Design and Implementation of User Interactive Wireless Smart Home Energy Management System

Transcription

1 Design and Ipleentation of User Interactive Wireless Sart Hoe Energy Manageent Syste Aryadevi Reanidevi Devidas 1, Subeesh T. S 2, Maneesha Vinodini Raesh 3 Center for Wireless Networks and Applications Arita Vishwa Vidyapeetha Aritapuri, Kolla, India 1aryadevird@a.arita.edu, 2 p2wna11019@students.arita.ac.in, 3 aneesha@a.arita.edu Abstract Electricity usage is increasing day by day due to the changing life style of hoe user and an increase in appliances in the hoe area network. Our proposed hoe energy anageent syste for hoe users will onitor, anage and control the usage of hoe appliances, by reducing the onthly electricity bill The proposed wireless architecture consists of an appliance control device called Wireless Enabled Electricity Manager (WEEMAN) installed next to a switch board or every device/ appliance in a roo. The central node called sart eter runs an algorith called Availability Based Energy Manageent algorith. This algorith learns about the previous usage patterns of the appliances, collects real tie power consuption of appliances fro WEEMAN to generate efficient energy load patterns. The highpoint of the algorith is that it gives an option for the user to set their onthly current bill and pro-actively control the operation of all the appliances according to the aount. We have developed a hardware test bed consisting of WEEMAN connected to soe selected appliances and a sart eter to control every WEEMAN. Keywords Hoe Energy Manageent, Hoe Area Network, Wireless Sensor Network, Sart Gird I. INTRODUCTION The electric power consuption (Kwh) in India was 689,537,000,000 as of 2011 and earlier it was 156,400,000,000 in the year 1990[5].The ain reason for this is due to an increase in electronic as well as electrical appliances in the hoe area network (HAN). When we copare the energy usage between 1990 to 2011, we can hardly find a hoe without a TV, washing achine, refrigerator etc. Major electricity consuption aong hoe appliances are lighting devices, that uses about 30 percent of electrical energy followed by refrigerators, fans, and electric water heaters etc. Figure 1 show coparison of electricity usage of various house hold appliances over the past 5 years and expected proportionate deand for power supply in the coing years. As per the statistics in figure 1, we can expect a huge deand for power supply fro the hoe environent especially for entertainent and heating/cooling appliances. There is a huge gap between the available and generated power supply, due to factors such as global waring and odernization. Utility copanies have to search for alternatives to avoid harnessing natural resources. Also, using natural resources is not a long ter solution since we have a very liited resource as well as a huge cost of converting the resource into usable electrical energy. So there is an increased need to anage, balance, and use power supply. Figure 1.Year wise energy consuption of appliances [5] The ain challenge in a sart hoe is to ipleent a Hoe Area Network (HAN) solution to interconnect appliances and offer sart services for energy anageent, cofort, and autoation. Energy anageent has pivotal significance aong those services. This energy anageent technique could be used during different ties for different appliances based on consuers behavior. The table shows the usage of appliance based on different ties on a sunny weekday. There will be soe changes for the weekend days, ainly during 10 a 4 p. Table 1 shows that the need of an appliance changes based on the consuers nature of work, behavior and teperature. For exaple, teperature changes ay affect (increase/decrease) the usage of heating /cooling appliances. If it is a baly day the usage of cooling appliances is higher and on a cold, rainy day heating appliances would be used. Power anageent technique observes these facts for proper scheduling of hoe appliances. This anageent technique keenly observes teperature changes by incorporating sensor odule to sense the real tie teperature as well as light values to ake acceptable decisions. The proposed power anageent syste works in a wireless esh network with WEEMAN as a node.the availability anageent algorith is designed to stay close to /13/$31.00 c 2013 IEEE 626

2 the user and learns the coon behavioral patterns inside the house irrespective of personal identity. Table 1. Tie based usage of appliances [2] The algorith will autoatically learn the iportance of an appliance at hoe, based on frequent usage Also it groups the appliances based on the different priority set by the user and algorith. The key ephasize of the anageent schee is that it proactively controls all appliances based on the option given by the user and budgets the aount for the following onth s electricity bill. This feature will ainly focus on those consuers who want to anage their onthly budget. This sart architecture helps the consuer in decreasing the electricity bill as well as enabling the utility copany to anage the discrepancy in the generated and deanded electric power. The proposed