analysis of energy saving optimization of campus buildings

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RESEARCH ARTICLE

Dingding TONG, Jing ZHAO

Analysis of energy saving optimization of campus buildingsbased on energy simulation

Higher Education Press and Springer-Verlag Berlin Heidelberg 2013

Abstract The energy consumption of campus buildingshas specic characteristics, because of the concentrateddistribution of peoples working time and locations thatchange in line with distinct seasonal features. Thetraditional energy system design and operation for campus

buildings is only based on the constant room temperature,such as 25C in summer and 18C in winter in China, nottaking into consideration the real heating or cooling loadcharacteristics of campus buildings with different func-tions during the whole day and whole year, which usuallyresults in a lot of energy waste. This paper proposes to setdifferent set-point temperatures in different operationstages of public and residential campus buildings to reducethe heating and cooling design load for energy station andtotal campus energy consumption for annual operation.

Taking a campus under construction in Tianjin, China as anexample, two kinds of single building models wereestablished as the typical public building and residential

building models on the campus. Besides, the models weresimulated at both set-point room temperature and constantroom temperature respectively. The comparison of thesimulation results showed that the single building energysaving method of the peak load clipping could be used forfurther analysis of the annual energy consumption ofcampus building groups. The results proved that thestrategy of set-point temperature optimization couldefciently reduce the design load and energy consumptionof campus building groups.

Keywords campus buildings, set-point temperature,energy simulation, energy saving optimization

1 Introduction

Nowadays with the expansion of new campus constructionof universities, campus energy consumption has becomean important component in building energy consumptioni n Chi na [1]. So the discussion of energy-savingoptimization of campus buildings has a great signicance

because of the huge energy saving potential. Presentresearches on campus energy efciency [24] mostly focuson energy retrot of existing buildings or development ofnew energy, instead of on optimization of energy saving ofcampus building groups.

The energy consumption of campus building groups hasspecic characteristics compared with other ordinary

building groups [5]. On the one hand, the distribution of

the staff on campus is concentrated in time and space. Inthe daytime, most of teachers and students usually gatherin public buildings like classrooms, libraries and ofces, sothe room temperature in these buildings should beincreased in winter while the room temperature inresidential buildings where there are not many teachersand students at that time should be decreased to someextent. On the contrary, when the students are staying indormitories at night, the room temperature in residential

buildings should be kept at the required standard while theroom temperature in the classrooms, libraries and ofceswhere there are not many teachers or students at that time

should be adjusted to the duty temperature. On the otherhand, the winter vacation in China usually lasts from late-January to late-February and the summer vacation fromearly-July to late-August, during which the conventionalheating and cooling load occurred could lead to less energyconsumption than the design condition. So both the totaldesign load and the peak load of the annual energyconsumption may be reduced because the design load ofthe energy station is determined by the adverse weathercondition which usually appears in vacations. If takingthese characteristics of energy consumption of campus

buildings into account at the design stage, the total annualenergy consumption of campus buildings can be decreased

Received February 19, 2013; accepted April 29, 2013

Dingding TONG, Jing ZHAO ()

School of Environmental Science and Engineering, Tianjin University,Tianjin 300072, ChinaE-mail: [email protected]

Front. Energy 2013, 7(3): 388398DOI 10.1007/s11708-013-0273-7


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effectively, and thus the initial investments and operationcosts of the energy station also can be saved to some extent[6,7].

This paper takes a new campus of Tianjin Universitywhich is under construction as an example to analyze theenergy-saving optimization of campus buildings based on

the specic energy consumption characteristics of campusbuilding groups using energy consumption simulationsoftware. The simulation software can perform an hour-to-hour dynamic energy consumption analysis, so thecharacteristics of the energy consumption of campus

building groups can be represented preferably [8,9]. Inview of the particularity of the energy consumption ofcampus building groups, an energy saving optimizationmode has been proposed and analyzed with the help ofenergy simulation software EnergyPlus [10,11]. It isconcluded that the energy saving optimization strategy

based on the specic characteristics of the energy

consumption of campus building groups can signi

cantlyreduce the total energy consumption and peak load.

2 Methodology

Combining the characteristics of energy consumption ofcampus buildings with dynamic energy consumptionsimulation, the optimization method for the total designload and annual energy consumption of the campus energysystem was proposed.

The campus buildings were simplied as residentialbuildings and public buildings according to their functions.

Therefore, the single residential building model and singlepublic building model [12] were established based on thenational design standard. Besides, the energy consumptionsimulation results of the single building models werecompared with the calculation results of the traditionaldesign method, and applied to the campus building groupfor further prediction analysis.

