Engineering and Natural Sciences

CENS Tech Report Series
Automated Power Management for Home Appliance using Raspberry Pi

Matthew Masengill and Somsak Sukittanon


Power production has been continuously pushed towards higher efficiency standards to reduce the consumption of resources and pollution. The baseload (minimum power that can be produced at a time) of many power plants causes a surplus in low demand times, which is primarily wasted. Demand side consumption management has the opportunity to fill the margin. Electric companies have discovered the potential to reduce waste such that the companies are beginning to implement more variable power rates. Given the introduction of these new rates, the economic market will grow a niche for consumer power management systems. The paper presents a method to automate when electricity is consumed for various appliances to a specified power rate. The system has the ability to automate power management with scheduled power rates (e.g. Free nights) and completely variable (Constantly updating). Completely variable electricity prices are accommodated with cut off electricity prices and cut off states. Completely variable pricing has not yet been introduced to the public; however, the design accommodates for this for perceived future implementation. Moderating electricity consumption will not only reduce waste but also satisfy the variable power rate incentive provided by the electric companies. Additionally, the system can be used for data acquisition as well as smart house capabilities. The user can view usage and see the cost association. The variable rates applied by the electric companies have been opt-in thus far.

Download the Document

Explore Our College

View an interactive brochure of our college.

View Brochure >



Internships are only available to students within three semesters of graduation (B.S.E.) who have not previously completed ENGR 313.

View Internships >


Technical Report Series

Technical reports available on this page are authored by Faculty, Staff, and Students of the College of Engineering and Natural Sciences at the University of Tennessee at Martin.

View technical report series >