The Online Journal on Power and Energy Engineering (OJPEE) Vol. (2) – No. (3)

Reference Number: W10-0053 223

Energy Saving Through Smart HomeEng. Inji Ibrahim Attia Prof. Dr. Hamdy Ashour

eng_inji@yahoo.com hashour@aast.eduElectrical Department and Computer Engineering, Arab Academy for Sciences and Technologies,

Alexandria, Egypt

Abstract-Energy saving is considered as one of the mostimportant issue affects the consumers, power systemquality and the global environment. The high energydemanded by home appliances, air conditioning andlighting makes homes to be considered as one of the mostcritical area for the impact of energy consumption. Smarthome technology is a good choice for people not only careabout security, comfort but energy saving as well. In thispaper, a smart home energy management technique basedon a set of sensors is presented. It minimizes the domesticenergy waste and can be adapted according to the userhabits. A proposed scenario is reported of daily routineand performed by 16 steps. Three assumptions of varyingthe time spent in each step according to different behaviorare examined. The effectiveness of the proposed set isshown based on a static correlation between the powerconsumption and saving.

Keywords- Energy saving, smart home, occupancysensor.

I. INTRODUCTION

Smart home technology started for more than a decade tointroduce the concept of device and equipment networking inhouse. Smart home contains internal network and intelligentcontrol on different home's services. The internal networkcan be built via wire or wireless communication techniquebetween sensors and actuators .The intelligent control meansthe entire house is managed or monitored by internet services[1]. Smart home is the integration of technology and servicesthrough home networking for a better quality of living.Integrating the home services as shown in figure 1 [2] allowsthem to communicate with one another through the homecontroller, thereby enabling single button to control thevarious home systems according to preprogrammedscenarios or operating modes [3].

Smart homes have the potential to improve home comfort,convenience, security and energy management. Moreover itcan be used for elder people and those with disabilities,providing safe and secure environments. A smart home is agood choice for people caring about security, health, energysaving and convenience. The benefits of smart technology athome could be apparent to everyone if this potential isfulfilled. This is when the system will be able to protecthabitant's privacy and having low cost. [4]

On the other hand, smart home is somewhere difficult to beimplemented due to its high initial cost. Anotherdisadvantage is that elder are more reluctant to try newthings or change their way of thinking about the risk of

losing privacy due to their feeling of being monitored all thetime [5].

Figure (1): .Smart home Integration services

In this paper a home energy management technique basedon a set of sensors is presented that can be adapted accordingto habitant's behavior. Section I is a brief definition of smarthome and its benefits. Section II describes how smart homecan reduce the energy consumption via managingintelligently the devices by controlling the lighting, airconditioning (HVAC) and other home appliances. In sectionIII, a case study is reported. Section IV shows the proposedscenario. Section V explains the calculations and thenumerical results to provide examples of possible advantagesachievable with the proposed system in term of energyconsumption.

II. ENERGY MANAGEMENT

One of the major benefits of smart home to consumers istheir ability to incorporate energy management featuresthrough lighting, air conditioning and home appliances.

A. LIGHTINGThe lights in a smart home can be turned on and off

automatically based on occupancy sensor. As example , whena person enters a room in the day time, the system will openthe drapes instead of turning on the lights, but at night itwould make sure the lights came on and they turned off whenno one is in the room hence waste of energy can be preserved.

B. AIR CONDITIONINGAn appropriate placement of temperature sensors and the

use of heating and cooling timers can reduce the energy used

The Online Journal on Power and Energy Engineering (OJPEE) Vol. (2) – No. (3)

Reference Number: W10-0053 224

and hence saving money and also the house can set to turn offair conditionings when no one is in the room.

C. HOME APPLIANCESSmart homes can even go further in energy management by

keeping track of the energy usage of each and every appliancein the house. The smart house controllers could schedule theoperation of heavy power consuming appliances (such asdishwashers and electric water heaters) to take maximumadvantage of off peak electric rates. [6]

III. CASE STUDY

Figure 2 shows the apartment which consists of 6 rooms.Their dimensions are listed in table 1.