The conventional building heating or cooling loadcalculation method is based only on the constant designroom temperature, such as 18C in heating season and25C in cooling season during all day. However, the

building load is time-varying, so, constant design tem-

perature cannot t for the varying load, which results inenergy waste. Therefore, the set-point room temperaturemode was proposed to optimize the design load and energyconsumption for the campus energy system compared withthe traditional constant room temperature mode. Xu et al.[13] proposed that intermittent heating and indoor designtemperature improvement could obviously reduce the

building energy consumption. Engdahl and Johanssondiscovered that the optimal control of the temperature ofsupply air could result in a signicantly lower HVACenergy use than with a constant supply air temperature[14]. Based on this theory, the design load and energyconsumption of two single building models in two room

temperature modes were simulated to verify the optimiza-tion result. The simulation results were applied for the

prediction of energy saving of the whole campus aftertesting the accuracy. Because the peak load of residential

buildings and public buildings on campus appears atdifferent times, based on the hourly simulation results, the

peak load as well the energy consumption of the wholecampus could be reduced. The comparison of thesimulation results and the traditional calculation resultsindicated that the optimization was valid.

It is worth noticing that this paper is mainly focus onbuilding load simulation, therefore, the term energyconsumptiononly refers to the thermal consumption.

3 Establishment of single building model

3.1 Establishment of residential building model

Taking a dormitory building on the old campus of TianjinUniversity as the prototype, a residential building modelwas created to serve as the criterion for determination ofthe average energy consumption of residential buildings onthe campus. The prototype building is a 6-storey buildingfacing south without basement, whose construction area is1840.32 m2 with a height of 16.85 m. There is a patio in themiddle section of the building which is used for daylighting and ventilation of some rooms. The thermal

performance parameters of the building model envelopwere selected according to China National DesignStandard for Residential Buildings [15].

The simplied standard building model is shown inFig. 1, while the settings of the space enclosing structurematerials and thermal performance parameters are listed inTable 1.

Fig. 1 Simplied residential building model

Dingding TONG et al. Analysis on energy saving optimization 389


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3.2 Establishment of public building model

Taking a teaching building on the old campus of TianjinUniversity as the prototype, a public building model wascreated to serve as the criterion for determination of theaverage energy consumption of public buildings on the

campus. The prototype building is a 10-storey buildingfacing south with basement, whose construction area is31204 m2 with a height of 43.4 m. The thermal perfor-mance parameters of building model envelop were selectedaccording to China National Design Standard for PublicBuildings [16].

The simplied standard building model is illustrated inFig. 2. The settings of the space enclosing structure

materials and thermal performance parameters are pre-sented in Table 2.

3.3 Settings of other parameters

The energy consumption simulation software Energy-

Pluswas used to analyze the energy saving optimizationstrategy based on the two single building models. Themeteorological data of Tianjin in typical meteorologicalyears [17] were used as input parameters for thesimulation. Other input parameters are tabulated in Table 3.

4 Analysis of load and energy consumptionof single building model at constant roomtemperature

The tradition design method usually calculates the heating

or cooling load based on the constant indoor designtemperature. According to the relevant Chinese buildingdesign standards [18], the indoor design temperature is18 C during heating season and 25 C during coolingseason.

4.1 Simulation results at constant room temperature

4.1.1 Simulation results of load and energy consumption of

the residential building model

The residential building model was simulated at constant

Table 1 Space enclosing structure materials of residential building and thermal performance parameters

Building envelope Materials Thickness/mm l/(W$m1$C1) R/(m2$C$W1) K/(W$m2$C1)

Exterior wall

Lime mortar 20 0.81

2.47 0.40Polystyrene 40 0.042

Aerated concrete blocks 250 0.19

Cement plaster 20 0.93

Roof


2.21 0.45

Lime mortar 25 0.81


Blast-furnace slag 30 1

Polystyrene 60 0.042

Aerated concrete blocks 100 0.19

Floor

Compacted clay 300 1.16

0.35 1.98Crushed stone concrete 100 1.51


Exterior window

Glass 3 0.9

0.40 2.50Air 12

Glass 3 0.9

Polystyrene 10 0.042

Fig. 2 Simplied public building model

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room temperature and the simulation results of the annualenergy consumption were obtained, as demonstrated inFig. 3.

