual EnergySaving

(kWh/m 2yr)

Percentagesaving

(%)As is

case 212.37 177.64 34.72 16.35

ECM_1 197.45 162.50 34.95 17.70ECM_2 179.63 151.63 28.01 15.59


17/20

16

ECM_3 172.09 141.83 30.26 17.59ECM_4 195.31 158.67 36.64 18.76ECM_5 217.99 181.99 36.00 16.51ECM_6 171.45 141.19 30.26 17.65

ECBC case 128.80 108.14 20.66 16.04

3.4. Sensitivity analysisAnalysis of variation of building size reveals that with increase in building size keeping theintensities of internal loads constant, the energy saving due to ECBC measures reduces from39 % to 15.9 % in Chennai, from 40.6 % to 28.6% in Hyderabad, and from 43.09 % to 16.7% in Ahmedabad.The effect of thermal adaptation in large buildings reduces significantly from 16 % to 10.5 %in Chennai, 16.8 % to 6.3 % in Hyderabad, and from 16.7 % to 6.2% in Ahmedabad.Similarly, analysis of change in internal load shows that effect of thermal adaptation gets

reduced further from 10.5 to 3.4 in Chennai, 6.2 to 2% in Ahmedabad and from 6.3 to 2.5%in Hyderabad. Table 9 illustrates the variation in internal load and corresponding energysavings in chosen climates. It is concluded from Table 9 that 27% energy saving is possibleconsidering small buildings with high internal loads in hot and dry climate whereas Table 10demonstrates that energy savings reduces as increase in building size and internal loads (highinternal load).Thus, sensitivity analysis reveals that the effect of adaptive set point gets reduced in large

building blocks however in all cases, considering thermal adaptation is important to estimatethe actual behaviour of unconditioned buildings and for estimating energy savings in building

with air conditioning.

Table 9 Energy consumption and energy savings potential at different internal loads Variationof LPD& EPD(W/m 2)

Fixed set point conditionsHyderabad Ahmedabad Chennai

As is'case

ECBCCase

Savings (%)

As is' case

ECBCCase

Savings (%)

As is' Case

ECBCCase

Savings (%)

LPD 10EPD 10

199.3 168.8 15.3 299.2 173.3 42.1 270.0 189.1 30.0

LPD 10EPD 15

222.8 207.8 6.7 321.2 212.1 34.0 295.4 228.5 22.6

LPD 12EPD 20

246.6 246.5 0.0 343.7 250.6 27.1 320.6 267.7 16.5

Table 10 Summary of results variation analyzed under representative citiesVariation forsensitivity analysis

Hyderabad Ahmedabad Chennai

% Energy savings withECBC Case over as iscase at fixed thermostat set

point conditions

Small building 40.6 43.09 39.35Large building withlow LPD/EPD

28.21 32.7 30.9

Large building withhigh LPD/EPD

- - -


18/20

17

% Energy savings withECBC Case over as iscase at adaptive thermostatset point conditions

Small building 40.3 43.33 39.12

Large building withlow LPD/EPD

6.3 6.6 10.5

Large building withhigh LPD/EPD

2.5 2.2 3.4

3.5. Summary and discussionIt is observed that buildings complying with the Energy Conservation building Code of India,may consume about 40% less energy as compared to building built with conventionalconstruction practices of India. Table 11 summarizes the results of above analysis which iscarried out for three different cities under different climatic zones. Maximum energy savingsis possible in hot and dry climate as there is large variation in weather conditions. Themaximum annual energy consumption ( as is case 212 kWh/m 2yr) was found in warm andhumid climate being similar variation in weather conditions round the year whereas minimum

annual energy consumption (89 kWh/m2

/yr) was observed in composite climate consideringadaptive thermostat settings. Therefore, result reveals that composite climate is muchappropriate for evaluating the effect of thermal adaptation due to moderate change in climaticconditions.

Table 11 Energy consumption considering fixed and adaptive set point conditions inrespective cities

Composite climate (Hyderabad)cases Energy consumption

Fixed Set point

(kWh/m2

/yr)


(kWh/m2

/yr)

EnergySaving

(kWh/m2

/yr)

Saving(%)

As is case 177.89 149.34 28.54 16.04ECBC case 105.69 89.20 16.49 15.60Saving % 40.6 40.3 42.2 -

Hot and Dry climate (Ahmedabad)cases Energy consumption

Fixed Set point(kWh/m 2/yr)


(kWh/m 2/yr)

EnergySaving

(kWh/m 2/yr)

Saving(%)


Warm and Humid climate (Chennai)cases Energy consumption

Fixed Set point(kWh/m 2/yr)


(kWh/m 2/yr)

EnergySaving

(kWh/m 2/yr)

Saving(%)


Sensitivity analysis shows that, energy savings gets reduced to 16% with increase in buildingsize and internal loads. The effect of thermal adaptation in large buildings reduces

significantly from 16 % to 10.5 % in warm and humid climate (Chennai), from 16.8 % to 6.3% in composite climate (Hyderabad), and from 16.7 % to 6.2% in hot and dry climate


19/20

18

(Ahmedabad). Similarly, analysis of change in internal load illustrates that effect of thermaladaptation gets reduced further from 10.5 to 3.4 % in Chennai, 6.3 to 2.5% in Hyderabad andfrom 6.2 to 2% in Ahmedabad. It is observed that large building with low internal load givesenergy savings of about 28 to 32% considering constant thermostat conditions which reduces

to 6 to 10% considering thermal adaptation. It is concluded that ECBC envelope improves theenergy performance of a building although specific measure should be chosen wisely as allthe ECMs do not offer same energy performance in all climates.4. ConclusionThis study evaluates improvement in energy efficiency of an air conditioned building blockemploying energy conservation measures recommended by National Energy ConservationBuilding Code (ECBC). Following are the key conclusion of the study-

- Small building with ECBC specifications gives energy saving opportunity of about43% compared to buildings built with conventionally practiced specifications ofIndia.

