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A design day for building load and energy estimation
\ PERGAMON
Building and Environment 23 "0888# 358Ð366
A design day for building load and energy estimation Tianzhen Hong\ S[ K[ Chou \ T[ Y[ Bong Department of Mechanical and Production Engineering\ National University of Singapore\ 09 Kent Rid`e Crescent\ 008159\ Sin`apore Received 06 November 0886^ revised 6 April 0887^ accepted 1 June 0887
Abstract We describe how a design day for building energy performance simulation can be selected from a {typical meteorological year| of a location[ The advantages of the design day weather _le are its simplicity and ~exibility in use with simulation programs[ The design day is selected using a weather parameter comprising the daily average dry bulb temperature and total solar insolation[ The selection criterion addresses the balance between the need to minimise the part!load performance of the air!conditioning systems and plants and the number of hours of load not met[ To validate the versatility of the design day weather _le\ we compare simulation results of the peak load and load pro_le of a building obtained from the DOE!1[0E code and a specially developed load estimation program\ PEAKLOAD[ PEAKLOAD is developed using the transfer function method and ASHRAE databases[ Comparative results are in good agreement\ indicating that a design day thus selected can be used when quick answers are required and simulations using a TMY _le cannot be easily done or justi_ed[ Þ 0888 Elsevier Science Ltd[ All rights reserved[
0[ Introduction ENERGY performance simulation has become an indispensable procedure in the design\ retro_tting and operation of an energy!e.cient building[ For medium to large multi!zone commercial buildings\ the exercise is usually carried out using a detailed simulation program "DSP# like DOE!1 ð0Ł or ESP ð1Ł[ To enable an hour! by!hour simulation and to ensure a reasonable level of accuracy\ a DSP requires a full set of annual weather data labeled as a {typical meteorological year| or TMY[ Thus\ a DSP accompanied by a TMY weather _le can be used to predict the building peak load and annual cooling load pro_le\ the annual system and plant energy con! sumption\ and a host of information on the part!load performance of the building[ However\ the preparation of a TMY weather _le can be an elaborate and time!consuming process[ The di.! culty is exacerbated by the fact that annual weather data are not easily available and building designers involved in performance simulations are not the ones responsible for weather information gathering and recording[ Thus\ there is a need for an alternative weather data _le which can be extracted from annual weather information[ Such a {reduced| weather _le would ensure shorter preparation time for DSP runs and open up opportunities for the use
Corresponding author[ Tel[] 9954 661 1104^ fax] 9954 668 0348^ e! mail] mpecskÝedu[nus[sg
of less complex simulation programs\ especially in the estimation of building peak load and load pro_le[ The ability to estimate accurately the peak cooling load of a building is the crucial _rst step in the design of an energy e.cient HVAC system and achieving thermal comfort[ Correct plant sizing not only relates to initial cost\ but also impacts the annual running cost of a build! ing[ Although the hourly cooling load and plant energy demand of a building can be calculated precisely with DSPs\ expertise of HVAC engineers and much labour time are required to prepare data _les\ besides the weather _le for DSP runs\ even if only cooling load information is required[ Moreover\ at the preliminary design phase\ infor! mation available is often insu.cient to run simulations with DSPs[ For example\ a DOE!1 user has to plan for an energy analysis and master DOE!1|s complex building description language before he can proceed to write the input _le con_dently[ For retro_tting works\ a DOE!1 user needs to be fairly experienced in energy auditing in order to exploit the capability of the code fully[ But when quick answers are required\ especially for HVAC systems and plant sizing\ the level of details required in the prep! aration of a DSP input _le cannot be easily justi_ed[ Thus\ for a building of conventional construction and operation\ professionals resort to non!DSPs like E19!II ð2Ł and Trace ð3Ł[ Current applications of non!DSP design tools have led to the use of various types of {reduced| weather data _les and correlations to suit speci_c locations[ If not correctly
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validated\ the input weather data can lead to serious over or under prediction of loads and plant capacities\ thus resulting in a less than accurate estimation of the energy performance[ In this paper\ we present a methodology for the selection of a design day weather _le for energy simulation[ Although intended for use with non!DSPs\ this {reduced| weather _le can be used in DSPs as an alternative to the more complicated TMY[ To test the validity of the design day weather _le\ a program PEAKLOAD is developed to estimate the design cooling load of a building using the {reduced| weather _le[ Results from PEAKLOAD are compared with those obtained from the DOE!1[0E code[ PEAK! LOAD is based on the transfer function method rec! ommended by ASHRAE ð4\ 5Ł[ Conduction transfer functions "CTF# of walls and roofs and weighting factors "WF# of zones are obtained from ASHRAE databases produced from research ð6\ 7Ł[