It is observed form Fig. 3 that the annual heating energyconsumption is 486858 MJ. The heating load is mainlyconcentrated at the period from October 20 to April 10 nextyear, while the annual peak load is 68411 W, appearing at

3:00 am on January 6. It is, therefore, deduced that theheating load index of residential buildings is 37.08 W/m2.

The annual cooling energy consumption is 305594 MJ.The cooling load is mainly concentrated at the period fromJune 25 to September 15, while the annual peak load is102755 W, appearing at 4:00 pm on July 5. It is, therefore,deduced that the cooling load index of residential buildingsis 60.17 W/m2.


the public building model

The public building model was simulated at constant roomtemperature and the simulation results of daily energyconsumption were obtained, as displayed in Fig. 4.

It is seen from Fig. 4 that the total annual heating energyconsumption is 9434740 MJ. The heating load is mainlyconcentrated at the period from October 20 to April 10 nextyear, while the annual peak load is 1314887 W, appearingat 3: 00 am on January 6. It is, therefore, deduced that theheating load index of public buildings is 42.14 W/m2.

The total annual cooling energy consumption is6174211 MJ. The cooling load is mainly concentrated at

Table 2 Space enclosing structure materials of public building and thermal performance parameters

Building envelope Materials Thickness/mm l/(W$m1$C1) R/(m2$C$W1) K/(W$m2$C1)

Roof

Cement mortar 20 0.93

2.17 0.46XPS 70 0.042

Reinforced concrete 150 1.74

Lime mortar 20 0.81

Exterior wall

Polymer mortar 6 0.87

1.92 0.52XPS 40 0.042

Aerated concrete 200 0.19

Lime mortar 20 0.81

Exterior window

Low emissivity glass 6 0.9

0.43 2.30Air 12

Low emissivity glass 6 0.9

Floor


0.39 2.53Crushed stone Concrete 60 1.51

Compacted clay 300 1.16

Table 3 List of other parameters setting

ItemsHeating energy consumption simulation Cooling energy consumption simulation

Resi den tial bu ildi ng P ubli c buil ding Res iden tial b uild ing P ubli c bui ldin g

Personnel density/(m2$per1) 4 4

Lighting power density/(W$m2) 20 20

Equipment power density/(W$m2) 20 20

Fresh air volume 1 h1 0.8 h1 50 m3$h1$per1 80 m3$h1$per1

Fig. 3 Annual energy consumption of residential building at

constant temperature



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the period from June 25 to September 15, while the annualpeak load is 2352130 W, appearing at 4:00 pm on July 5. Itis, therefore, deduced that the cooling load index in public

buildings is 81.85 W/m2

.

4.2 Calculation results of load using traditional method

To test the accuracy of simulation results, the heating andcooling load of two single building models were calculatedusing the traditional theoretical calculation method whichinvolves building envelope basic heat consumption,inltration heat loss, invasion heat loss respectively. Thetraditional theoretical cooling load calculation methodinvolves cooling load of the building envelope, heatreleased by indoor heat and humidity source, outdoor aircooling load respectively [19].

The calculation made by using the traditional methodshows that the heating and the cooling load of theresidential building is 46.32 and 63.16 W/m2, respectively,and the heating and the cooling load of the public buildingis 40.93 and 82.54 W/m2, respectively.

4.3 Conclusion of load analysis at constant room

temperature

To check the accuracy of the simulation results, loadcalculation was conducted using the traditional method.The summary and comparison of the calculation results

using the two methods are given in Table 4. It can be seenthat there exist relative errors in the acceptable range,which proves that the simulation results can be consideredto be reliable and effective.

5 Analysis of load and energy consumptionof single building model at set-point roomtemperature

5.1 Strategies for load reduction

The operation of the HVAC system should be based on theuse of the buildings. The special characteristics of thecampus buildings energy consumption are embodied bythe relative centralized distributions of peoples workingtime and locations on the campus and the reduction ofcampus energy consumption in vacations as mentionedabove. So, based on the characteristics of the energyconsumption of campus buildings, when there are notmany teachers or students in certain buildings, the properdecrease of the design room temperature in winter andincrease of it in summer can effectively reduce the energyconsumption of the HVAC system in buildings. As the

national standard mentioned, the practical building opera-tion condition should be taken into account when settingthe indoor temperature in summer and winter. Therefore,the concept of set-point temperature mode is proposed,which means setting another indoor design temperatureduring the time when there are not many teachers orstudents in residential buildings or public buildings. In thisway, the total energy consumption of heating and coolingcan be reduced to some extent [20].