Figure (2): Layout of apartment indicating the distribution ofsensors used (Sweet Home 3D software)

RoomsEntrance hallBedroomRoomBathroomDiningRoom

Kitchentotal

Area/m:s2548161616129

Table 1 simulated home area

The sensors are distributed into home in order to provideaccurate information about the occupant's location andactivities. Occupancy sensors are used instead of motionsensors because last ones are preferred for security rather thanfor building and lighting control. They respond only tomoving objects, so if an individual in a room working at adesk, motion sensors will often cease to see him [7]. Figure 3describes examples of the two types of occupancy sensorsdistributed into the model .The first one is a passive infrared(PIR) sensor that automatically control lights by detecting theheat from occupants moving within an area (900 square feet)to determine when the space is occupied with a low cost [8].The other, is used to adjust the temperature and lighting levelaccordingly for better energy management with a high cost[9] .Table 2 illustrates the number of sensor used per roomand their distribution through the apartement is shown infigure 2.

Figure (3) (a): Occupancy sensor for lighting(b): Occupancy sensor for lighting and HVAC

Sensor typeTargetHallBed-room

Livingroom

Bath-room

Diningroom

KitchenTotal

LightControl

1051013

Light+HVAC

0110103

Table 2 list of sensor per room

IV. PROPOSED SCINERIO

Scenario management allows users to define a set ofbehavior rules. A lot of sequences can be implementedaccording to the habitant's age and its social status. A scenariofor an elderly house holder who has a high risk of fallingdown is proposed in [11]. Furthermore, a scenario for anindividual gets back at evening and leaving in the morning issuggested in [12]. In this paper a scenario for a man and hiswife getting back home and leaving in morning is presented.

TimeWifeHusbandActionWrong Behaviors

1At 14

o'clockBack homeHall is On

214-14:30Enters

bedroomBedroom is On

Hall is left on for 30minutes

At 14:30Hall is Off

14:30-15Enters

bathroomBathroom is On

Bedroom still OnBedroom is left on for

30 minute sAt 15

o'clockBathroom bedroom

Off

415-17Enterskitchen

Kitchen is On Livingroom is On

Living room is left onfor 2 hours

At 17o'clock

Husbandbackhome

Hall is On

617-17:30waiting herhusband in

living

He entersbedroom

Living is OnBedroom is On

At 17:30Hall is Off

717:30-18

stillwaiting herhusband in

living

He entersbathroom

Bathroom is OnBedroom still On

Living is On

Bedroom is left on for30 minuets

At 18o'clock

Bathroom. BedroomOff

818-18:30Enterskitchen topreparelaunch

He iswaitingher intoliving

Kitchen is On Diningis On Living is On

Dining room is left onfor 30 minutes

918:30-19They enter the diningroom for launch

Dining is On

1019-20Enters thekitchen

waiting herinto living

room

Kitchen is On Diningroom still On Living

room is On

Dining room is left onfor 1 hour

At 20o'clock

Kitchen Dining roomLiving room are Off

1120-21They enter bedroomBedroom is On

The Online Journal on Power and Energy Engineering (OJPEE) Vol. (2) – No. (3)

Reference Number: W10-0053 225

1221-23They enter living roomLiving is On1323-24Enters the

kitchen topreparedinner

waiting indiningroom

Kitchen is On Diningis On Living room is

On

Dining Room is lefton for 1 hour

1424-24:30Enter the dining roomfor dinner

Kitchen is Off Diningroom is on

1524:30-1Enters thekitchen

Back toliving room

Kitchen is On Diningstill On

Dining Room is lefton for 30 minutes

At 1o'clock

Dining room KitchenLiving are Off

161-2Back to bedroom tosleep

Bedroom is On

At 2o'clock

All rooms are Off

Table 3.Proposed scenario

Actually, the human habit cannot be controlled because itchanges according to our life so the change of powerconsumption is related to the change of numbers of hoursspent in each room and thus saving in KWH. The previousscenario listed in table 3 is adjusted three times and table 4represents the number of hours spent in each room to realizeeach step of the 16 steps shown before during different habitsassumptions.