dant rainfalls due to the maritime exposure of the island and its close proximity to the equator[ Its tropical oceanic climate means little seasonal variations in meteorological parameters[ On an average day\ the dry!bulb temperature lies between 14Ð21>C\ while the relative humidity ranges from 64) in the late afternoon to 84) in the early morning[ The cloud cover is signi_cant resulting in about 39) of the total solar radiation being the di}use com! ponent[ On very clear days\ the ratio of the di}use to total solar radiation is about 19)[ The current TMY _le for energy simulation in Sin! gapore is a set of annual weather data for 0868[ The TMY _le contains 7659 hours of information on solar insolation\ dry and wet bulb temperatures\ and wind speed[ Table 0 lists eight daily weather parameters of the 0868 weather _le[ Figure 0 shows the distribution of the annual daily maximum dry!bulb temperature[ For application in PEAKLOAD\ the design day is selected from the 254 days in 0868[
1[ Design day selection
1[1[ Basis for selecting the design day weather _le
As weather is random in nature\ di}erent types of buildings and HVAC systems and plants respond to wea! ther di}erently[ The outdoor design conditions for HVAC system design and building energy estimation should be chosen in line with speci_c applications and risk levels allowed[ Several methods to determine the outdoor design conditions have been discussed by Lam and Hui ð8Ł[ These methods by and large employ stat! istical techniques to determine values of several meteoro! logical parameters such as dry bulb temperature and wet bulb temperature\ according to their respective signi_cant levels based on long term weather records of a location[ For HVAC system designs\ an outdoor design point which combines values of parameters is su.cient[ But for HVAC plant sizing and building energy analysis\ more detailed data like hourly values of air temperature and humidity\ wind speed and direction\ and solar radiation are required[ In this paper\ the authors explore a new method\ which identi_es an equivalent temperature\ on a daily basis\ and picks out several possible design days from a TMY weather _le[ The method uses the DOE!1 code to run the simulation for a reference building opera! ting on the design days to determine the peak cooling loads\ based on which a valid design day is selected at the end[ The design day thus selected is a real historical day which re~ects the natural hourly variations of meteoro! logical parameters\ and on the other hand\ takes the building thermal dynamics into account[
The design day weather _le consists of 13 hourly values of dry!bulb temperature\ humidity\ wind velocity\ total horizontal solar radiation\ and direct normal radiation[ Because of the signi_cant thermal inertia of a building and its internal structure\ the e}ects of the hour!by!hour ~uctuation of the weather are not immediately felt but are distributed over several hours of the day[ Thus\ the in~uence of the weather parameters on system and plant loads cannot be attributed solely to weather parameters at any given hour but to a set of hourly values over a time period[ As such\ the design day weather _le is selec! ted from a complete set of weather data for a single day chosen from the TMY[ Theoretically\ the design day is to be the day having
1[0[ TMY for Singapore The main features of the tropical Singapore climate are the relatively uniform daily temperature pro_le and small diurnal change\ high relative humidity\ and abun!
Table 0 Annual statistics of the Singapore 0868 TMY Weather parameter
Annual maximum
Annual minimum
Annual average
Tmax Tmin Tavg Vavg RHavg Tsavg Qht Qdn
24[5 16[7 18[5 3[5 87[6 15[6 14[4 18[2
14[5 10[0 13[5 9[1 61[1 11[7 0[5 9[2
29[3 13[5 16[0 1[9 75[0 14[0 05[2 02[2
Tmax daily maximum dry bulb temperature ">C#^ Tmin daily minimum dry bulb temperature ">C#^ Tavg daily average dry bulb temperature ">C#^ Vavg daily average wind velocity "m:s#^ RHavg daily average relative humidity ")#^ Tsavg daily average wet bulb temperature ">C#^ Qht daily total horizontal solar radiation "MJ:m1#^ Qdn daily total direct normal radiation "MJ:m1#[
360
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Fig[ 0[ Histogram of the annual daily maximum dry bulb temperature[
the most adverse set of weather conditions so as to enable the selected systems and plants to meet the indoor com! fort criterion throughout the year when performing at their maximum capacity[ In this design mode\ where the number of hours of load not met is minimised\ the HVAC systems and plants are likely to perform frequently at part!load[ This is not energy e.cient[ On the other hand\ one could seek to reduce the number of hours of part! load performance[ Adopting this approach\ it is not necessary to design for maximum load[ Rather\ attention can be paid to mitigate adverse e}ects caused by speci_c weather parameters such as high ambient temperature\ high humidity\ and extreme radiation transmission through the building envelope[ Adopting the latter approach to the selection of a design day\ gains in the initial and year!round energy savings more than com! pensate for the loss of thermal comfort when the load is not met in those few hours in the year[ 1[2[ Key weather parameters Di}erent building types and HVAC systems respond to climatic variations di}erently[ A host of weather par! ameters combine to drive the dynamic thermal response of a building[ Among all the weather parameters that in~uence the energy performance of a building\ the dry! bulb temperature\ the wet!bulb temperature\ and the solar radiation may be regarded as the most signi_cant ones[ Besides acting as control parameters in the selection of a design day\ these parameters o}er clues for inter! ventions to reduce discomfort in occupied zones[ Table 1 presents three sets of key parameters and their correlations[ Because of the way the three parameters are correlated with one another\ they cannot reach their maximum values simultaneously on the same day[ The combined in~uence of the weather parameters on the energy performance of a building cannot be easily inferred from weather data alone[ Therefore\ it is necess!
