PhD Thesis Defense

Over the last two decades, the rapidly decreasing units costs of solar, wind, and energy storage technologies have launched a fundamental transformation in how electric power is produced, distributed, and consumed. Proliferation of these technologies has effected a shift towards a more decentralized, flexible, and sustainable energy system that can meet the growing demand for energy while reducing greenhouse gas emissions from fossil fuels. The work in this thesis studies two principal themes in this transformation: uncertainty and decentralization. 

Uncertainty is a key challenge in the modern grid resulting from the weather dependence of variable renewables and volatile loads like electric vehicles distributed throughout the grid. Electricity markets, whose function is to regulate the precise balance of supply and demand across the system, face a pressing need for dispatch mechanisms that account for uncertainty while providing participation incentives for generators and loads. We introduce a framework for multi-stage market dispatch and pricing under a general description of forecast uncertainty that enables system operators to explicitly incorporate uncertainty into market-clearing prices. In related work, we propose mechanisms that guarantee feasibility of multi-interval dispatch under robust uncertainty and provide participation incentives for shiftable demand response in forward multi-interval markets. 

The trend towards a more decentralized energy system stems from the inherent modularity of distributed energy resources (DERs) as well as the persistent growth in end-use loads. This evolution presents significant challenges to system operators who typically lack the tools and processes for managing a complex, distributed power system. To fill this gap, we introduce and implement a Microgrid Operating System (μOS), a software platform for monitoring, modeling, and optimizing microgrids and distribution systems. The Microgrid OS is a central layer that links DER hardware, such as batteries, solar, and flexible loads, to energy applications like cost minimization, emissions reduction, and wholesale market participation. We present several key modules of the Microgrid OS in the context of implementation projects in microgrids, commercial buildings, and distribution networks.