Advances in communication and control have begun the transformation of traditional power grids into more efficient “Smart Grids”. Two main features of the Smart Grid include demand side control and distributed generation (DG). Demand side control concerns load-shedding during peak consumption times while DG is electricity generation at the point of consumption, leading to a more decentralized system. As the Smart Grid grows, the amount of DG and controllable loads will greatly increase leading to high control complexity. Complexity is further increased when DG is a renewable source, such as a wind or solar generation unit, due to inherent natural variability. To manage this increased complexity, the use of microgrids (MG) has been proposed. A MG is a subsystem of the larger utility grid, with its own generators, loads, storage units, and energy management system, capable of operating autonomously. It has been shown that coupling MG within a multi-microgrid network (MMGN) can be advantageous due to resource sharing. Building upon a previously developed topology design found in the literature, we have created a dynamic topology design scheme for grouping MG within a MMGN. By using forecasted load and generation data, the MG are organized to maximize renewable DG usage, ensure survivability and limit dependence on the utility grid. The design scheme is designed for the medium and low voltage levels of a Smart Grid and can adapt to the addition of MG to the network. Using a simulated network of MG, we have shown the advantages of our design scheme.
A Dynamic Topology Design Scheme for a Multi-Microgrid Network
Presenter: John D'Agostino
Faculty Advisor: Rifat Sipahi