Table 1 Correlation coe.cients of selected weather parameters Weather parameters
Correlation coe.cient
Tavg and Tsavg Tavg and Qht Tsavg and Qht Tavg and RHavg RHavg and Qht
9[54 9[46 9[97 −9[61 −9[56
ary to obtain additional information that can o}er an objective indication of the design day[ 1[3[ An equivalent temperature To study the combined e}ect of the key parameters\ we de_ne an equivalent temperature\ Te\ which incorporates the relative contributions of the daily average dry!bulb and wet!bulb temperatures and the daily horizontal solar insolation\ thus\ Te aTavg¦bTsavg¦ghQht
"0#
where a\ b and g take values of either 9 or 0\ and h is a coe.cient that converts solar radiation into temperature expressed as h
"surface solar absorptance# "surface convection coefficient#
"1#
Di}erent combinations of a\ b\ and g will lead to di}erent criteria hence di}erent design days[ The criterion of hQht is replaced by Qht without a}ecting the choice of the design day[ It should be noted that Te is the sol!air temperature if a 0\ b 9\ and g 0[ Table 2 lists six possible design days obtained from Singapore|s TMY\ including one obtained from the criterion of maximum hourly dry bulb temperature[ The design days are chosen
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Table 2 Possible design days selected by various criteria
Weather criterion
Design day "at occurrence of maximum value of criterion#
Te Tavg Qht Te Tsavg Te Tavg¦Tsavg Te Tavg¦Tsavg¦hQht Te Tavg¦hQht"solÐair temperature# Hourly dry!bulb temperature
04 March 08 September 10 May 19 May 19 May 29 April 1 June
at the occurrence of the maximum value of the respective criteria[ 1[4[ Maximum hourly cooling load and part!load per! formance For each of the possible design days shown in Table 2\ the DOE!1[0E code is used to determine the maximum cooling load and number of hours of loads not met for a reference building[ Figures 1 and 2 show the building elevation and plan\ respectively[ The reference building is assumed to operate 13 hours a day[ It is a 01!storey air!conditioned building with external walls facing north\ south\ east and west[ A typical ~oor of the building is divided into 5 zones[ Tables 3 and 4 provide some details of the building[ The DOE!1 calculated cooling load of the building is presented in Table 5 against the possible selected design days[ A seventh design day\ 20 January\ is found by
Fig[ 1[ Elevation of the reference building[
taking the day with the maximum cooling load[ Table 5 also shows the number of hours of load not met annually by the building systems and plants[ The _gures in brack! ets are the percentage of the annual number of hours of load not met[ It should be noted that the building air! conditioning plant capacities are automatically sized by the DOE!1[0E code based on the peak cooling load of the design day[ Upon inspection of Table 5\ one may be led to conclude that 20 January\ having the maximum cooling load of 609 kW\ is the design day[ The criterion for this selection is the minimum number of hours of load not met[ Design! ing for this day will provide for more than enough capacity to handle the building load[ However\ as is explained above\ this mode will cause the systems and plants to operate with the maximum number of hours at part load[ The building will have a low annual load factor and a low global energy e.ciency[ If the choice is based on the maximum ambient dry bulb temperature\ 1 June will be the design day[ However\ weather data on 1 June would have given us a maximum cooling load of 433 kW and the design would have resulted in 0047 hours of load not met[ This is clearly unacceptable[ This implies that other weather parameters need to be considered when selecting a design day[ Between the two extremes of 433 and 609 kW\ 08 September\ 04 March and 29 April appear to be reason! able design days[ They have relatively low percentage of hours of load not met[ Their cooling loads are 82[4\ 84[1 and 85[1) of the peak load of 609 kW\ respectively[ It appears that the maximum daily average ambient dry bulb temperature and the maximum solar insolation\ either on their own or combined\ can provide a good indication of the design day[ In this study\ we select 29 April as the design day[ This is the day when the daily average sol!air temperature peaks[ For this design day\ we obtain a reasonable 07 hours of load not met annually[ It should not be di.cult to take some measures to reduce any discomfort in the air!conditioned zones when the load exceeds the design capacity of the systems and plants during those hours[ Thus\ the sol!air temperature may prove to be a useful criterion to be applied to picking the design day in trop! ical climates[ It should be noted that there are no absolute criteria to selecting design days[ The crucial concern is the trade! o} between hours of load not met\ i[e[\ design risk\ and the total cost of the HVAC systems and plants[ For buildings where human comfort is concerned\ it is not critical that indoor temperature or humidity ranges beyond the design conditions for brief periods of severe weather[ Therefore\ design days with less severe weather conditions can be adopted in order to reduce the initial and operating costs of HVAC systems[ If the cost of the failure to maintain the indoor design conditions is signi_cant or unbearable\ then the design day that covers
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Fig[ 2[ Plan of the reference building[
Table 3 Floor area and usage of the various zones
2[ Development of peakload
Zone
Area "m1#
Usage
Air!conditioned<
0 1 2 3 4 5
264 264 264 264 599 399
O.ce O.ce O.ce O.ce Corridor Elevator
Yes Yes Yes Yes Yes No
Table 4 Description of the reference building
Having found a way of selecting the design day\ a non! DSP called PEAKLOAD is developed to calculate the building peak load\ cooling load pro_le\ and zone tem! perature pro_le\ using the design day weather _le[ PEAK! LOAD can be used on its own or within BEST ð09Ł[ BEST is a program developed in collaboration with the Building Control Division of the Singapore Public Works Depart! ment[ BEST is designed to be used by engineers\ architects and building services professionals in complying with prescriptive and energy performance standards relating to air conditioned commercial buildings[ 2[0[ Structure and algorithm
