Design and Implementation of Energy Efficient Home Automation System

Transcription

1 Indian Journal of Science and Technology, Vol 9(6), DOI: /ijst/016/v9i6/84141, February 016 ISSN (Print) : ISSN (Online) : Design and Implementation of Energy Efficient Home Automation System Rajesh Singh *, Piyush Kuchhal, Anita Gehlot and Sushabhan Choudhury University of Petroleum and Energy Studies, Dehradun , Uttarakhand, India; rsingh@ddn.upes.ac.in, pkuchhal@ddn.upes.ac.in, anita@ddn.upes.ac.in, schoudhury@ddn.upes.ac.in Abstract Objectives: This paper provides solution for home automation, in terms of an energy efficient system. The objective is to design a device in the form of an intelligent remote control, to control the ambient condition of a house. Methods: An intelligent RF based remote control is developed which is capable of controlling in two modes- autonomous and semiautonomous. The dimming levels of appliances are tuned with optimized PID controller. A real hardware prototype is developed to control two parameters- light intensity and humidity level of the room. The tuning parameters of PID controller are calculated with the help of overall transfer function of the system, which includes the feedback signal from sensor, objective function of optimization algorithm and transfer function of the appliance (which is used to control the ambient conditions of room). Particle Swarm Optimization algorithm is used to optimize the tuning parameters for PID and results shows more energy efficiency with proposed system, when compared to conventional systems. Findings: The experimental results show prominent saving of energy by using proposed PSO-PID algorithm for designed system. It is calculated as 37.49% for light intensity control system and for humidity control saving comes out 36.9%. Novelty of the proposed system is new approach in terms of intelligent hybrid remote control. Keywords: Energy Efficient, Home automation, intelligent remote control, PID controller, PSO-PID 1. Introduction In 1 proposes a new observe, learn and adapt algorithm with the combination of wireless sensor networks and artificial intelligence, for smart homes. The technique discussed in the paper is based on the observing patterns for change in parameters but doesn t consider users requirement and comfort. In discusses about simulation model for control system design with wireless network. For the simulation purpose PiccSIM simulator is used and results introduces relationship between the network type and control performance. This paper discusses the simulation models for control system design and evaluates performance of the system but doesn t consider hardware complications. In 3 describes the design a smart home management toolkit system has three components like smart plug, gateway and a mobile application. Smart home management system is proposed with mobile application which is not a cost effective solution. In 4 describes, the design of temperature control with various control strategies using microcontroller with the help of feedback control. A microcontroller based tool kit is designed only for temperature control other physical parameters required for human comfort are not considered. In 5 proposes an energy management system based on wireless sensor networks has two main components like a wireless sensor network and an intelligent home gateway for sensing and transmitting electricity data and remote monitoring and control of home appliances. Real time monitoring and controlling of home appliances are proposed, but control of dimming levels are not discussed. In 6 proposes particle swarm optimization for wireless sensor network for an energy saving system for office lightning by using fluorescent lamps with dimming capacity. Paper concludes PSO as power saving algorithm *Author for correspondence

