A Projection-based Dual Algorithm for Fast Computation of Control in Microgrids

We present a novel algorithm for the computation of optimal predictive storage and reactive power control in microgrids. This algorithm is based on the dual decomposition approach, but takes care of the local constraints by means of primal projections. This significantly increases the speed of convergence. Further, we show the convergence of the algorithm to an optimizer for a more general class of quadratic programs that includes the storage and reactive power control problem Then, we present a distributed way of implementing the algorithm which is based on the Jacobi overrelaxation. Simulations compare the algorithm performance with that of a purely dual decomposition approach, in a set of different microgrid testbeds.