The specic setting values of set-point temperature andcorresponding time are shown as Table 5. Since not manystudents stay at school in the winter and summer vacation,the indoor design temperature of residential buildings is setat 15C and that of public buildings 5C in the wintervacation, while the indoor design temperature of residen-tial buildings is set at 28C and that of public buildings30C in the summer vacation. At other times during theheating season, the indoor design temperature of residen-tial buildings is set at different values with the movementof students at the university. As is presented in Table 5, theindoor design temperature of public building changes from5C (00:0003:00) to 17.5C (07:0008:00) in theheating season. The gradual change of the designtemperature may reduce the excessive load.

5.2 Simulation results of load and energy consumption atset-point temperature

According to the set-point temperature above, the energy

Fig. 4 Annual energy consumption of public building at constant

temperature

Table 4 Contrast of results calculated in two methods

ItemsSimulation results Traditional calculation results

Residential building Public building Residential building Public building

Heating load index/(W$m2) 37.08 42.14 46.32 40.93

Cooling load index/(W$m2) 60.17 81.85 63.16 82.54

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consumption of the two single building models weresimulated by EnergyPlus.


residential building model

The distribution of the hourly heating energy consumption,with the highest heating energy consumptionJanuary 6,is depicted in Fig. 5. It can be seen that in the set-pointroom temperature mode, there is no signicant change inthe peak load. The reason for this is that the peak load inthe constant temperature mode occurs at 3:00 am, insteadof in the period of set-point temperature mode forresidential buildings. So in the set-point temperature

mode, the peak load which is 69651 W still appears at3:00 am and the heat load index is 37.85 W/m2.

The date when the highest annual cooling energyconsumption appears moves from July 5 to June 30 dueto the set-point temperature in the summer vacation. The

distribution of the hourly energy consumption of coolingon that day is illustrated in Fig. 6. It can be seen that thetime for the peak load moves from 4:00 pm to 2:00 pm, andthe peak load changes from 102755 W to 76584 W, thusthe deduced cooling load index is 54.71 W/m2.

In conclusion, the annual heating energy consumptionand cooling energy consumption of the singleresidential building model is 426339 MJ and 166540 MJrespectively.

Table 5 Settings of the set-point temperature

Date Time Setting temperature of the

residential building/C Time

Setting temperature of the

public building/C

The winter vacation for the

heating season

(From January 15 to February

20)

00:0024:00 15 00:0024:00 5

Other days during the heating

season

08:0012:00 15 00:0003:00 5

14:0018:00 15 03:0004:00 8.5

04:0005:00 11.5

05:0006:00 14.5

06:0007:00 16.5

07:0008:00 17.5

22:0024:00 5

Other days 18 Other days 18

The summer vacation for the

cooling season

(From July 1 to August 20)

00:0024:00 28 00:0024:00 30

Other days during the cooling

season

00:0008:00 25 00:0008:00 30

22:0024:00 25 22:0024:00 30

Others 28 Others 25

Fig. 5 Distribution of hourly heating energy consumption on

January 6

Fig. 6 Distribution of hourly cooling energy consumption on

June 30



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public building model

The distribution of the hourly heating energy consumption,with the highest heating energy consumptionJanuary 6,is exhibited in Fig. 7. It can be seen that the peak load in

constant temperature mode occurs at 3:00 am, just in theperiod of set-point temperature for public buildings. So inthe set-point temperature mode the peak load appearing at9:00 am changes to 1407132 W. And the deduced heat loadindex also changes to 45.09 W/m2.

The date of the highest annual cooling energyconsumption moves from July 5 to June 30 due to theset-point temperature in the summer vacation. Thedistribution of the hourly cooling energy consumption onthat day is shown in Fig. 8. It can be seen that there is no

signicant change in the peak cooling load. This is becausethe peak load in constant temperature mode occurs at 4:00

pm, instead of in the period of set-point temperature modefor public buildings. So in the set-point temperature mode,the peak load which is 1641261 W, still appearing at 16:00

pm, and the heat load index is 75.52 W/m2.

In conclusion, the annual heating energy consumptionand cooling energy consumption of single public building

model is 5362360 and 3440570 MJ respectively.

6 Contrast and analysis of simulationresults of single building model in the twomodes

6.1 Contrast and analysis of load simulation

Load index simulation results at constant room tempera-ture (Mode-C) and set-point room temperature (Mode-S)are shown respectively in Table 6. The distribution of theannual heating and cooling energy consumption ofresidential and public buildings are shown in Figs. 9and 10.