Walls
External] 49 cm concrete\ 1[9 cm air layers\ 9[7 cm spandrel glass on exterior[ Total R 9[560 "m1K#:W\ Uw 0[38 W:"m1 K# Interior] 0[48 cm gypsum board\ 09 cm air layer\ 0[48 cm gypsum board[ Total R 9[347 "m1K#:W
Roofs
0[14 cm roof gravel\ 9[84 cm built up roo_ng\ R4 polystyrene insulation\ 04[1 cm concrete\ 09[1 cm air layer\ 0[2 cm acoustic tile[ Total R 0[474 "m1K#:W
Floors
04[1 cm concrete ~oors[ Total R 9[125 "m1K#:W
Windows
Window!to!wall ratio 9[21\ Shading coe.cient 9[1 Glass conductance 9[48 W:"m1K#^ Uf 0[38 W:"m1K#
the worst weather conditions should be employed[ For a tropical location like Singapore\ the seasonal variation of climate is trivial\ therefore one design day may be appropriate[ For other countries or locations\ di}erent design days for di}erent seasons may be necessary[
There are two modules within PEAKLOAD[ The cal! culating core is implemented in a Fortran module PLcal\ which reads the building data _le Peakload[inp\ the design day weather data\ and ASHRAE CTF:WF dat! abases\ performs the required calculations\ and generates the results _le Peakload[oup[ The other module\ PLgui\ is implemented in Visual Basic thus providing users with an interactive interface for keying in building data and generating the input _le Peakload[inp[ PLgui also pro! vides graphical presentation of calculation results[ PLgui enables PEAKLOAD to import building _le from BEST so that users avoid having to key in the input data twice[ PEAKLOAD uses the algorithm of the transfer func! tion method well described in Refs ð4 and 5Ł[ As the model is based on a single design day\ the calculations of the conduction heat gains for walls and roofs\ zone cooling loads\ and zone heat extraction rates are iterated for a 13!h periodic cycle of the design day until these hourly heat ~ows and the load pro_le converge to a steady per! iodic pattern[
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Table 5 Design days with peak load and hours of load not met Criterion
Design day
Peak cooling load of design day "kW#
Hours of load not met
Te Tavg Qht Te Tsavg Te Tavg¦Tsavg Te Tavg¦Tsavg¦hQht Te Tavg¦hQht Hourly dry!bulb temperature Hourly cooling load
04 March 08 September 10 May 19 May 19 May 29 April 1 June 20 January
565 553 534 509 509 572 433 609
15 "9[2)# 61 "9[7)# 072 "1[0)# 355 "4[2)# 355 "4[2)# 07 "9[1)# 0047 "02)# 9 "9)#
2[1[ Validation Information on external walls\ windows\ roofs\ skylights\ zone\ and some empirical coe.cients\ are required as input of PEAKLOAD[ Figures 3 and 4 show some input data[ Simulation results from PEAKLOAD are shown in Figs 5 and 6[ Results of the hour!by!hour calculations obtained by the DOE!1[0E code and PEAKLOAD for the reference building on the design day are compared in Fig[ 7[ It can be seen that the two load pro_les agree reasonably well
with the load pro_les peaking coincidentally at 3[99 pm[ The peak cooling load obtained from DOE!1[0E and PEAKLOAD is 572 and 546 kW\ respectively\ which gives a relative error of less than 3)[ In the above comparison\ PEAKLOAD models the reference building as a single zone to facilitate quick calculations[ This treatment has the e}ect of averaging the cooling load over the entire air!conditioned space of the building[ For DOE!1[0E simulation\ the typical ~oor of the reference building is modelled as a 4!zone air! conditioned space[ This may explain the somewhat lower
Fig[ 3[ Description of windows[
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364
Fig[ 4[ Description of air!conditioned zone[
Fig[ 5[ Hourly plant cooling loads of the design day[
peak load value computed by PEAKLOAD compared to that obtained from DOE!1[0E[ It should be noted that the PEAKLOAD and DOE!1[0E codes utilise a similar set of precalculated transfer function coe.cients[ However\ with better zoning\ DOE!1[0E code is better
able to provide a realistic depiction of the thermal inter! actions of the zones and the external environment[ Thus\ for better accuracy\ zone by zone calculations using the design day weather _le is recommended[ The total build! ing load can then be obtained by a summation of the
365
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Fig[ 6[ Hourly outdoor temperature and zone temperature of the design day[
Fig[ 7[ Plant cooling loads given by DOE!1[0E and PEAKLOAD[
hourly zone loads[ The peak design load is the coincident peak load for the entire building[
3[ Conclusion We have described a procedure for obtaining a design day weather _le from a location|s TMY for use in load and energy simulation programs[ An equivalent temperature weather criterion is chosen to identify the design day from 254 days of the TMY[ We show that for regions with tropical oceanic climate\ like Singapore\ the design day
can be selected based on the daily average sol!air tem! perature[ To validate the method\ a comparison is made of the cooling load pro_le and peak load of a reference building calculated by the DOE!1[0E code and a specially developed program PEAKLOAD[ PEAKLOAD is implemented on the basis of ASHRAE CTF:WF data! bases and the design day weather data[ Good agreement of results is obtained[ Thus\ the methodology of selecting the design day weather _le o}ers interesting possibilities for users of simulation software of varying degree of com! plexity[ This will facilitate the works of engineers and architects\ especially at the early building design stage[
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Acknowledgement This project was sponsored by the National Science and Technology Board "NSTB# of Singapore[
References ð0Ł DOE!1 Manuals "Version 1[0#[ U[S[ National Technical Infor! mation Service\ Department of Commerce\ Spring_eld\ Virginia\ U[S[A[] 0879[ ð1Ł Clarke JA\ Mclean D[ ESP] A building and plant energy simulation system\ Version 4\ Release 2\ University of Strathclyde\ Glasgow\ U[K[\ 0875[ ð2Ł HAP Version 0[0 E19!II Operational Manual[ Syracuse\ NY\ U[S[A[] Carrier Corporation\ 0877[
366
