Robust implementation of algorithms for distributed generation control of small-footprint power systems

Together with advancements in communication and computer processing technologies, the widespread integration of distributed energy resources (DERs) in the form of renewable energy sources, e.g., wind and solar, will make available new and valuable ancillary services to power systems such as voltage support and frequency regulation. Given the relative size of the resources, however, the provision of these services will require the coordination of several DERs such that their collective capabilities have sufficient impact on a system level. This thesis proposes a method for controlling distributed generation resources (DGRs) without the need for a centralized decision maker. In particular, we discuss a class of iterative algorithms which are capable of coordinating a set of DGRs in order to collectively achieve a predetermined goal. We begin by formulating an unconstrained algorithm which we later extend to account for individual DGR capacity constraints. A convergence analysis of the algorithms is presented, followed by the discussion of a modification that enhances the resiliency of the algorithms when the communication links are imperfect. Next, the development of a hardware testbed comprised of low-complexity devices equipped with wireless transceivers that implements the algorithms is described. We conclude by illustrating the efficacy of the algorithms by utilizing the hardware testbed to control the synchronous generators to regulate the electrical frequency in a small-footprint power system