Stochastic energy management in distribution grids

Variabilities of renewable energy sources critically challenge contemporary power distribution grids. Depending on grid conditions, solar energy may have to be curtailed to comply with network limitations. On the other hand, smart inverters installed with solar panels enable for reactive power support at fast response rates. Existing energy management schemes may not efficiently integrate intermittent generation. Inherent operational flexibilities, such as flexible voltage regulation margins and instantaneous inverter or distribution line overloading could be judiciously exploited. To that end, an ergodic energy management framework is put forth calling for joint control of active and reactive power using smart inverters. Although tighter operational constraints are enforced in an average sense, looser margins are satisfied at all times. A stochastic dual subgradient solver is devised using an approximate linearized grid model. The algorithm is distribution free, and enjoys provable convergence. Numerical tests on a 56-bus distribution feeder demonstrate that the novel scheme yields lower energy cost upon its deterministic counterpart.