ScenarioHour/stepHour/stepHour/stepSteps1st assumption2nd assumption3rd assumption

111120.50.50.530.50.50.54l0.52s0.50.50.560.50.50.570.50.50.580.50.50.590.50.50.5

101.51111111123221300.511400.50.51501.50.51600.51

Table 4 Time spent in each step

V. NUMERICAL RESULTS AND DISCUSSION

The whole apartment is simulated using Sweet Home 3Dsoftware according to the dimensions shown in table 1. Eachroom is simulated using DIALux software to calculate thepower required for lighting. The air condition capacity wascalculated according to the Canadian standards.[12] Thehome appliances capacity was calculated according to theU.S. Department of Energy's Office for Energy Efficiencyand Renewable Energy (EERE).[13]. Figure 4 shows theliving room as an example showing the number of lamps andtotal power required for lighting. Table 5 shows the powerconsumption of each room for lighting, air conditioning andhome appliances in KWH/Day.

Figure (4): Living room lighting luxes

HallBedroomLivingRoom

BathroomDiningRoom

KitchenTotal

Area/m282548161616129Light

KWH/day0.0880.1760.2780.1330.0880.1330.896

HVACKHB/day

02.273.5602.1107.94

HomeAppliancesKWH/day

00.110.16001.2001200.2

Table 5 power consumption per room

Table 6 is a comparison between the previous assumptionslisted in table 4 showing in each, the power consumption,percentage saving in power and consequently in electricitybill.

The results shown in figure 5 confirm that the proposedenergy management smart home can be adapted each time theoccupant's habit change and thus the saving target.

1st assumption2nd assumption3rd assumptionTotal

KWH/month935.311858.231549.08

Total savingKWH/month

224.13379.47619.2

% saving/month23.96 %20.42 %38.58 %Saving in LE %61.36 %27.44 %48.82 %

Table 6 Comparison between the different assumptions

Figure (5): The daily consumption, percentage saving inpower and in electric bill for the previous trials.

The Online Journal on Power and Energy Engineering (OJPEE) Vol. (2) – No. (3)

Reference Number: W10-0053 226

One of the case study objectives is to evaluate the relationbetween the power consumption and the saving. ThusCorrelation statistical method is suggested for calculation.[14] A correlation coefficient is a single number thatdescribes the degree of relationship between two variablesthat ranges from -1 to +1, indicating perfect negativecorrelation at -1, absence of correlation at zero, and perfectpositive correlation at +1. Table 7 indicates the relationcalculated between two random variables (X, Y) according tothe correlation coefficient (r) ant its meaning. [15]

Relationship Between X and Yr = +1.0 Strong - Positive As X goes up. Y always also goes upr = + 0.5 Weak - Positive As X goes up: Y tends to usually also go up

r = 0 -No Correlation - X and Y are not correlatedr = -0.5 Weak - Negative As X goes up: Y tends to usually go downr = -1.0 Strong - Negative As X goes up. Y always goes down

Table 7 Correlation coefficient meaning

Figure 6 shows that the relation between the powerconsumption (A) and the saving in KWH (B) is weak positiverelation (r=0.55). This means that the great increase in powerconsumption should not be accompanied by a great increasein power saving because the system could be adaptedaccording to occupant's behavior.

Figure (6): (a): Correlation Coefficient(b): Correlation between monthly power consumption

and saving

Figure 7 shows that the relation between the powersaving(C) and the saving in cost (D) is strong positive relation(r = 0.99). This means that the increase in power saving isaccompanied by a great increase in cost saving as shown intable 6.

