The iPhone recommendation system
Technology just made being “green” easier. Computer science researchers at the University of Arkansas and University of San Francisco have developed an automated energy-management system that monitors energy generation and consumption in off-grid and grid-tied homes that use solar energy or wind power. As part of the system, an iPhone application warns homeowners of critical battery situations, suggests appliances to turn on or off, recommends ideal times to execute tasks that require greater power and adjusts power states of devices to reduce energy consumption.
The home monitoring system
“Our system alerts the homeowner of critical situations and then suggests which appliances to turn off. From anywhere, as long as they have their smart phone, homeowners can then use the software to direct the system to shut off the suggested appliance or a different one,” said Nilanjan Banerjee, assistant professor of computer science and computer engineering at the University of Arkansas.
Banerjee, Pat Parkerson, associate professor of computer science and computer engineering at the University of Arkansas, and Sami Rollins, professor at the University of San Francisco, installed a suite of monitoring tools in an off-grid, solar-powered home in Fayetteville. The researchers collected generation and consumption data during the summer of 2010 and in November and December of 2010. In addition to monitoring power-generation devices of the photovoltaic system, their system also tracked individual appliances, including a refrigerator, washer and dryer, hot-water heater and television.
Data collected by the monitoring system demonstrated important findings. First, energy harvested from the solar panels and energy consumed by the house varied greatly, but in a predictable manner.
Second, the study demonstrated that traditional energy-management techniques are insufficient in off-grid homes. Finally, the data showed that manual and reactive techniques do not prevent critical battery situations. The homeowner in the study was conservative with energy consumption and carefully monitored battery voltage. Still, he had to rely on a backup generator approximately 25 percent of the time because he could not predict times in which harvesting solar energy was low.