ð3Ł Trace] The Customer Direct Service Network University Package User|s Guide Manual[ Lacrosse\ WI\ U[S[A[] Trane Inc[\ 0876[ ð4Ł ASHRAE Handbook] Fundamentals[ GA\ U[S[A[] ASHRAE press\ 0886[ ð5Ł McQuiston FC\ Spitler JD[ Heating and cooling load calculation manual[ GA\ U[S[A[] ASHRAE press\ 0881[ ð6Ł Sowell EF[ Load calculations for 199539 zones[ ASHRAE Trans! actions 0877^83"1#]605Ð25[ ð7Ł Sowell EF[ Classi_cation of 199539 parametric zones for cooling load calculations[ ASHRAE Transactions 0877^83"1#]643Ð66[ ð8Ł Lam JC\ Hui Sam CM[ Outdoor design conditions for HVAC system design and energy estimation for buildings in Hong Kong[ Energy and Buildings 0884^11"0#]14Ð32[ ð09Ł Building Energy Standards "BEST#\ User|s Guide to Building Energy Conservation Standards Calculations[ National University of Singapore\ Department of Mechanical and Production Engin! eering\ 09 Kent Ridge Crescent\ Singapore 008159] 0884[
Building and Environment 23 "0888# 358Ð366
A design day for building load and energy estimation Tianzhen Hong\ S[ K[ Chou \ T[ Y[ Bong Department of Mechanical and Production Engineering\ National University of Singapore\ 09 Kent Rid`e Crescent\ 008159\ Sin`apore Received 06 November 0886^ revised 6 April 0887^ accepted 1 June 0887
Abstract We describe how a design day for building energy performance simulation can be selected from a {typical meteorological year| of a location[ The advantages of the design day weather _le are its simplicity and ~exibility in use with simulation programs[ The design day is selected using a weather parameter comprising the daily average dry bulb temperature and total solar insolation[ The selection criterion addresses the balance between the need to minimise the part!load performance of the air!conditioning systems and plants and the number of hours of load not met[ To validate the versatility of the design day weather _le\ we compare simulation results of the peak load and load pro_le of a building obtained from the DOE!1[0E code and a specially developed load estimation program\ PEAKLOAD[ PEAKLOAD is developed using the transfer function method and ASHRAE databases[ Comparative results are in good agreement\ indicating that a design day thus selected can be used when quick answers are required and simulations using a TMY _le cannot be easily done or justi_ed[ Þ 0888 Elsevier Science Ltd[ All rights reserved[
0[ Introduction ENERGY performance simulation has become an indispensable procedure in the design\ retro_tting and operation of an energy!e.cient building[ For medium to large multi!zone commercial buildings\ the exercise is usually carried out using a detailed simulation program "DSP# like DOE!1 ð0Ł or ESP ð1Ł[ To enable an hour! by!hour simulation and to ensure a reasonable level of accuracy\ a DSP requires a full set of annual weather data labeled as a {typical meteorological year| or TMY[ Thus\ a DSP accompanied by a TMY weather _le can be used to predict the building peak load and annual cooling load pro_le\ the annual system and plant energy con! sumption\ and a host of information on the part!load performance of the building[ However\ the preparation of a TMY weather _le can be an elaborate and time!consuming process[ The di.! culty is exacerbated by the fact that annual weather data are not easily available and building designers involved in performance simulations are not the ones responsible for weather information gathering and recording[ Thus\ there is a need for an alternative weather data _le which can be extracted from annual weather information[ Such a {reduced| weather _le would ensure shorter preparation time for DSP runs and open up opportunities for the use
Corresponding author[ Tel[] 9954 661 1104^ fax] 9954 668 0348^ e! mail] mpecskÝedu[nus[sg
of less complex simulation programs\ especially in the estimation of building peak load and load pro_le[ The ability to estimate accurately the peak cooling load of a building is the crucial _rst step in the design of an energy e.cient HVAC system and achieving thermal comfort[ Correct plant sizing not only relates to initial cost\ but also impacts the annual running cost of a build! ing[ Although the hourly cooling load and plant energy demand of a building can be calculated precisely with DSPs\ expertise of HVAC engineers and much labour time are required to prepare data _les\ besides the weather _le for DSP runs\ even if only cooling load information is required[ Moreover\ at the preliminary design phase\ infor! mation available is often insu.cient to run simulations with DSPs[ For example\ a DOE!1 user has to plan for an energy analysis and master DOE!1|s complex building description language before he can proceed to write the input _le con_dently[ For retro_tting works\ a DOE!1 user needs to be fairly experienced in energy auditing in order to exploit the capability of the code fully[ But when quick answers are required\ especially for HVAC systems and plant sizing\ the level of details required in the prep! aration of a DSP input _le cannot be easily justi_ed[ Thus\ for a building of conventional construction and operation\ professionals resort to non!DSPs like E19!II ð2Ł and Trace ð3Ł[ Current applications of non!DSP design tools have led to the use of various types of {reduced| weather data _les and correlations to suit speci_c locations[ If not correctly
S9259Ð0212:88:, ! see front matter Þ 0888 Elsevier Science Ltd[ All rights reserved PII] S 9 2 5 9 Ð 0 2 1 2 " 8 7 # 9 9 9 2 4 Ð 2
369
T[ Hon` et al[:Buildin` and Environment 23 "0888# 358Ð366
validated\ the input weather data can lead to serious over or under prediction of loads and plant capacities\ thus resulting in a less than accurate estimation of the energy performance[ In this paper\ we present a methodology for the selection of a design day weather _le for energy simulation[ Although intended for use with non!DSPs\ this {reduced| weather _le can be used in DSPs as an alternative to the more complicated TMY[ To test the validity of the design day weather _le\ a program PEAKLOAD is developed to estimate the design cooling load of a building using the {reduced| weather _le[ Results from PEAKLOAD are compared with those obtained from the DOE!1[0E code[ PEAK! LOAD is based on the transfer function method rec! ommended by ASHRAE ð4\ 5Ł[ Conduction transfer functions "CTF# of walls and roofs and weighting factors "WF# of zones are obtained from ASHRAE databases produced from research ð6\ 7Ł[
