Optimal distribution in smart grids with volatile renewable sources using a message passing algorithm

The design of future electricity grids will allow for renewable energy generators to be effectively incorporated into the network. Current methods of economic dispatch were not designed to accommodate the level of volatility and
uncertain nature of sources such as wind and solar; here we demonstrate how an optimisation algorithm called message passing, which is based on principled statistical physics methodologies and is inherently probabilistic, could
be an alternative way of considering source volatility efficiently and reliably. The algorithm iteratively passes probabilistic messages in order to find an approximate global optimal solution with moderate computational
complexity and inherently consider source volatility. We demonstrate the capabilities of message passing as a distribution algorithm in the presence of uncertainty on synthetic benchmark IEEE networks and show how the volatility increase effects distribution costs