architecture enables consuer participation in electricity anageent using wireless counication devices. It gives exibility to the consuers in switching on a high priority load by switching o one or a set of low priority loads without a ecting the cofort level of the consuers. The IEEE [6] low rate wireless personal area network is one of the protocols ost suitable for wireless sensor networks. This has MAC/PHY [7] layers of IEEE , that has a protocol for well-known sensor nodes, e.g. MICAz TelosB otes, etc. Its ost frequently cited characteristics are low power consuption, long battery life, low product cost, and open standards. Mesh networking of ZigBee [8] also akes IEEE attractive in hoe autoation. The paper is organized as follows: Section 2 describes the work related to this field. Section 3 and 4 includes the syste architecture and the design of the algoriths. Section 5 discusses the experientation setup followed by conclusion. II. RELATED WORKS Jinsung Byun and Sehyun Park describes a self adapting intelligent syste [1] created with ainly two coponents called Self adapting Intelligent Sensor (SIS) and Self adapting Intelligent Gateway (SIG).The Wireless Sensor Network s life tie and syste resource anageent can be iproved with the help of the proposed Energy Efficient Self Clustering Network (ESSN) and the Node Type indicator Routing protocol (NTIR). In order to reduce the service creation and execution tie of the network, SIS collects the sensor values and with the help of the ebedded adaptive rule based engine it develops the control signal directly according to the rules. Green Hoe Energy Manageent Syste (GHEMS) [2] is introduced as a technology to reduce and anage hoe energy use. They clai that the feedbacks regarding the energy usage by consuers are the best solution to reduce the total energy use. Hoe appliances are connected to the electrical outlets. GHEMS deterines the power and energy consuption of hoe appliances and convey the easured power and energy inforation to the hoe server through ZigBee network. The HEMS in the hoe server collects the energy consuption value fro the electrical channels and shows hourly, daily, weekly, and onthly energy usage of hoe appliances. The electrical outlets deterine the status (Switch on, Switch off, Stand by) of the hoe appliances. HEMS which operates in the hoe server deterines the gathered tie of standby ode and noral ode. Then it infors the user regarding how long the device was used in the noral ode and related power consued by that device during that tie. The user thus receives the frequency and energy usage of each hoe appliance. Using the accuulated data fro HEMS, the user can deterine unnecessary energy waste in the standby ode and the operational energy used in the noral ode. HEMS also pops up a coparison chart of hoe appliances that is siilar to other appliances. The user receives energy profile reference fro energy portal service. The efficiency of the hoe appliances are very uch related to the quality of supply voltage we are putting into the device. The Hoe Energy Manageent (HEM) [3] solution can offer efficient energy and real tie budgeting inforation that enables users to optiize hoe energy use. Users can achieve visibility into household energy usage and anage how energy is utilized with the HEM. The proposed work [4] is to odel an energy based context, which is basically in relation to huan context and their power consuption. It first analyzes the relationship between the context and each of its associated appliances and later each of its capability to generate energy saving schees. Energy Saving service in a sart hoe can often be attained by turning off an appliance that is not presently used or by turning the working ode of an appliance to a ore energy proficient one. This ethodology saves alost 25% of energy by eradicating energy-waste situations at hoes every day. In an energy based context power consuption of a device is categorized into explicit and iplicit power consuption. Explicit power consuption is closely related to huan activity with a device. Iplicit power consuption refers to appliances that are not directly related to huan activity. In the above research work [1] the coplexity of the syste increases with an increase in coponents such as SIG and SIS and these coponents are needed in every roo. GHEMS [2] shares every hoe s appliances usage pattern to the external world without taking proper security easures and by doing so the usage pattern of appliances are vulnerable to security breaches.. But our proposed syste uses WEEMAN based on the nuber of switch boards in a roo to control all appliances inside HAN International Conference on Advances in Coputing, Counications and Inforatics (ICACCI) 627

