Uncertainty and Decentralization: Two Themes in an Energy Transformation

Citation

Werner, Lucien Desloge (2023) Uncertainty and Decentralization: Two Themes in an Energy Transformation. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/scmm-p028. https://resolver.caltech.edu/CaltechTHESIS:06122023-232029846

Abstract

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 study 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), such as solar and storage, 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 (OS), 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. The core functions it provides are data acquisition and processing, system modeling and learning, and optimization and control. We present key modules of the Microgrid OS in the context of several implementation projects in microgrids, commercial buildings, and distribution networks.