Semester

Summer

Date of Graduation

2005

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Powsiri Klinkhachorn.

Abstract

High prices are associated with the peak electricity demand and thus, price can be used as an indicator of power system condition in the peak load management programs. This paper investigates the potential of peak load management based on price-responsive load control for the residential sector. The Computer Aided Home Energy Management (CAHEM) system controls residential demand in response to the hourly market data including price, load and temperature data. A fuzzy demand controller incorporates customer preferences in determining operational settings of residential appliances. A prototype CAHEM system is demonstrated using X10 home networking technology. The aggregate level effects of the CAHEM system on peak load reduction are simulated for the Pennsylvania-New Jersey-Maryland market during the summer of 1999. The study also estimates the optimal level of large-scale adoption of the CAHEM system.

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