It can be seen that for both the residential building andthe public building, the annual heating and cooling energyconsumption are signicantly reduced in set-point roomtemperature. Furthermore, the cooling load index of Mode-S decreases signicantly compared with that of Mode-C,

but the heating load index is even slightly higher than thatin Mode-C. This is because in winter, the indoortemperature of public buildings is set at 5C at night,while in the daytime the indoor temperature is set at 18C,which presents such a large temperature gradient that it

Fig. 8 Distribution of hourly cooling energy consumption on

June 30

Fig. 7 Distribution of hourly heating energy consumption on

January 6

Fig. 9 Annual energy consumption of two modes for residential

building

Fig. 10 Annual energy consumption of two modes for public

building

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takes more energy to raise the temperature from 5C to18C in unit time, making the heating load index of public

buildings in Mode-S slightly larger than that in Mode-C.And that also accounts for the fact that the set-pointtemperature of the public buildings in Table 5 in theheating season increases hourly, just in order to avoid the

excessive load caused by the large temperature gradient.The same is true of residential buildings, but the gap

between the heat load indices in the two modes is smallerthan that of public buildings. The reason for this is that thetemperature gradient of residential buildings caused by theset-point temperature is lower than that of public buildings.Even though the load increases to some extent, the annualenergy consumption decreases to a great degree.

6.2 Contrast and analysis of energy consumption simulation

6.2.1 Contrast of energy consumption of residential

building

As is shown in Fig. 9, the annual heating energyconsumption of the residential building is 426339 MJ inMode-S and 486858 MJ in Mode-C respectively. Theannual cooling energy consumption is 166540 MJ inMode-S and 305594 MJ in Mode-C respectively. It isevident that the monthly heating energy consumption inMode-S is lower than that in Mode-C, especially inJanuary and February, and as well as monthly coolingenergy consumption, especially in July and August; thus itcould be concluded that the indoor design temperatureadjustment can denitely reduce the annual energyconsumption of the residential building.

6.2.2 Contrast of energy consumption of public building

As is shown in Fig. 10, the annual heating energyconsumption of the public building is 5362360 MJ inMode-S and 9434737 MJ in Mode-C respectively. The

annual cooling energy consumption is 3440570 MJ inMode-S and 6174211 MJ in Mode-C respectively. It isapparent that the monthly heating energy consumption inMode-S is lower than that in Mode-C, especially inJanuary and February, and as well as monthly coolingenergy consumption, especially in July and August; thus it

could be concluded that the indoor design temperatureadjustment can denitely reduce annual energy consump-tion of the public building.

6.2.3 Summary and analysis of annual energy consumption

The simulation results are summarized in Table 7. It can beseen that the annual heating and cooling energy consump-tion of the residential building is reduced by 12.4% and45.5% respectively, and the annual heating energyconsumption and cooling energy consumption of public

buildings is reduced by 43.1% and 44.3% respectively. The

reason for the less reduction of total annual heating energyconsumption in residential buildings than public buildingsis that some of the dormitories still need heating in thewinter vacation, so the set-point temperature shouldnt beset at a very low degree, and therefore, the energy-savingeffect is not as obvious as that of public buildings.

7 Analysis of load and energy consumptionof campus building groups

7.1 Prediction of load and energy consumption of campus

building groups based on energy saving optimization method

7.1.1 Optimization method

According to the simulation results in Figs. 58, the peakloads of two kinds of buildings appear at different times.The simulation results of the single building model atset-point emperature can be applied to campus

Table 6 Contrast of load index in two modes

ItemsMode-C Mode-S

Re side nti al bu ildi ng P ubli c bui ldin g Resi den tial buil ding Pub lic b uild ing

Heating load index/(W$

m2) 37.08 42.14 37.85 45.09

Cooling load index/(W$m2) 60.17 81.85 54.71 75.52

Heating energy consumption/MJ 486858 9434740 426339 5362360

Cooling energy consumption/MJ 305594 6174211 166540 3440570

Table 7 Total load of campus buildings in optimization method

Items Cooling load/W Heating load/W Cooling load of building group/W Heating load of building group/W

Residential buildings 0 965370716213330 31368771

Public buildings 16213330 22341226



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building groups that include both public and residentialbuildings to obtain the total load and energy consumption[21]. By adding the load hour by hour, the load andenergy consumption of campus building groups can beobtained.