3 III. ARCHITECTURE DESIGN In today s electrical grid, power wastage has been so high due to the careless handling of hoe appliances by consuers. One of the ajor reasons for this issue is due to a lack of a syste for coordinating the load operation and for controlling the energy consuption. The wireless devices are connected to each and every load for onitoring and controlling the consuption at hoe. The ain coponents of this architecture as shown in the Figure 2 are sart eter and WEEMAN. In HAN, whenever a load is switched ON, it tries to counicate with the sart eter. Every load using the proposed hardware [WEEMAN] counicates with each other and with sart eter. In our hoe area network, the sart eter works as a aster node and it is used to collect the consued power fro all other devices and also calculate the total power utilized by the resident. The sart eter as shown in the figure 4 also functions as an interface between the resident and the utility copany. Fro the utility copany, it will collect the inforation of current Tie of Use (TOU); depending on TOU, sart eter will calculate possible operating tie for each device based on an algorith called availability based anageent algorith. consued power value. The WEEMAN will control the appliance using relays and relay driver IC as per the decision fro the central unit called sart eter. Figure 3.Wireless Enabled Electricity Manager Figure 2.Hoe Energy Manageent Architecture A. WEEMAN [Wireless Enabled Electricity Manager] WEEMAN will be placed in every roo beside every switch board and we are able to connect eight devices siultaneously. As shown in Figure 3 the hardware contains sensors (ACS 714) to sense the load currents there by calculating the power drawn by every appliance in the PIC icrocontroller. The PIC will give a unique notation to every appliances attached to it and wirelessly send this unique id and power consuption value to the sart eter using low power 2.4 GHz odule CC2420 [7] zigbee transceiver. During the tie of installation consuer will give the nae of the appliance to WEEMAN and later it will be counicated to sart eter. Every WEEMAN will be in direct range with sart eter and will update the sart eter when ever consuer uses any appliance or if there is a change in Figure 4.Workflow diagra B. Avilabilty Based Manageent Algorith The hoe energy anageent syste generally has different functions such as controlling the energy consuption at peak ties, updating custoers about the real tie power consuption inside the hoe area network, and helping the custoer to schedule the operation of their appliances based on real tie pricing fro the utility copany. The proposed algorith enhances the existing hoe energy anageent feature and helps the consuer to supervise their onthly budget. The algorith collects input fro consuers in the for of onthly current bill and controls the operation of all the appliances in HAN. There will be a iniu aount that the consuer can enter as their electricity budget. This International Conference on Advances in Coputing, Counications and Inforatics (ICACCI)

4 depends on the nuber of appliances at hoe and the connection type. The algorith always provides iportance to user priority by analyzing the usage of appliances by the consuer. The algorith scrutinizes the user s priority by categorizing the appliances based on the frequency of use per onth, the ties of day the appliance is used and the consuer s preference. The utility copany can also benefit fro the algorith in case a user utilizes extra power supply that is beyond their liit fro the grid. The sart eter notifies this to the utility copany, and they can ipose a penalty for extra power consuption. The operation of the algorith is basically the counication between different odules which is explained using a flow chart in figure 5. B.1. User interrupts The odule User Interrupts will be activated whenever a user gives inputs and it passes the inforation to evaluation and decision aking odules. The ain user input the algorith receives is the aount of onthly electricity bill. If the consuer has not set any aount, then the algorith seeks the previous onth s electricity bill aount. The user can set a priority for each appliance and set of desirable load fro sart eter also through this odule. The algorith gives consuer the adinistrative power and he or she can always bypass the algorith s decision in an eergency with the help of this odule. When the user inputs the aount, the algorith calculates the total nuber of energy units for a onth (u ) that the user can utilize based on the real tie pricing fro the utility copany. Later the units will be sent to the evaluation odule. Whenever WEEMAN and sart eter counicate with each other, that data is updated in real tie. B.2. Real tie data handling The updated real tie data anages essages fro WEEMAN; the contents of the essage will be WEEMAN id, appliance id, power value of the appliance and nae of the appliance. WEEMAN will send a essage to sart eter whenever there is a change in the power value. Also at the tie of initial set up, WEEMAN will also send inforation about the priority of different appliances set by the user. When sart eter receives this essage, it will update the database with field s appliance id, power value, switch off/on tie stap and the status (on/off) and activates the decision aking odule. This database will be useful to analyze the usage pattern of the appliance and the tie of use as a future reference. The odule will also interact with the external utility copany to collect inforation