Residence Energy Control System Based on Wireless Smart Socket and IoT

Abstract:

To avoid resources on green earth being exhausted much earlier by human beings, energy saving has been one of the key issues in our everyday lives. In fact, energy control for some appliances is an effective method to save energy at home, since it prevents users from consuming too much energy. Even though there are numerous commercial energy-effective products that are helpful in energy saving for particular appliances, it is still hard to _nd a comprehensive solution to effectively reduce appliances’ energy consumption in a house. Therefore, in this paper, an intelligent energy control scheme, named the residence energy control system (RECoS) is proposed, which is developed based on wireless smart socket and Internet of Things technology to minimize energy consumption of home appliances without deploying sensors. The RECoS provides four control modes, including peak-time control, energy-limit control, automatic control, and user control. The former two are operated for all smart sockets in a house, while the latter two are used by individual smart sockets, aiming to enhance the functionality of energy control. The experimental results show that the proposed scheme can save up to 43.4% of energy for some appliances in one weekday.

 

Existing System:

 

Most of the electronic appliance control applications utilize a lot of sensors to sense users’ locations and activities. Some of them even use Open Service Gateway initiative (OSGi) [5] or Service-Oriented Architecture (SOA) [6] to predict users’ behaviors in a house, with which to manage the home appliances in this house. Some previous studies [7], [8] improved functions of sockets set up in a house and connected with wireless networks to control home appliances. Sensing users’ location, motion, and habits with a large number of sensors may not be an energy ef_cient method since these sensors consume considerable resources. So it would be better for them to be low cost and high coverage. Also, according to the survey on developed countries by the International Energy Agency, the energy consumed by idle appliances, called standby energy, in a house is about 3% to 11% of total energy consumed by the house [9]. Basically, house energy can be further reduced if standby energy is effectively lowered without signi_cantly affecting users’ everyday lives, implying that the con_ict between house energy saving and user’s living convenience need to be balanced.

 

Proposed  System:

 

In this paper, an intelligent energy saving scheme, named the Residence Energy Control System (RECoS for short), is proposed to reduce the energy consumption of home appliances without deploying sensors. The RECoS, based on wireless smart sockets and IoT technology, not only monitors/controls the standby power consumption of an individual appliance, but also manages energy consumed by all controllable appliances. The RECoS also invokes the neural network algorithm to study user’s lifestyle and automatically turns off the power of each smart socket connected to IoT when the electric appliances are not in use. The experiments demonstrate that the RECoS can save up to 43% of energy for some appliances in a weekday. In the RECoS, no sensor is deployed, and the information of appliances’ energy consumption is collected by smart sockets through IoT. Those home appliances regularly or periodically staying in their standby states will be turned off by switching off the corresponding power supply embedded in their smart sockets with an electronic approach. After receiving user de_ned energy limit for a smart socket, the RECoS gives a one-day energy quota to the smart socket, and accordingly controls the energy consumed by those appliances connected to the socket.

 

Conclusion:

 

One of the main purposes of constructing a smart house is to automatically control those appliances in the house to achieve the goals of energy saving and smart living. In this paper, the RECoS controls the energy consumption in a residence through IoT and smart sockets. The RECoS provides four control modes to control the on/off state of home appliances connected to smart sockets. A simple IoT structure which integrates smart sockets, home gateway, energy controller, ZigBee, and Internet is proposed. Most importantly, the RECoS is sensorless and can be applied to outdated appliances, i.e., those without providing network connections. By using the neural network algorithm for smart learning, the RECoS can save unnecessary energy consumed by a house, and the experimental results show that up to 43.4% of energy can be reduced for a water dispenser in a weekday. Other appliances can also save some amounts of energy.

 

References: 

 

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[3] Cisco, “Bringing the smart grid into the home: The value of home energy management for utilities,” Cisco Syst. Inc., San Jose, CA, USA, White Paper C11-606976-00, Jun. 2010.

 

[4] V. Kopytoff and R. Kim, “Google plans meter to detail home energy use,” San Francisco Chronicle, San Francisco, CA, USA, Tech. Rep. 3172167, Feb. 2009.

 

[5] OSGi Alliance, “About the OSGi service platform,” Tech. Whitepaper, Revision 4.1, Jun. 2007.

 

[6] E. Newcomer and G. Lomow, Understanding SOA With Web Services. Reading, MA, USA: Addison-Wesley, Dec. 2004.

 

[7] M. Lee, Y. Uhm, Y. Kim, G. Kim, and S. Park, “Intelligent power management device with middleware based living pattern learning for power reduction,” IEEE Trans. Consum. Electron., vol. 55, no. 4, pp. 2081_2089, Nov. 2009.

 

[8] W. K. Park, C. S. Choi, I. W. Lee, and J. Jang, “Energy ef_cient multifunction home gateway in always-on home environment,” IEEE Trans. Consum. Electron., vol. 56, no. 1, pp. 106_111, Mar. 2010.

 

[9] Standby Power Annex: Summary of Activities and Outcomes Final Report, MAIA Consulting, Geneva, Switzerland, Apr. 2014.

 

[10] A. H. Mohsenian-Rad, V. W. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “Autonomous demand-side management based on gametheoretic energy consumption scheduling for the future smart grid,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 320_331, Dec. 2010.