Abstract: The present disclosure provides for distributed resource scheduling performed by an advanced resource scheduling (ARS) module implemented on a distributed grid management (DGM) server in a power system. The ARS module is configured to automatically generate a resource schedule for controllable distributed energy resources (e.g., resources that are remotely controllable by DGM server and ARS module) in a distribution network of the power system, such as power generation resources and energy storage resources, to provide power in a cost-effective (e.g., optimal) manner. The ARS module is configured to take into account the operating limits of the distributed energy resources (DERs), the cost curves of the DERs, the system load demand, and other operating constraints to determine the most economical operating plan for the DERs, using an optimization technique such as the particle swarm optimization (PSO) algorithm.

Abstract: The present disclosure provides for distributed resource scheduling performed by an advanced resource scheduling (ARS) module implemented on a distributed grid management (DGM) server in a power system. The ARS module is configured to automatically generate a resource schedule for controllable distributed energy resources (e.g., resources that are remotely controllable by DGM server and ARS module) in a distribution network of the power system, such as power generation resources and energy storage resources, to provide power in a cost-effective (e.g., optimal) manner. The ARS module is configured to take into account the operating limits of the distributed energy resources (DERs), the cost curves of the DERs, the system load demand, and other operating constraints to determine the most economical operating plan for the DERs, using an optimization technique such as the particle swarm optimization (PSO) algorithm.