- The effect of thermal adaptation itself offers up to 16% energy conservation throughadaptive thermostat settings changing as per mean monthly outdoor temperature.

- However, in case of large buildings having high internal heat gain resulting fromlighting, equipment, occupancy; energy savings due to adaptive thermostat getreduces to negligible amount.

- The effect of thermal adaptation is of the same order for buildings constructed withcommon practices and buildings having specifications as per ECBC.

Study suggests implementation of recommended envelope measures of building code toimprove energy efficiency in warm climatic conditions. Study highly recommends the use of

roof insulation over other ECMs except ECBC case. This measure alone offers 20% energysavings whereas group of other envelope measures gives 40% energy savings opportunities.Wall insulation also put forward significant energy conservation. Combination of roof andglass (ECBC roof + Glass SHGC) measure has not been found much effective over roofalthough it is recommended over wall insulation. This study also suggests use of adaptivethermostat control to reduce additional 16% energy consumption over fixed thermostat. Useof envelope measures along with adaptive thermostat concept is highly recommended.This, study would be useful to facility managers, investor, architects, engineers, andcontractors to choose the appropriate envelope measures in particular climate and to operateair conditioner on monthly variable thermostat settings to provide the most comfortableenvironment.AcknowledgementWe thank to Prof. Andreas Wagner and Dr. Marcel Schweiker from Department of BuildingPhysics and Building Services (fbta), Karlsruhe Institute of Technology Karlsruhe, Germanyfor their help during revision of this paper.References

[1]. A. Synnefa, M. Santamouris, H. Akbari, Estimating the effect of using cool coatingon energy loads and thermal comfort in residential buildings in various climateconditions, Energy and Buildings 39 (2007) 1167-1174.

[2]. USAID, Energy Conservation Building Code User Guide, BEE New Delhi, 2009.[3]. S. Chirarattananona, V. D. Hienc, P. Tummua, Thermal performance and cost


20/20

19

effectiveness of wall insulation under Thai climate, Energy and Buildings 45 (2012)82 90.

[4]. W. A. Friess, K. Rakhshan, T.A. Hendawi, S. Tajerzadeh, Wall insulation measuresfor residential villas in Dubai: A case study in energy efficiency, Energy and

Buildings 44 (2012 ) 26 32.[5]. A. Bhatia, V. Garg, J. Mathur, Calibrated simulation for estimating energy savings bythe use of cool roof in five Indian climatic zones, Journal of Renewable andSustainable Energy 3(2) (2011), art. no. 023108

[6]. L. Perez-Lombard, J. Ortiz, C. Pout, A review on buildings energy consumptioninformation, Energy and Buildings 40 (2008) 394 398.

[7]. J. Yua, L. Tian, C. Yang, X. Xu, J. Wang, Optimum insulation thickness of residentialroof with respect to solar-air degree-hours in hot summer and cold winter zone ofchina, Energy and Buildings 43 (2011) 2304-2313.

[8]. H. Radhi, Can envelope codes reduce electricity and CO2 emissions in different typesof buildings in the hot climate of Bahrain?, Energy (2009) 205 215.

[9]. Y. Jinghua,T. Liwei, Y. Changzhi, X. Xinhua, W. Jinbo, Optimum insulationthickness of residential roof with respect to solar-air degree-hours in hot summer andcold winter zone of china, Energy and Buildings 43 (2011) 2304 2313.

[10]. O. Kaynakli, A review of the economical and optimum thermal insulation thicknessfor building application, Renewable and Sustainable Energy Reviews 16 (2012) 415 425.

[11]. H. Akbari, S. Konopacki, M. Pomerantz, Cooling energy savings potential ofreflective roofs forresidential and commercial buildings in the United States, Energy

24 (1999) 391 407.[12]. ANSI/ASHRAE Stnadard 90.1-2007, Energy Standard for Building Except Low-Rise

Residential buidings Atlanta 2007.[13]. ASHRAE: Standard 55, Thermal environmental conditions for human occupancy,

American Society of Heating Refrigeration and Air Conditioning Engineers, Atlanta,GA, USA, 1992.

[14]. S. Wijewardane, M.T.R Jayasinghe, Thermal comfort temperature range for factoryworkers in warm humid tropical climates, Renewable Energy 33 (2008) 2057-2063.

[15]. K.W.H. Mui, W.T.D. Chan, Adaptive comfort temperatrue model in air-conditioend buildings in Hong Kong, Building and Environment 38 (2003) 837-852.

[16]. N. Yamtraipat, J. Khedari, J. Hirunlabh, Thermal comfort standards for airconditioned buildings in hot and humid Thailand considering additional factors ofacclimatization and education level, Solar Energy 78 (2005) 504-517

[17]. A. Auliciems, de Dear, Air-conditioning in Australia I human thermal factorsArchitectural Science Review 29 (3) (1986) 67-75.

[18]. BEE, Energy Conservation Building Code, Ministry of Power Government of India New Delhi 2007 1-70.

Documents

Enb Ibecc Adaptaiton and Ecbc