2 Design and Implementation of Energy Efficient Home Automation System for lightning system but other comfort parameters are not considered. In 7 describes a controller design method for temperature plastic extrusion system which improved settling time, couple effects, time constants, and undesirable overshoot. Paper includes simulation of GA based temperature control system no hardware implementation is done. And also no comparative analysis is done with other algorithms. In 8 presents a solution for stability to nonlinear system, while deals with level control of the system by dynamic response tests on a full scale simulator of a closed feed water heater and set points in the presence of various disturbances. Simulation based results are evaluated for controlling the water heater with PSO, but no comparative analysis is done with other algorithms. According to 9, PSO is good to tackle the problems which are nonlinear, non-differentiating able and multimode domain. PSO can be applied to location optimization of WLAN base station for indoor propagation problem. Paper describes ACO and PSO as optimizing algorithm only theoretically no actual implementation tricks are discussed. In 10 narrates an automatic voltage regulator system with better control performance and comparative study between real valued genetic algorithm and PSO with PID. Paper evaluates performance of AVR system with comparative analysis of GA, PSO and PID, it doesn t offer same type of exercise with other systems or hybrid system. In 11 proposes a Zigbee with IR code learning to control home appliances in a room to reduce power consumption by control the dimming light. The room architecture is proposed which is controlled by IR remote control of any home appliance. In 1 describes a test bed for smart homes for the evaluation of zigbee based home appliance control. A WPAN based smart lightning system is discussed in detail. In 13 proposes a home energy management system to analyze energy consumption and generation both. A gateway is used to monitor the energy consumption and compares it with renewable energy generation. In 14 describes the development of an intelligent heating System with the help of GA-PID. Real time implementation is done and results shows better results with GA-PID as compared to conventional systems. Due to the increasing demand for comfort and the requirements for energy savings. Zigbee based system would be better solution for home automation 15,16. In 17 proposes an innovative controller for thermal power plant with the combination of PID and genetic algorithm. MATLAB Simulink results shows better results in terms of transient response with proposed system when compared to Ziegler s Nichols tuned PID controller. In 18 describes a home automation system with the help of Raspberry pi and Pi camera by using modified template matching technique.. Proposed System A new approach for home automation is described in this paper. A system is designed in the form of an intelligent hybrid remote control. It is termed as hybrid as multiple appliances of the house can be controlled by a single remote control. The concept is to control the ambient condition of whole house by adjusting dimming levels of the appliances. It includes heating/cooling control system, humidity level control system, light intensity control system etc. Figure 1 shows the architecture for the proposed system for a two BHK house. Here it is considered that a normal middle class Indian house has two bed rooms, wash rooms, kitchen and one hall room. The whole system comprises of two parts- remote control and receiver section each room is equipped with a receiver section (appliance control section) and a single remote control is required to control all the receiver sections. It is done by assigning a unique ID to each appliance of each room and a data packet format is designed to control the respective appliance. A smart remote controlled system is developed, which provides a low cost and energy efficient solution. The system can be operated in two modesautonomous and semiautonomous modes. In autonomous mode the parameters are controlled by the system itself by adjusting applied voltage levels for respective appliance. It is done by adjusting the optimized PID parameters at the receiver end. In semiautonomous mode, the parameters are controlled through the intelligent remote. It is done by changing the dimming levels through switches provided on remote. The remote control comprises of sensors, switch array, microcontroller, LCD display and RF modem. For testing the system a hardware prototype is developed for controlling two parameters-light intensity control Figure 1. Architecture of the proposed system. Vol 9 (6) February Indian Journal of Science and Technology

3 Rajesh Singh, Piyush Kuchhal, Anita Gehlot and Sushabhan Choudhury and humidity level control of a room size of cubic feet. The receiver board comprises of dimmer for each appliance, microcontroller (Atmega16), and RF modem. The whole concept is to control the ambient conditions of a house with the help of single remote control in license free network..4ghz Zigbee module is used as RF communication media between receiver section and remote control. A system is designed in the form of remote control for light intensity and humidity level of a room. To control light intensity a 100W bulb and to control humidity level a 18W exhaust fan is used for experiment set up. Dimmer circuits are tuned to operate for sixteen levels. Figure and 3 shows block diagrams for remote control and receiver section respectively. It has capability to display all ambient conditions, which are under comfort levels for human being. In household uses lot of power is waste due to less knowledge about exact suitable environmental parameters. [eronomics.about.com] describes about the standard light intensity values. For living room general light intensity required is 300 lux and to perform any task it is 500 lux. For family room/home theater general value is 300 Figure. Block diagram for remote control. lux, for task it is 500 lux and to watch TV it is 150 lux only. For children bedroom general intensity of light required is 500 lux and if task is to perform it is 800 lux. For adult bedroom general is 300 lux and for performing task it is 500 lux. All these values are standard and generally not known to general people. Similarly [ describes about environmental parameters temperature and humidity which are dependent on each other. The comfort values for human beings has different values. In summer with light cloths if relative humidity is 30% then comfort temperature value is 4.4 to 8 0 C and if humidity is 60% then this value drops to 3 to C. In the winters with warm cloths if relative humidity is 30% then comfort temperature value is 0.5 to C and if humidity is 60% then this value drops to 0 to 4 0 C. If these values would be known to people, then it would be helpful to utilize power efficiently. The proposed system not only display these values, but all intelligently maintains these ambient conditions for house. 3. Methodology The basic flow of the process is to make the system intelligent by applying PID controller with optimization algorithm. System collects the data from sensor node as feedback signal in a closed loop, so that a fixed ambient conditions are maintained as required by the user. Firstly calibration of sensors are done with standard instruments, then dimming operation is elaborated with proper mapping and distribution of 0V which is household supply in India. For Sensors calibration standard instruments are referred for measuring temperature. Sensor output results are compared with standard data and accurate calibration is achieved. Proteus simulation is done for controller based circuits before actual hardware fabrication of the system, to check the feasibility and accuracy of the system. The experiment is performed in a room size of cubic feet with one receiver node and one remote control. Figure 3. Block diagram for receiver section. 3.1 Dimming Level Analysis In dimmer circuit, the rms value of the voltage supplied to the appliance is varied by controlling the firing angle of a triac. By controlling the firing angle, the voltage dimmer level of appliance is varied. The dimmer circuits are maintained to trigger at sixteen levels that means, the appliances can be controlled at sixteen levels. Table 1 shows the power consumption of bulb and exhaust fan w.r.t dimming levels. Vol 9 (6) February Indian Journal of Science and Technology 3