regarding real tie pricing. B.3. Evaluation Evaluation regarding type casting of hoe appliances in to different categories (Continuous, Reserved, User priority and Delayable) will be done periodically. Evaluation odule perfored periodically in every day and later perfored based on the behavioral change in the consuer towards the usage of appliances in their daily life. The assuption is that we have already learnt about the previous onth s usage pattern of all the appliances and the algorith knows about every appliance inside the HAN. The appliances are divided into regular load, reserved load, and user priority load. The algorith assues that every load in the HAN will be categorized in either of the above classification. If an appliance sees to be operating above 80 % of days in a onth, then the algorith groups it as regular load. Siilarly, appliances that are being used between 40 % - 80% / day then it is grouped as a reserved load. For exaple, soe user will operate appliances such as a vacuu cleaner, grinder etc only on soe specific day or days in a week. The algorith will store that data in eory and we receive the onthly-allotted units fro the user interrupt odule. The onthly-allotted units (u ) are again divided into daily-allotted units (u d ), continuous units (u c ) and reserved units (u r ). Allocation depends on the onthly average operational tie (ot avg ) of specific days (Sunday, Monday,.Saturday) based on the previous onth s usage pattern of the appliances and the nuber of regular and reserved loads on that day. The algorith reserves soe units fro the regular and reserved loads for the day and it is called as reserved units (u r ). In case the user doesn t use the daily or reserved units for a day then it will be added into free units (u f ) at the end of every day. User can take soe units as credit fro the following days during eergency conditions in the for of borrowed units (u b ) if there are no free units are available. B.4. Decision aking If any user switches on any appliance, real tie data anipulation odule will infor that to the decision aking odule with appliance id. The odule will check the category of newly arrived appliance in the database. If the appliance is classified as a regular or reserved load on that day then the algorith perits to switch on the appliance up to the expected operational tie for the day. The algorith will decreent the units fro the allotted reserved units based on consuption. If the appliance is not a reserved or regular load for that day then the algorith will check for free units in the account. The algorith allows the appliance to work up to the axiu allotted free units if there is availability. During circustances such as the appliances are arked as user priority load and there are no free units available, the algorith will search for any appliance, which is operating at the oent that can, start working later. The algorith will delay the operation of such appliances whose power consuption is siilar to the new appliance. It will help the algorith to incorporate the real tie deand for an appliance, without disturbing the unit s distribution. In case there is no such delayable load at that oent, the algorith gives an option to the consuer to operate the appliance on deand instantaneously by switching off soe 2013 International Conference on Advances in Coputing, Counications and Inforatics (ICACCI) 629

5 other loads, whose deand is less copared to the current appliance on deand. It will also help users to keep the power consuption of the residence within the stipulated liit. The algorith waits for the user to select appliances to switch off fro the display screen to accoodate their deanded load. If the user does not want to switch off any appliance, then the algorith accepts the user s deands and borrows soe units fro the upcoing days to eet the extra deand. The units will be borrowed only based on the user s perission and depending on the availability of free units in the subsequent days of the previous onth. Later the credited units will be nullified fro the free units. At the end of the day free units will be updated if the consuer has not used the reserved units for that day. P avg = Average power of a hoe appliance in KW t avg = Average onthly opertational tie of an appliance D I U = ot * p avg avg d = 1 i = 1 where i and d are the nuber of appliances and nuber of days in a onth respectivel y (2) The algorith always cross checks the values between and range ofu.ie U u, akes sure that u value is in within a certain U Δu u U +Δ u (3) If u is not coes in range of U then algorith gives a warning essage to the consuer that appliances inside the HAN is out of hand with the aount entered by the consuer. Figure 5. Flow chart C. Matheatical Analysis of Algorith The algorith starts with receiving consuers expected onthly electricity bill.then algorith calculates onthly allowed energy units (u ) fro that aount if A = Monthly current bill aount given by the user D= Days of aonth( 28,29,30or31) C() t = Real tie pricing for a unit fro utility side u A T D t = 0 () = (1) C t Where t is the real tie varries based on Peak and off peak