dant rainfalls due to the maritime exposure of the island and its close proximity to the equator[ Its tropical oceanic climate means little seasonal variations in meteorological parameters[ On an average day\ the dry!bulb temperature lies between 14Ð21>C\ while the relative humidity ranges from 64) in the late afternoon to 84) in the early morning[ The cloud cover is signi_cant resulting in about 39) of the total solar radiation being the di}use com! ponent[ On very clear days\ the ratio of the di}use to total solar radiation is about 19)[ The current TMY _le for energy simulation in Sin! gapore is a set of annual weather data for 0868[ The TMY _le contains 7659 hours of information on solar insolation\ dry and wet bulb temperatures\ and wind speed[ Table 0 lists eight daily weather parameters of the 0868 weather _le[ Figure 0 shows the distribution of the annual daily maximum dry!bulb temperature[ For application in PEAKLOAD\ the design day is selected from the 254 days in 0868[
1[ Design day selection
1[1[ Basis for selecting the design day weather _le
As weather is random in nature\ di}erent types of buildings and HVAC systems and plants respond to wea! ther di}erently[ The outdoor design conditions for HVAC system design and building energy estimation should be chosen in line with speci_c applications and risk levels allowed[ Several methods to determine the outdoor design conditions have been discussed by Lam and Hui ð8Ł[ These methods by and large employ stat! istical techniques to determine values of several meteoro! logical parameters such as dry bulb temperature and wet bulb temperature\ according to their respective signi_cant levels based on long term weather records of a location[ For HVAC system designs\ an outdoor design point which combines values of parameters is su.cient[ But for HVAC plant sizing and building energy analysis\ more detailed data like hourly values of air temperature and humidity\ wind speed and direction\ and solar radiation are required[ In this paper\ the authors explore a new method\ which identi_es an equivalent temperature\ on a daily basis\ and picks out several possible design days from a TMY weather _le[ The method uses the DOE!1 code to run the simulation for a reference building opera! ting on the design days to determine the peak cooling loads\ based on which a valid design day is selected at the end[ The design day thus selected is a real historical day which re~ects the natural hourly variations of meteoro! logical parameters\ and on the other hand\ takes the building thermal dynamics into account[
The design day weather _le consists of 13 hourly values of dry!bulb temperature\ humidity\ wind velocity\ total horizontal solar radiation\ and direct normal radiation[ Because of the signi_cant thermal inertia of a building and its internal structure\ the e}ects of the hour!by!hour ~uctuation of the weather are not immediately felt but are distributed over several hours of the day[ Thus\ the in~uence of the weather parameters on system and plant loads cannot be attributed solely to weather parameters at any given hour but to a set of hourly values over a time period[ As such\ the design day weather _le is selec! ted from a complete set of weather data for a single day chosen from the TMY[ Theoretically\ the design day is to be the day having
1[0[ TMY for Singapore The main features of the tropical Singapore climate are the relatively uniform daily temperature pro_le and small diurnal change\ high relative humidity\ and abun!
Table 0 Annual statistics of the Singapore 0868 TMY Weather parameter
Annual maximum
Annual minimum
Annual average
Tmax Tmin Tavg Vavg RHavg Tsavg Qht Qdn
24[5 16[7 18[5 3[5 87[6 15[6 14[4 18[2
14[5 10[0 13[5 9[1 61[1 11[7 0[5 9[2
29[3 13[5 16[0 1[9 75[0 14[0 05[2 02[2
Tmax daily maximum dry bulb temperature ">C#^ Tmin daily minimum dry bulb temperature ">C#^ Tavg daily average dry bulb temperature ">C#^ Vavg daily average wind velocity "m:s#^ RHavg daily average relative humidity ")#^ Tsavg daily average wet bulb temperature ">C#^ Qht daily total horizontal solar radiation "MJ:m1#^ Qdn daily total direct normal radiation "MJ:m1#[
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Fig[ 0[ Histogram of the annual daily maximum dry bulb temperature[
the most adverse set of weather conditions so as to enable the selected systems and plants to meet the indoor com! fort criterion throughout the year when performing at their maximum capacity[ In this design mode\ where the number of hours of load not met is minimised\ the HVAC systems and plants are likely to perform frequently at part!load[ This is not energy e.cient[ On the other hand\ one could seek to reduce the number of hours of part! load performance[ Adopting this approach\ it is not necessary to design for maximum load[ Rather\ attention can be paid to mitigate adverse e}ects caused by speci_c weather parameters such as high ambient temperature\ high humidity\ and extreme radiation transmission through the building envelope[ Adopting the latter approach to the selection of a design day\ gains in the initial and year!round energy savings more than com! pensate for the loss of thermal comfort when the load is not met in those few hours in the year[ 1[2[ Key weather parameters Di}erent building types and HVAC systems respond to climatic variations di}erently[ A host of weather par! ameters combine to drive the dynamic thermal response of a building[ Among all the weather parameters that in~uence the energy performance of a building\ the dry! bulb temperature\ the wet!bulb temperature\ and the solar radiation may be regarded as the most signi_cant ones[ Besides acting as control parameters in the selection of a design day\ these parameters o}er clues for inter! ventions to reduce discomfort in occupied zones[ Table 1 presents three sets of key parameters and their correlations[ Because of the way the three parameters are correlated with one another\ they cannot reach their maximum values simultaneously on the same day[ The combined in~uence of the weather parameters on the energy performance of a building cannot be easily inferred from weather data alone[ Therefore\ it is necess!