7.1.2 Prediction of total load in optimization method

The new campus is located in Tianjin in North China. Thetotal building area of the public buildings is 495430 m2 forheating and 214700 m2 for cooling. And the total buildingarea of residential buildings for heating is 255025 m2.Since there is no central cooling system in the residential

buildings, the cooling load of residential buildings can beignored for energy station design. Based on these area dataand simulation results of hourly heating and cooling loadindex in unit area of the two single models by theoptimization strategy, the peak load of residential and

public buildings were obtained. It is known that the heatingload and cooling load of all residential buildings are9653707 W and 0, and the heating load and cooling load ofall public buildings are 22341226 and 16213330 W. Then,the peak load of the whole campus building groups canalso be calculated by adding the load of residential

buildings and that of public buildings respectively, asshown in Table 5. It should be noticed that the heating loadof the building groups is not equal to the sum of two kindsof buildings, which was explained in detail in 6.3.

7.1.3 Prediction of annual energy consumption in

optimization method

Similar to the load calculation, the annual energyconsumption of campus building groups in optimizationmethod were calculated based on campus area and thesimulation results of hourly heating and cooling energyconsumption in unit area of the two single models. Theresults show that the annual heating energy consumption is138043165 MJ and the annual cooling energy consump-tion is 23672917 MJ, whose distribution is shown inFig. 11.

7.2 Prediction of total load based on traditional calculation

method

According to the heating and cooling area and the loadindex calculated using traditional method, multiplied bythe heating and cooling area, the load of the campus

building groups were obtained. That the heating load andthe cooling load of building groups is 32090708 and17721338 W.

7.3 Contrast and analysis of the results of load prediction

The results of load prediction above are summarized inTable 8. It can be seen that both the cooling load and theheating load of campus building groups when using theoptimization method are obviously less than that whenusing the traditional method. This is because the daily peakload of different types of campus buildings appears at

different times. The speci

c hourly heating load onJanuary 6 (the day the annual peak load appears) isshown in Fig. 12. It is observed from Fig. 12 that the peakload of residential buildings (9653707 W) appears at 3:00am and that of public buildings (22341226 W) appears at9:00 am.

By adding the heating load of all the buildings, the peakload of campus groups is found to appear at 8:00 am(31368771 W), neither 3:00 am nor 9: 00am, which is lessthan the sum of two buildings in their peak time (22341226W+ 9653707 W = 31994933 W). In addition, since thereis no central cooling system in the residential buildings onthe campus, the peak clipping of total cooling load cannot

be obtained.

Fig. 11 Annual energy consumption of campus building groups

Table 8 Contrast of load prediction in two methods

Items Traditional Optimization method

Heating load/W 32090708 31368771

Cooling load/W 17721338 16213330

Fig. 12 Daily energy consumption of two modes on January 6

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7.4 Contrast and analysis of the results of annual energy

consumption prediction

By adding the annual energy consumption of residentialand public buildings, the annual energy consumption of thewhole campus building groups was obtained. The

comparison of the heating energy consumption of twomodes (which is 138043165 and 206390476 MJ respec-tively) shows that the optimization method can save33.12% of energy. The comparison of the cooling energyconsumption of two modes (which is 2327291 and42484830 MJ respectively) shows that the optimizationmethod can save 45.22% of energy. The distribution of thetotal energy consumption of building groups is shown inFig. 13.

As it can be seen that the annual heating and coolingenergy consumption using the optimization method isobviously lower than the values without optimization,which proves that the optimization strategy is effective to alarge extent.

8 Conclusions

The idea of energy-saving optimization for campusbuilding groups has been proposed based on the energyconsumption characteristics of campus buildings, and the

feasibility of the idea has been veried through speciccase analysis, which creates a new research view on theenergy-saving strategy of campus building groups.

Based on the energy consumption characteristics ofcampus buildings, the set-point temperature mode was

proposed. Compared with the traditional theoreticalmethod to calculate the load, the dynamic simulationmethod is the foundation to realize the optimizationstrategy under the help of energy simulation software

EnergyPlus.The comparison indicates that applying theoptimization strategy can reduce the annual energyconsumption of campus building groups and save the

operation cost of the HVAC systems. In respect of loadpeak clipping, the peak load of two types of buildinggroups occurs at different times, by which the peak loadclipping can be achieved, and the total campus designedload can be reduced to save the initial investment.

The optimization strategies are based on the character-

istics of the energy consumption of campus buildings,which is common on university campuses regardless of thetype of the university, the number of the students, and theregion where the university is located. Thus the optimiza-tion strategy can be widely used in campus energy

planning. With this optimization strategy, the initialinvestment and operation cost of heating and coolingsystems can be reduced effectively.

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