Optimal Control of Stochastic Power Buffers in DC Microgrids

Power buffers are DC-DC converters where a large capacitor helps shield the DC grid from abrupt load changes. While point of load converters (PoLC)s are mainly tasked with meeting the terminal load requirements, power buffers add inertia to the DC grid during transients. The stochastic behaviour of loads could necessitate an adaptive optimal control strategy for power buffers. The optimal control of power buffers is usually formulated as a nonzero-sum differential game. The load behaviour can be captured using a multivariate probabilistic collocation method (MPCM) to sample its uncertainty. An integral reinforcement learning (IRL) algorithm, applied to the multiplayer differential game, finds the optimal control policy. Simulation studies demonstrate the performance of the IRL-based stochastic optimal control of power buffers in a DC microgrid.