Table 1 Correlation coe.cients of selected weather parameters Weather parameters
Correlation coe.cient
Tavg and Tsavg Tavg and Qht Tsavg and Qht Tavg and RHavg RHavg and Qht
9[54 9[46 9[97 −9[61 −9[56
ary to obtain additional information that can o}er an objective indication of the design day[ 1[3[ An equivalent temperature To study the combined e}ect of the key parameters\ we de_ne an equivalent temperature\ Te\ which incorporates the relative contributions of the daily average dry!bulb and wet!bulb temperatures and the daily horizontal solar insolation\ thus\ Te aTavg¦bTsavg¦ghQht
"0#
where a\ b and g take values of either 9 or 0\ and h is a coe.cient that converts solar radiation into temperature expressed as h
"surface solar absorptance# "surface convection coefficient#
"1#
Di}erent combinations of a\ b\ and g will lead to di}erent criteria hence di}erent design days[ The criterion of hQht is replaced by Qht without a}ecting the choice of the design day[ It should be noted that Te is the sol!air temperature if a 0\ b 9\ and g 0[ Table 2 lists six possible design days obtained from Singapore|s TMY\ including one obtained from the criterion of maximum hourly dry bulb temperature[ The design days are chosen
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Table 2 Possible design days selected by various criteria
Weather criterion
Design day "at occurrence of maximum value of criterion#
Te Tavg Qht Te Tsavg Te Tavg¦Tsavg Te Tavg¦Tsavg¦hQht Te Tavg¦hQht"solÐair temperature# Hourly dry!bulb temperature
04 March 08 September 10 May 19 May 19 May 29 April 1 June
at the occurrence of the maximum value of the respective criteria[ 1[4[ Maximum hourly cooling load and part!load per! formance For each of the possible design days shown in Table 2\ the DOE!1[0E code is used to determine the maximum cooling load and number of hours of loads not met for a reference building[ Figures 1 and 2 show the building elevation and plan\ respectively[ The reference building is assumed to operate 13 hours a day[ It is a 01!storey air!conditioned building with external walls facing north\ south\ east and west[ A typical ~oor of the building is divided into 5 zones[ Tables 3 and 4 provide some details of the building[ The DOE!1 calculated cooling load of the building is presented in Table 5 against the possible selected design days[ A seventh design day\ 20 January\ is found by
Fig[ 1[ Elevation of the reference building[
taking the day with the maximum cooling load[ Table 5 also shows the number of hours of load not met annually by the building systems and plants[ The _gures in brack! ets are the percentage of the annual number of hours of load not met[ It should be noted that the building air! conditioning plant capacities are automatically sized by the DOE!1[0E code based on the peak cooling load of the design day[ Upon inspection of Table 5\ one may be led to conclude that 20 January\ having the maximum cooling load of 609 kW\ is the design day[ The criterion for this selection is the minimum number of hours of load not met[ Design! ing for this day will provide for more than enough capacity to handle the building load[ However\ as is explained above\ this mode will cause the systems and plants to operate with the maximum number of hours at part load[ The building will have a low annual load factor and a low global energy e.ciency[ If the choice is based on the maximum ambient dry bulb temperature\ 1 June will be the design day[ However\ weather data on 1 June would have given us a maximum cooling load of 433 kW and the design would have resulted in 0047 hours of load not met[ This is clearly unacceptable[ This implies that other weather parameters need to be considered when selecting a design day[ Between the two extremes of 433 and 609 kW\ 08 September\ 04 March and 29 April appear to be reason! able design days[ They have relatively low percentage of hours of load not met[ Their cooling loads are 82[4\ 84[1 and 85[1) of the peak load of 609 kW\ respectively[ It appears that the maximum daily average ambient dry bulb temperature and the maximum solar insolation\ either on their own or combined\ can provide a good indication of the design day[ In this study\ we select 29 April as the design day[ This is the day when the daily average sol!air temperature peaks[ For this design day\ we obtain a reasonable 07 hours of load not met annually[ It should not be di.cult to take some measures to reduce any discomfort in the air!conditioned zones when the load exceeds the design capacity of the systems and plants during those hours[ Thus\ the sol!air temperature may prove to be a useful criterion to be applied to picking the design day in trop! ical climates[ It should be noted that there are no absolute criteria to selecting design days[ The crucial concern is the trade! o} between hours of load not met\ i[e[\ design risk\ and the total cost of the HVAC systems and plants[ For buildings where human comfort is concerned\ it is not critical that indoor temperature or humidity ranges beyond the design conditions for brief periods of severe weather[ Therefore\ design days with less severe weather conditions can be adopted in order to reduce the initial and operating costs of HVAC systems[ If the cost of the failure to maintain the indoor design conditions is signi_cant or unbearable\ then the design day that covers
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Fig[ 2[ Plan of the reference building[
Table 3 Floor area and usage of the various zones
2[ Development of peakload
Zone
Area "m1#
Usage
Air!conditioned<
0 1 2 3 4 5
264 264 264 264 599 399
O.ce O.ce O.ce O.ce Corridor Elevator
Yes Yes Yes Yes Yes No
Table 4 Description of the reference building
Having found a way of selecting the design day\ a non! DSP called PEAKLOAD is developed to calculate the building peak load\ cooling load pro_le\ and zone tem! perature pro_le\ using the design day weather _le[ PEAK! LOAD can be used on its own or within BEST ð09Ł[ BEST is a program developed in collaboration with the Building Control Division of the Singapore Public Works Depart! ment[ BEST is designed to be used by engineers\ architects and building services professionals in complying with prescriptive and energy performance standards relating to air conditioned commercial buildings[ 2[0[ Structure and algorithm
Walls
External] 49 cm concrete\ 1[9 cm air layers\ 9[7 cm spandrel glass on exterior[ Total R 9[560 "m1K#:W\ Uw 0[38 W:"m1 K# Interior] 0[48 cm gypsum board\ 09 cm air layer\ 0[48 cm gypsum board[ Total R 9[347 "m1K#:W
Roofs