Fig (7): (a): Correlation Coefficient(b): Correlation between saving in power

consumption and cost

The correlation coefficient between (A &B) and (C&D) arecalculated using Excel software and then illustrated in figure6 and 7.

Table8 represents the daily power consumption and thesaving in power daily and monthly showing also the saving inelectricity bill for the 3rd assumption.

TotalKWH/Day

TotalKWH/Month

TotalKWH/Year

Budget inL.E.

Electric PowerConsumption

51.636 1549.08 18588.96 515.08

Electric PowerSaving

20.064 619.2 7430.4 284.178

PercentageSaving

38.85% 39.95% 39.97% 44.82%

Table 8 .Third assumption calculations

Table 8 records that only one family could save about 620KWH /month. Taking into consideration that Egypt consist ofabout 17 million family according to the statistics of2006,thus a total energy saving could be about 3000 MWwhich is equivalent to 3 power stations each is formed of 3units and each unit capacity would be 300 MW.

On the individual level, this family saves about 230L.E/month which is equivalent to 2770.824 L.E/year. Thesensors cost about 570$ and communication network about1000$ thus a total cost would be 1570$ which is equivalent toabout 8949 L.E. Thus this initial cost would be covered in3years. For sure, these values depend on occupant's habit asshown through the different assumption.

The Online Journal on Power and Energy Engineering (OJPEE) Vol. (2) – No. (3)

Reference Number: W10-0053 227

VI. CONCLUSION

In this paper a home energy management is presentedbased on a set of sensors to minimize the domestic energywaste according to human habits. A proposed scenario issuggested for daily routine to maximize the occupant's energysaving. The home power consumption is calculated and therooms lighting are simulated using DIALUX software. Theresults are satisfactory and indicate that smart home based ona set of sensors could perform energy management which isnot only an individual need but economical target. Therelation between the power consumption and saving(power/cost) is illustrated using Excel. A strong relationbetween the saving in power and saving in cost is obtained.

VII. REFREANCES

[1] B. Kim, S. Hong, Y. Jeong and D. Eom, The Study ofApplying Sensor Networks to a Smart Home, PowerSystems Computation Conference (PSCC), Sevilla, 2428June 2002

[2] http://get-fuse.com/home automation.php[3] R. Robles and T. Kim Applications, Systems and

Methods in Smart Home Technology: A Review,International Journal of Advanced Science andTechnology, Vol. 15, February, 2010.

[4] C. Bjorkskog , Human Computer Interaction in SmartHome, available on:http://www.hiit.fi/~oulasvir/58307110/smarthomes.pdf

[5] http://www.id.carleton.ca/ web/ student %20 papers%20PDF/ inclusive %20technology / Isaza Shelton_Diana_ SeminarPaper08.pdf

[6] M. Kawidean, M.Kassim, design development andimplementation of smart home systems using RF andpower line communication , The 2nd NationalIntelligent Systems And Information TechnologySymposium (ISITS'07), Oct 30-31, 2007,ITMA -UPM,Malaysia.

[7] http://www.daintree.net/downloads/whitepapers/occupancy.pdf

[8] http://www.smarthome.com[9] http://www. bchydro. com/[10] http://www.tiresias.org/research/guidelines/smart hom

e.htm[11] Y. Rahal, H. Pigot, and P. Mabilleau, Location

Estimation in a Smart Home: System Implementationand Evaluation Using Experimental Data, InternationalJournal of Telemedicine and Applications, Vol. 2008.

[12] http://oee.nrcan.gc.ca/publications/infosource/pub/roomaircond/pdf/AC e Worksheet! 04.pdf

[13] http://www.energysavers.gov/your home/appliances/index.cfm/my topic=10040

[14] http://www.socialresearchmethods.net/kb/statcorr.php[15] http: //www. sixsi gmaspc. com/ dictionary/

correlationcoe fficient-scatterplot.html