4 Design and Implementation of Energy Efficient Home Automation System Table 1. Power consumption of bulb and exhaust fan w.r.t dimming levels Dimming level Firing angle Input Voltage (V) Current (ma) for bulb Current (ma) for exhaust fan power consumption by 100W Bulb (W) power consumption by 18W exhaust (W) System Analysis System analysis is done on MATLAB tool with the help of PID controller and optimizing algorithm. Figure 4 shows block diagram of PID controller and optimization algorithm, for the appliances. Before actual implementation of the controller overall transfer function is to find out, which includes the transfer function of the appliance, feedback signal and objective function of the optimization algorithm. On the bases of the overall transfer function PID tuning parameters are calculated and transient responses are observed. Figure 5 shows the modelling of system by using MATLAB. Step response and transient response of bulb and exhaust fan are calculated on the bases of simulation. 4.1 Light Intensity Control System Analysis Transfer function for Bulb Transfer function of bulb is observed as Ls e Ts () = (1) 1 + st Where, L Inductance of filament. R Resistance of filament. Overall transfer function of Light Intensity control system for PID controller is (17970s+ 73) ( s s+ 73) () Overall transfer function of Light Intensity control system for GA-PID is (.003e004 s + 903) (3) (s + 530s + 903) Overall transfer function of Light Intensity control system for PSO-PID is (3.011e004 s e004) (s s e004) (4) Table shows the calculated PID tuning parameters for the bulb. Table 3 shows the transient response for light intensity control system with PID, GA-PID and PSO-PID controllers. 4 Vol 9 (6) February Indian Journal of Science and Technology

5 Rajesh Singh, Piyush Kuchhal, Anita Gehlot and Sushabhan Choudhury Figure 6 (a), (b), (c) shows the step response for bulb with PID, GA-PID and PSO-PID respectively. Figure 4. Block diagram of PID controller with optimization algorithm. 4. Humidity Control System Analysis Transfer function of exhaust fan is observed as s dte + 13 = Ts () = dvs 0.18s s (5) (a) Figure 5. System modelling with MATLAB. Table. bulb The PID tuning parameters calculated for PID GA-PID PSO-PID K P K I K D (b) Table 3. Transient response for light intensity control system with PID, GA-PID and PSO-PID controller PID GA-PID PSO-PID Rise Time(s) Settling Time(s) Overshoot Peak Time (s) (c) Figure 6. (a) Step response of bulb with PID. (b) Step response of bulb with GA-PID. (c) Step response of bulb with PSO-PID. Vol 9 (6) February Indian Journal of Science and Technology 5

6 Design and Implementation of Energy Efficient Home Automation System Where, Te= Electrical torque. Vs= Supply voltage. Overall transfer function of Humidity control system for PID controller is (35.38 s s+ 310) ( s s s+ 310) (6) Overall transfer function of humidity control system for GA-PID is (a) (99.6 s e004 s+ 655) ( s s e004 s+ 655) (7) Overall transfer function of humidity control system for PSO-PID is (150.6 s e004 s e004) ( s s e004 s e004) (8) Table 4 shows the calculated PID tuning parameters for the exhaust fan. Table 5 shows the transient response for humidity control system with PID, GA-PID and PSO- PID controllers Figure 7 (a), (b), (c) shows the step response for exhaust fan with PID, GA-PID and PSO-PID respectively. (b) 5. Software Development The whole system is developed on Atmega16 microcontroller. Firmware for remote control and receiver section Table 4. The PID tuning parameters calculated for exhaust fan PID GA-PID PSO-PID K P K I K D Table 5. Transient response for light intensity control system with PID, GA-PID and PSO-PID controller PID GA-PID PSO-PID Rise Time(s) Settling Time(s) Overshoot Peak Time (s) (c) Figure 7. (a) Step response of exhaust fan with PID. (b) Step response of exhaust fan with GA-PID. (c) Step response of exhaust fan with PSO-PID. is developed with AVR studio4 with Embedded C and program is burnt on controller with USB programmer using WINRAR. Zigbee is used for wireless communication between remote and receiver, data is sent in the form of packet with length of five byte with unique ID. 5.1 Data Packet Format 0xEA Autonomous / Semiautonomous Node ID Data 0x0D Figure 8 shows the Flowchart for remote control operation for the system. 6 Vol 9 (6) February Indian Journal of Science and Technology

