2006-2007: In collaboration with the Team for Research in Ubiquitous Computing (TRUST) and support from the National Science Foundation, this student team designed a software tool to simulate residential power management in response to dynamically changing electricity pricing. Electricity is usually sold to residences at one flat rate, but power companies are moving toward pricing electricity based on the time of day that power is used. How consumers will respond to this information and whether consumer appliances can incorporate price-based behavior, however, is not well understood.
The team designed a simulation package consisting of a processing program (simulator) coupled with a graphical user interface. The team tested the accuracy of the simulator by modeling a real home and comparing the actual and simulated data. Given user input about appliance parameters, the simulator uses historic five-minute pricing data and specific decision algorithms to determine whether to increase, decrease, or not change power consumption and, in turn, whether to start, continue, or stop running specific appliances. At the end of the simulation, the results of electricity consumption and cost, for each appliance and the house overall, are displayed graphically for the user. The team also developed an educational module for high school students with lectures, activities, a website, and the downloadable simulator.