Distributed dynamic algorithm for energy management in smart grids

Historically, the electric power grid has been dominated by fossil fuel-based power plants, where a central entity called the energy management system controls and optimizes resources. With the growth of renewable energy sources, distributed algorithms are projected as alternative paradigms to handle large optimization problems given the sheer volume of data and its privacy. This chapter studies the mathematical foundations for different decentralized and distributed algorithms applicable in power systems for convex functions to solve an economic dispatch problem. In the proposed algorithm, each agent updates the time-varying estimate of average power mismatch and the market price via dynamic average consensus in a distributed fashion and finds consensus on those variables. The problem is modeled as a discrete-time linear system, and the stability and convergence of the distributed subgradient algorithm are investigated. Finally, the efficacy of the algorithm is demonstrated in the IEEE 39 bus network.