Assessment of grid-friendly collective optimization framework for distributed energy resources

Recent developments in the advanced control of renewable energy resources and distributed generation systems are resulting in pressures to adopt tariffs of increasing complexity. Independently of the tariff structure, utility customers can programmatically optimize their schedule consumption for reducing their energy bills.

However, as the penetration of distributed energy resources increases, there is an increasing chance of a “tragedy of the commons” mechanism taking place, where taking advantage of tariffs for local benefit can ultimately result in power quality degradation. In this work, we use a scheduling optimization tool, in combination with a distribution feeder simulator, to investigate techniques that could mitigate the deleterious effect of “selfish” optimization, so that the high-penetration use of DERs to reduce operating costs remains advantageous while the quality of service and overall energy cost to the community is not affected.