7 Rajesh Singh, Piyush Kuchhal, Anita Gehlot and Sushabhan Choudhury 5. Remote Control and Receiver Section Working The remote control is initialized by pressing ON/OFF switch. After this controller waits for an interrupt signal. When any of the switches is pressed controller is to read it. First of all, user is to select the mode of operation. In semiautonomous mode, user is to select dimming level of appliance with the help of switch array provided on the remote control. In autonomous mode sensors (humidity and LDR) on remote control plays important role to maintain the ambient conditions. The user is to just feed the required values of physical parameters i.e., humidity and light intensity through remote control. Rest is the responsibility of receiver section. Here sensors comes into role to maintain each parameter. Sensor is to sense the present value of parameter in the surrounding. Now this sensor value (act as feedback signal to receiver section) and input value by user (act as reference signal to receiver section) both are transmitted to the receiver section trough Zigbee and receiver part start its role to trigger the dimming circuit at desired level. Receiver section plays different roles in two different modes (Semi-autonomous and autonomous), for semiautonomous mode it has only to follow the values given by the remote control to set the dimming level of appliance set by user. But in autonomous mode the role of receiver is not just to receive the input values and sensor value. Now receiver is to generate error signal by calculating the difference between sensor value and input value from remote control. Kp, Ki and Kd values are being calculated by PSO-PID and appliance is triggered at the required dimming level, itself by receiver section. It is done by judging the requirement of the system to shift the level at upper side or lower side. Figure 8. Flowchart for remote control operation. 6. Result and Discussion The prototype is developed with one 100W bulb to control light intensity, one 18W exhaust fan to control the humidity level of room. An experiment set up placed in a room size of cubic feet. Receiver section comprises of Atmega16, dimmer circuits for appliances, bulb, exhaust fan and RF modem. Remote control comprises of LDR, humidity sensor, switch array, LCD, Atmega16 and RF modem. Table 8. Power consumption for 100W Bulb to maintain light Intensity at 00lux or 80% LDR value with initial 0% intensity using PID, GA-PID and PSO-PID Time Light Intensity (%) (Outdoor) Light Intensity at 80% LDR (room) Power consumption for PID Power consumption for GA-PID Power consumption for PSO-PID 6:30 PM :30 PM :30 PM :30 PM :30 PM Total Power(W) Vol 9 (6) February Indian Journal of Science and Technology 7

8 Design and Implementation of Energy Efficient Home Automation System For calculation of energy consumption an experiment is conducted for duration of four hours, in the month of March 015 and energy meter is used for actual power calculation for the said duration. As shown in the Table 8 initial outdoor light intensity is observed as 0% at 6:30 P.M. As it was evening time the outdoor light intensity is decreasing with passage of time and 100W bulb is sufficient for providing required light intensity for mentioned room size. Figure 9 shows the percentage energy saving with optimized PID controller for bulb. Performance for humidity level control is also checked with experiment set up. Table 9 shows the power consumption by exhaust fan for the experiment duration. Initial value of humidity is observed as 44% at :00 P.M. Power consumption for the exhaust fan was calculated with the help energy meter. Figure 10 shows the percent energy saving with optimized PID controller for exhaust fan. Figure 10. exhaust fan. Percentage Power saving w.r.t conventional Figure 11. Developed system with receiver section and remote control. Figure 9. bulb. Percentage Power saving w.r.t conventional Figure 1. Snapshot for receiver section. Table 9. PID Time Power consumption for 18 W exhaust fan to maintain humidity at 4% using PID, GA-PID and PSO- % Humidity (Initial) Humidity 4% Power consumption for PID Power consumption for GA-PID Power consumption for PSO-PID :00 PM to 3:00 PM :01 PM to 4:00 PM :01 PM to 5:00 PM :01 PM to 6:00 PM Total Power (W) Vol 9 (6) February Indian Journal of Science and Technology

