Distributed technique for power ‘scheduling’ advances smart grid concept


Power plants around the country use a centralized scheduling approach to forecast and distribute energy. This centralized approach does not support the integration of renewable energy systems and battery storage systems.  The rise of on-site energy storage technologies makes centralized scheduling calculations significantly more complex.


  1. Researchers from North Carolina State University have developed a new technique for scheduling energy in electric grids that moves away from centralized management by tapping into the distributed computing power of energy devices.
  2. By having each device communicate with its immediate neighbors, the device can calculate and schedule how much energy it will need to store, how much to contribute to the network, and how much to draw from the network. In this way, the program can determine the optimal schedule for the entire grid.
  3. Distributed computing seeks to replace the traditional control center with a decentralized approach. This approach advances the smart grid concept by coordinating the energy being produced and stored by both conventional and renewable sources.
  4. The technology has been validated in simulations, and the researchers are in the process of implementing it in an experimental smart grid system at the National Science Foundation FREEDM Systems Center on NC State’s campus. They expect to have results in 2016.


  1. Utilities
  2. Government and government regulators of utilities
  3. Alternative energy and battery storage companies


  1. Distribute paper for peer review
  2. Get data from multiple tests and report out results
  3. Pilot large-scale demonstrations
  4. Gain industry acceptance and scale usage




2 thoughts on “Distributed technique for power ‘scheduling’ advances smart grid concept

  1. Interesting topic, one of the most fascinating aspects is how smart grids don’t scale up well. Since on-site energy storage makes power scheduling calculations significantly more complex.


  2. It would also be interesting to see how this system would interact with the current system of electricity production pricing. Currently power plants put in bids right before peak demand, or a surge of electrical use, and indicate how much money they’re selling electricity for and how much electricity they will provide. This technology would require a much more dynamic pricing system.


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