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Digital Direct Load Scheduling for Smart Appliances Using Renewable Resources

Researchers from the UC Davis Electrical and Computer Engineering Department have developed an innovative mathematically optimized scheduling algorithm for smart appliances, such as plug-in hybrid electric vehicles, which enables integration of considerable amounts of intermittent renewable resources like wind and solar energy into the power grid while ensuring optimum stability.
This novel system was designed from a rigorous mathematical model to provide the most optimal scheduling solution for smart appliances. It is future proof, as it is designed to be very flexible, able to handle different types of smart appliances, and yet still takes into consideration the many uncontrollable loads on the power grid. The system utilizes off the shelf communication devices and runs a software package that can be placed on a customer’s home computer, lowering costs significantly. It is able to handle a wide variety of energy sources, from traditional generated sources brought from far away to local renewable resources. It is highly scalable, usable in a local community setting or broadly by a large utility. It will compensate consumers for their voluntary participation in the program and also provide them with cheaper renewable energy sources. It will not only schedule the most optimal load for the power supplier to reduce load fluctuations, but will also minimize the net costs of providing power to the consumer by predicting future power supply and demand while purchasing power from the wholesale market accordingly on a day to day basis.
A proof of concept simulation has been developed and operates properly.


  • Low cost
  • Research proven solution
  • Minimizes cost of providing power
  • Handles multiple appliance types
  • Heavy integration of renewable energy sources


  • Alizadeh, Mahnoosh
  • Scaglione, Anna
Tech ID: 21837 / UC Case 2011-756-0