9 Rajesh Singh, Piyush Kuchhal, Anita Gehlot and Sushabhan Choudhury Figure 13. Snapshot for remote control in autonomous and semiautonomous modes. 7. Conclusion For light intensity control result shows percentage power saving for PID is 30%, for GA-PID saving is 37% and for PSO-PID it is 37.49%. For humidity control system result shows percentage power saving for PID is 3%, for GA-PID saving is 34% and for PSO-PID it is 36.9% It is concluded that the PSO-PID is most energy efficient method among the selected methods and is best suited for proposed system. The developed system is for the control of light intensity and humidity level control of the room. Figure 10, 11, 1 shows the snapshots for the developed system, receiver section and remote control respectively. In the similar manner the system can be implemented on any home appliance and the whole home can be handled with a single remote control. It is new approach for home automation systems and can be implemented in existing houses without any renovation. It is low cost and energy efficient system and in the reach of middle class families in India. 8. References 1. Qela B, Mouftah HT. Observe, Learn, and Adapt (OLA) - An algorithm for energy management in smart homes using wireless sensors and artificial intelligence. IEEE Transactions on Smart Grid. 01 Sep; 3(4):6 7.. Bjorkboma M, Nethib S, Erikssona LM, Janttib R. Wireless control system design and co-simulation. Control Engineering Practice, Elsevier. 011 Sep; 19(9): Keyson D, Mahmud AA, Hoogh MD, Luxen R. Designing a portable and low cost home energy management toolkit. The 3rd International Conference of Sustainable Energy Information Technology, Procedia Computer Science, Elsevier; 013. p Ibrahim D. Teaching digital control using a low-cost microcontroller- based temperature control kit. International Journal of Electrical Engineering Education, SAGE journals. 011; 40(3): Kim WH, Lee S, Hwang J. Real-time energy monitoring and controlling system based on ZigBee sensor networks. International Symposium on Intelligent Systems Techniques for Ad hoc and Wireless Sensor Networks, Procedia Computer Science, Elsevier; 011. p Si W, Ogai H, Hirai K, Takahashi H, Ogawa M. An improved PSO method for energy saving system of office lighting. IEEE Proceedings of SICE Annual Conference (SICE); 011 Sep. p Ravi S, Sudha M, Balakrishnan PA. Design of intelligent self-tuning GA ANFIS temperature controller for plastic extrusion system. Modelling and Simulation in Engineering, Hindawi Publishing Corp. 011; Tong Q, Zou X, Zhang Q, Gao F, Tong H. The hardware/ software partitioning in embedded system by improved particle swarm optimization algorithm. IEEE Symposium on embedded computing; 011. p Zheng G, Zhang Z. Intelligent wireless electric power management and control system based on ZigBee technology. IEEE International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), 011. p Wong CC, Li SA, Wang HY. Optimal PID controller design for AVR system. Tamkang Journal of Science and Engineering. 009; 1(3): Han J. Remote-controllable and energy-saving room architecture based on ZigBee communication. IEEE Transactions on Consumer Electronics. 009 Feb; 55(1): Dae-Man H, Lim JH. Smart home energy management system using IEEE and ZigBee. IEEE Transactions on Consumer Electronics. 010; 56(3): Jinsoo H, et al. Smart home energy management system including renewable energy based on ZigBee and PLC. IEEE Transactions on Consumer Electronics. 014; 60(): Singh R, Kuchhal P, Choudhury S, Gehlot A. Implementation and evaluation of heating system using PID with genetic algorithm. Indian Journal of Science and Technology. 015; 8(5): Singh R, Kuchhal P, Yadav MS, Sharma MK, Choudhury S, Anita. Optimization and implementation of intelligent RF remote controlled heater system. International Journal of Control and Automation. 015; 8(5): Vol 9 (6) February Indian Journal of Science and Technology 9

10 Design and Implementation of Energy Efficient Home Automation System 16. Singh R, Kuchhal P, Yadav MS, Choudhury S, Anita. Intelligent integrated RF remote control for fan, light and heater. International Journal of Applied Engineering and Research, RI Publications. 015; 10(3): Meena AR, Kumar SS. Design of GA tuned two-degree freedom of PID controller for an interconnected three area automatic generation control system. Indian Journal of Science and Technology. 015; 8(1). 18. Kundukulam EJ, Sudharson A. Implementing and optimizing template matching techniques for home automation. Indian Journal of Science and Technology. 015; 8(19). 10 Vol 9 (6) February Indian Journal of Science and Technology