0[14 cm roof gravel\ 9[84 cm built up roo_ng\ R4 polystyrene insulation\ 04[1 cm concrete\ 09[1 cm air layer\ 0[2 cm acoustic tile[ Total R 0[474 "m1K#:W
Floors
04[1 cm concrete ~oors[ Total R 9[125 "m1K#:W
Windows
Window!to!wall ratio 9[21\ Shading coe.cient 9[1 Glass conductance 9[48 W:"m1K#^ Uf 0[38 W:"m1K#
the worst weather conditions should be employed[ For a tropical location like Singapore\ the seasonal variation of climate is trivial\ therefore one design day may be appropriate[ For other countries or locations\ di}erent design days for di}erent seasons may be necessary[
There are two modules within PEAKLOAD[ The cal! culating core is implemented in a Fortran module PLcal\ which reads the building data _le Peakload[inp\ the design day weather data\ and ASHRAE CTF:WF dat! abases\ performs the required calculations\ and generates the results _le Peakload[oup[ The other module\ PLgui\ is implemented in Visual Basic thus providing users with an interactive interface for keying in building data and generating the input _le Peakload[inp[ PLgui also pro! vides graphical presentation of calculation results[ PLgui enables PEAKLOAD to import building _le from BEST so that users avoid having to key in the input data twice[ PEAKLOAD uses the algorithm of the transfer func! tion method well described in Refs ð4 and 5Ł[ As the model is based on a single design day\ the calculations of the conduction heat gains for walls and roofs\ zone cooling loads\ and zone heat extraction rates are iterated for a 13!h periodic cycle of the design day until these hourly heat ~ows and the load pro_le converge to a steady per! iodic pattern[
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Table 5 Design days with peak load and hours of load not met Criterion
Design day
Peak cooling load of design day "kW#
Hours of load not met
Te Tavg Qht Te Tsavg Te Tavg¦Tsavg Te Tavg¦Tsavg¦hQht Te Tavg¦hQht Hourly dry!bulb temperature Hourly cooling load
04 March 08 September 10 May 19 May 19 May 29 April 1 June 20 January
565 553 534 509 509 572 433 609
15 "9[2)# 61 "9[7)# 072 "1[0)# 355 "4[2)# 355 "4[2)# 07 "9[1)# 0047 "02)# 9 "9)#
2[1[ Validation Information on external walls\ windows\ roofs\ skylights\ zone\ and some empirical coe.cients\ are required as input of PEAKLOAD[ Figures 3 and 4 show some input data[ Simulation results from PEAKLOAD are shown in Figs 5 and 6[ Results of the hour!by!hour calculations obtained by the DOE!1[0E code and PEAKLOAD for the reference building on the design day are compared in Fig[ 7[ It can be seen that the two load pro_les agree reasonably well
with the load pro_les peaking coincidentally at 3[99 pm[ The peak cooling load obtained from DOE!1[0E and PEAKLOAD is 572 and 546 kW\ respectively\ which gives a relative error of less than 3)[ In the above comparison\ PEAKLOAD models the reference building as a single zone to facilitate quick calculations[ This treatment has the e}ect of averaging the cooling load over the entire air!conditioned space of the building[ For DOE!1[0E simulation\ the typical ~oor of the reference building is modelled as a 4!zone air! conditioned space[ This may explain the somewhat lower
Fig[ 3[ Description of windows[
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Fig[ 4[ Description of air!conditioned zone[
Fig[ 5[ Hourly plant cooling loads of the design day[
peak load value computed by PEAKLOAD compared to that obtained from DOE!1[0E[ It should be noted that the PEAKLOAD and DOE!1[0E codes utilise a similar set of precalculated transfer function coe.cients[ However\ with better zoning\ DOE!1[0E code is better
able to provide a realistic depiction of the thermal inter! actions of the zones and the external environment[ Thus\ for better accuracy\ zone by zone calculations using the design day weather _le is recommended[ The total build! ing load can then be obtained by a summation of the
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Fig[ 6[ Hourly outdoor temperature and zone temperature of the design day[
Fig[ 7[ Plant cooling loads given by DOE!1[0E and PEAKLOAD[
hourly zone loads[ The peak design load is the coincident peak load for the entire building[
3[ Conclusion We have described a procedure for obtaining a design day weather _le from a location|s TMY for use in load and energy simulation programs[ An equivalent temperature weather criterion is chosen to identify the design day from 254 days of the TMY[ We show that for regions with tropical oceanic climate\ like Singapore\ the design day
can be selected based on the daily average sol!air tem! perature[ To validate the method\ a comparison is made of the cooling load pro_le and peak load of a reference building calculated by the DOE!1[0E code and a specially developed program PEAKLOAD[ PEAKLOAD is implemented on the basis of ASHRAE CTF:WF data! bases and the design day weather data[ Good agreement of results is obtained[ Thus\ the methodology of selecting the design day weather _le o}ers interesting possibilities for users of simulation software of varying degree of com! plexity[ This will facilitate the works of engineers and architects\ especially at the early building design stage[
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Acknowledgement This project was sponsored by the National Science and Technology Board "NSTB# of Singapore[
References ð0Ł DOE!1 Manuals "Version 1[0#[ U[S[ National Technical Infor! mation Service\ Department of Commerce\ Spring_eld\ Virginia\ U[S[A[] 0879[ ð1Ł Clarke JA\ Mclean D[ ESP] A building and plant energy simulation system\ Version 4\ Release 2\ University of Strathclyde\ Glasgow\ U[K[\ 0875[ ð2Ł HAP Version 0[0 E19!II Operational Manual[ Syracuse\ NY\ U[S[A[] Carrier Corporation\ 0877[
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ð3Ł Trace] The Customer Direct Service Network University Package User|s Guide Manual[ Lacrosse\ WI\ U[S[A[] Trane Inc[\ 0876[ ð4Ł ASHRAE Handbook] Fundamentals[ GA\ U[S[A[] ASHRAE press\ 0886[ ð5Ł McQuiston FC\ Spitler JD[ Heating and cooling load calculation manual[ GA\ U[S[A[] ASHRAE press\ 0881[ ð6Ł Sowell EF[ Load calculations for 199539 zones[ ASHRAE Trans! actions 0877^83"1#]605Ð25[ ð7Ł Sowell EF[ Classi_cation of 199539 parametric zones for cooling load calculations[ ASHRAE Transactions 0877^83"1#]643Ð66[ ð8Ł Lam JC\ Hui Sam CM[ Outdoor design conditions for HVAC system design and energy estimation for buildings in Hong Kong[ Energy and Buildings 0884^11"0#]14Ð32[ ð09Ł Building Energy Standards "BEST#\ User|s Guide to Building Energy Conservation Standards Calculations[ National University of Singapore\ Department of Mechanical and Production Engin! eering\ 09 Kent Ridge Crescent\ Singapore 008159] 0884[