A stackelberg game approach for two-level distributed energy management in smart grids

The pursuit of sustainability motivates microgrids that depend on distributed resources to produce more renewable energies. An efficient operation and planning relies on a holistic framework that takes into account the interdependent decision-making of the generators of the existing power grids and the distributed resources of the microgrid in the integrated system. To this end, we use a Stackelberg game-theoretic framework to study the interactions between generators (leaders) and microgrids (followers). Entities on both sides make strategic decisions on the amount of power generation to maximize their payoffs. Our framework not only takes into account the economic factors but also incorporates the stability and efficiency of the smart grid, such as the power flow constraints and voltage angle regulations. We present three update schemes for microgrids. In addition, we develop three other algorithms for generators, and among which a fully distributed algorithm enabled by phasor measurement units is proposed. The distributed algorithm merely requires the information of voltage angles at local buses for updates, and its convergence to the unique equilibrium is shown. We further develop the implementation architectures of the update schemes in the smart grid. Finally, case studies are used to corroborate the effectiveness of the proposed algorithms.