In recent years, the share of renewable energy sources (RESs) has been increasing in the electricity generation mix with a mandate to reduce greenhouse gas emissions that are released from burning fossil fuels. Indeed, a large share of electricity from renewable resources is required to de-carbonize the electricity sector. With the evolution of smart grids and microgrids, effective and efficient penetration of renewable generation such as wind and solar can possibly be attained. However, the intermittent nature of wind and solar generation makes microgrid operation and planning a complex problem and there is a need for a flexible grid to cope with the variability and uncertainty in their generation profiles. This research focuses on the coordination of distributed energy resources, such as energy storage systems (ESSs) and demand response (DR) to present an efficient solution towards improving the flexibility of microgrids, and supporting high levels of renewables generation. The overall goal of this research is to examine the influence of coordinated operation of ESS and DR on microgrid operations in the presence of high penetration levels of renewable generation. Deterministic and stochastic short-term operational planning models are developed to analyze the effects of coordinating ESS and DR, vis-à-vis their independent operation, on microgrids with high renewable generation. Special focus is on operation costs, scheduling and dispatching of controllable distributed generators, and levels of renewable generation. A set of valid probabilistic scenarios is considered for the uncertainties of load, and intermittency in wind and solar generation sources. The numerical results considering a benchmark microgrid indicate that coordinated operation of ESS and DR is beneficial in terms of operation costs, vis-à-vis their independent presence in the microgrid, when there is sufficient renewable generation. The coordinated operation reduces the risk in scheduling and increases the flexibility of the microgrid in supporting high levels of renewable generation.

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Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.