tie Based on the previous onth usage pattern of the appliances algorith calculates U fro Later algorith allots units for each day in a onth fro u based on the equation u... = ud1+ ud2 udn (4) The value of u d will be equal to D u = u + u + u + u (5) ( ) d f b c r d = 1 IV. EXPERIMENTATION SETUP The designed hardware odel for WEEMAN is shown in Figure 6. The loads [Hoe appliances] are connected with WEEMAN through a relay switch and relay odule. The essage and alar noti cation for the custoer will be displayed in the LCD interface provided in WEEMAN. For creating an experiental test bed, we have connected ainly a 200 W Incandescent Bulb [Load A] and a Table fan [Load B] with the WEEMAN. When we switch on both the loads siultaneously as shown in figure 6, the WEEMAN calculates the power consued and sends it to the controlling station [sart eter]. By that tie sart eter takes onthly electricity bill using a GUI created in lab view as shown in the figure International Conference on Advances in Coputing, Counications and Inforatics (ICACCI)

6 delay optiization between WEEMAN and sart eter, and protection of architecture against central node (sart eter) failure is going to be our future work.. ACKNOWLEDGMENT We would like to express our iense gratitude to our beloved Chancellor Shri. Mata Aritanandaayi Devi for providing us otivation and inspiration for doing this research work. REFERENCES Figure 6. Experiental test bed using WEEMAN Upon receiving the power value fro WEEMAN the sart eter runs the availability based energy anageent algorith and updates the database to categorize the loads. With this experientation set up based on the onthly current bill given by the user, the algorith detects a violation in consuption of units. In this scenario the user has given load A as a higher priority than load B. So the sart eter sends a essage including load B s device id and delay tie value to WEEMAN.. Figure 7.Sart eter GUI for user input When WEEMAN receives a essage, it identifies the load to be switched o based on the device id received fro the sart eter and switches o load B. Load B will be switched on again, when tie elapses during the stipulated tie of delay When the load is switched off and on by WEEMAN it will display the essages on the LCD as Bulb is OFF Bulb is ON and Total Power consuption is 40 W etc. V. CONCLUSION AND FUTURE WORK The proposed architecture and counication terinology enables consuers to control the house hold electricity use and efficiently anage their onthly current bill. Also it enables the utility copany to lessen the discrepancy between the deanded and generated power. The [1] Jinsung Byun and Sehyun Park, Meber, IEEE, Developent of a Self-adapting Intelligent Syste for Building Energy Saving and Context-aware Sart Services, IEEE Transactions on Consuer Electronics, Vol. 57, No. 1, February [2] Chang-Sic Choi, Wan-Ki Park, Ilwoo Lee Meber, IEEE Green Hoe Energy Manageent Syste [Ghes] Through Coparison Of Energy Usage Between The Sae Kinds Of Hoe Appliances IEEE Transactions on Consuer Electronics, Vol. 57, No. 1, January [3] C. W. Liu, W.C. Wu, P. Y. Lin, C.Y. Hsueh Develop a Power Quality Measureent Syste Integrated with HAN Hoe Energy Manageent Syste IEEE Transactions on January [4] Mao-Yung Weng, Chao-Lin Wu, Ching-Hu Lu, Hui-Wen Yeh, and Li- Chen Fu Context-aware Hoe Energy Saving based on Energy-Prone Context IEEE Transactions on January [5] The world bank,back ground paper Residential Consuption Of Electricity In India Docuentation Of Data And Methodology, july [6] M. Erol-Kantarci and H. T. Mouftah, TOU-aware Energy Manageent and wireless Sensor Networks for reducing peak load in sart grids,72 nd IEEE conference on Vehicular Technology, pp. 1-5, [7] Z.Fan, G. Kalogridis, C. Efthyiou, M. Sooriyabandara, M. Serizawa, and J. McGeehan, The New Frontier of Counications Research: Sart Grid and Sart Metering,First insternational Conference on Energy-Efficient Coputing and Networking, [8] M. Erol-Kantarci and H. T. Mouftah, Wireless Sensor Networks for Cost-Efficient Residential Energy Manageent in the Sart Grid, IEEE Trans. Sart Grid, vol. 2, no. 2, pp , 2011 [9] H. Mohsenian-Rad and A. Leon-Garcia, Optial residential load control with price prediction in real-tie electricity pricing environents, IEEE Trans. Sart Grid, vol. 1, pp , Sep [10] J.Han,C.S.Choi,W.K.Park,andI.Lee,Green hoe energy anageent syste through coparison of energy usage between the sae kinds of hoe appliances, in Proc.15thIEEEInt. Syp. Consu.Electron. (ISCE), Jun. 2011, pp. 14 [11] A.-H. Mohsenian-Rad and A. Leon-Garcia, Optial residential load control w/ price prediction in real-tie electricity pricing environents, IEEE Trans. Sart Grid, vol. 1, pp , Sep [12] S. Shao,M. Pipattanasoporn, and S. Rahan, Developent of physical based deand response-enabled residential load odels, IEEE Trans. Power Syst., 2012, accepted for publication [13] A. Molderink, V. Bakker, M. Bosan Johann, L. Hurink, and G. J. M. Sit, Manageent and control of doestic sart grid technology, IEEE Trans. Sart Grid, vol. 1, no. 2, pp , International Conference on Advances in Coputing, Counications and Inforatics (ICACCI) 631