||In Taiwan, we have faced the lack of energy for a long time in recent decades. To solve this problem, the government has proposed the plan to build more power plants. On the other hand, there is another solution based on the development of the “Demand Response” technology. This technology can support a distributed system that aims to reduce the use of electricity by energy-saving facilities to alleviate the danger of power shortage. The concept of demand has been implemented into industrial power systems —the Home Energy Management System (HEMS). HEMS measures and analyzes the status of home appliances’ energy usage in a house. HEMS uses wired/wires network communications to transmit power consumption information. In order to obtain reference data for optimizing power consumption more efficiently, HEMS uses Internet of Things technologies to provide power information feedback to electric power industry as well as to monitor and control the unloading of power plants more precisely. By deploying HEMS in general users’ home space, the goal of reducing power spikes can be achieved after the collective efforts contributed by all smart-energy houses with HEMS. |
This thesis proposes an IoT-based HEMS. The design of this system contains several functional devices, including home gateway, ZigBee communication, power meter, and home appliances, thereby forming a small-scaled HEMS environment in smart home space. Based on the proposed system design and implementation, our study in this thesis conducts practical testing and verification. Our study efforts can meet the requirements of home appliance management, mutual communications between home appliances, and unloading control mechanisms, along with the analysis of power usage. Therefore, at peak hours, we can operate various home appliances to stay in minimum energy demand, avoid unnecessary power outages, solve unsatisfactory power consumption, and decrease economic losses. Besides, a friendly energy visualization platform is combined to ease users’ understanding of energy usage and energy conservation.
|| Khan, Aftab Ahmed Razzaq, Sohail Khan, Asadullah Khursheed, Fatima Owais, “HEMSs and Enabled Demand Response in Electricity Market: An Overview,” Renewable and Sustainable Energy Reviews, vol. 42, pp 773-785, 2015.|
 Qusay F. Hassan, “Introduction to the Internet of Things,” Wiley-IEEE Press, 2018.
 The Raspberry Pi Foundation, Raspberry Pi [Online]. Available: https://www.raspberrypi.org/about.
 OASIS. MQTT [Online]. Available: http://mqtt.org.
 Andrew Wheeler, “Commercial Applications of Wireless Sensor Networks Using ZigBee,” IEEE Communications Magazine, vol. 45, issue. 4, pp. 70-77, April 2007.
 Markandeshwar Jerabandi, Mallikarjun M Kodabagi, “A Review on Home Automation System,” 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon), Bangalore, India, August 2017.
 Yaw-Wen Kuo , et al, “ Design of a Wireless Sensor Network-Based IoT Platform for Wide Area and Heterogeneous Applications,” IEEE Sensors Journal, vol. 18, June 2018.
 V C Jishnu Sankar , et al, “Integration of Demand Response with Prioritized Load Optimization for Multiple Homes”, 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), pp. 21-23, 2017.
 Milica Leki?; Gordana Garda?evi?, “ IoT Sensor Integration to Node-RED Platform”, 17th International Symposium INFOTEH-JAHORINA (INFOTECH), March 2018.
 Olivier Hersent, et al, IEEE 802.15.4, Wiley Telecom, pp. 376, 2012.
 ECHONET Consortium..ECHONET Lite (2018, Jan 10) [Online]. Available:
 European Commission. (2018, Jan 20) ENERinTOWN [Online].
 台灣智慧能源產業協會.(2018, Jan 20) TaiSEIA [Online].Available:http://www.taiseia.org.tw.
 Digi International Inc. (2018, Feb 2)XBee、ZigBee、XCTU [Online]. Available:https://www.digi.com.
 Tom Marrs, JSON at Work: Practical Data Integration for the Web,O′Reilly Media,2017.
 Peacefair. (2018, Feb 2) PZEM004T [Online]. Available:https://github.com/olehs/ PZEM004T.
 經濟部能源局電力組，「低壓智慧電表推動規劃 (智慧電網推動) 電力小組 能源轉型白皮書重點推動方案」，經濟部能源局，民國106年11月。
 S. Veleva and D. Davcev, “Data Mining as an Enabling Tech nology for home energy management system,” in Proc. IEEE Int. Conf. Innovative Smart Grid Technologies, Jan. 2012.