Models for Energy Systems Planning and Economics in the Age of Energy Transition
Motivated by the aggressive push towards society-scale decarbonization, power grids face pressure to pro-actively integrate large penetrations of renewable energy and energy storage technologies, many of which vary in their techno-economic characteristics from the traditional centralized, economy-of-scale generation dogmas. Furthermore, electrification of traditionally fossil-dependent sectors (e.g. transportation, buildings and manufacturing) increases demand for electricity and alternative fuels, which further stresses power grids. Addressing these challenges require next-generation mathematical models and algorithms that help bridge the divide between these technologies and the current power grid practices. In this presentation, we will adopt a bottom-up approach to describe how distributed generation resources can be used to assist power grids in accommodating renewable energy resources, and how to mitigate emerging communication and cybersecurity risks that limit the ability of these resource to provide grid support services at scale. We will focus on specific examples of high-rise buildings and electric vehicle charging stations to illustrate how these resources can be safely aggregated into grid-scale resources that can compete with traditional resources in electricity markets. Then, we will discuss a transition towards stochastic and risk-cognizant electricity market designs, and demonstrate the importance of internalizing variance of future market states and risk trading mechanisms to obtain efficient market outcomes.