UCLA

Microgrids, as one of the key components to enable the future smart grid, refer to low-voltage power distribution systems integrated with distributed energy resources (DERs) and controllable loads, which can operate either with or without the grid (i.e., grid-connected or islanded mode). The integration of DERs and controllable loads brings tremendous opportunities to increase power system efficiency, sustainability, and reliability. However, the intermittency and variability of renewable DERs and limited supply especially when the microgrid is operating in islanded mode introduce significant challenges to maintain the fundamental supply-demand balance for system stability. Therefore, the goal of this dissertation is to solve the supply-demand balancing problem in microgrids using optimization-based energy management.

Most of the existing energy management algorithms in the literature consider the aggregate supply-demand balance as an abstract mathematical function while omitting the underlying power distribution network and the associated power flow and system operational constraints. Consequently, such approaches may result in control decisions that violate the real-world constraints. Therefore, in the first part of this dissertation, we study the supply-demand balancing problem in microgrids under more realistic conditions and propose algorithms for microgrid energy management that take into account the power flow and system operational constraints on a distribution network. By incorporating the distribution network in the modeling, we present the relationship between the physical structure of a microgrid and the energy management on the network.

Another major challenge in microgrid energy management is to design a two-way communication system in order to implement the algorithms. A variety of heterogeneous devices in a microgrid need to be managed by such a system using the energy management algorithms. Unfortunately, most of those devices still use proprietary protocols and cannot interoperate with each other. Furthermore, many devices managed by the system reside on the customer side requiring autonomy and local intelligence. Therefore, in the second part of this dissertation, we focus on the design and implementation of a system architecture that enables interoperability and autonomy for microgrid energy management. We present the design of a unified communication interface that is protocol and technology agnostic for interoperability and a decentralized system architecture for autonomy on the customer side.