Distributed Consensus-Based Coordination of Flexible Demand and Energy Storage Resources

Distributed, consensus-based algorithms have emerged as a promising approach for the coordination of distributed energy resources (DER) due to their communication, computation, privacy and reliability advantages over centralized approaches. However, state-of-the-art address DER problem in independent time periods therefore are inherently unable capture time-coupling operating characteristics flexible demand (FD) storage (ES) resources. This paper demonstrates that fail converge when these considered. In order this fundamental limitation, novel algorithm is proposed which includes additional consensus variables. These variables express relative maximum power limits imposed on FD ES effectively mitigate concentration responses at same steer consensual outcome feasible optimal solution. The convergence optimality theoretically proven while case studies numerically demonstrate its convergence, optimality, robustness initialization information loss, plug-and-play adaptability.