EAGER: Toward Renewable Dominated Electric Energy Systems (RENDES)

Ohio State University, The, Columbus OH

Investigators

Abstract

This is a project to study long term planning problems for the electric grid assuming a transition from today's thermal-dominated electric energy systems to a renewable energy-dominated system. Two topics that will be the focus of the work are market design and the associated valuation of energy resources, and capacity expansion. Major issues in market design for such systems include determining an appropriate market model for grids with high penetration of renewable sources; determining how such markets should clear to protect the interests of all parties while maximizing a measure of social welfare; and finding appropriate valuation models of various energy resources so as to recover costs that are not covered by the regular market clearing price. If successful, the project will have significant impact on planning for a future grid with increasing levels of renewable generation. By engaging with electric power industry members through an industry funded research consortium at the PI institution, the researchers will ensure that their results are available to industry members while also receiving feedback from industry on the project as it develops. More specifically, the aim of this project is to create mathematical models to analyze the transition from today's electric power systems to a future renewable-dominated design. The research issues noted above have not been addressed in the technical literature, pose significant intellectual challenges, and are crucial to guarantee a secure electricity supply in the future. The project will develop an integrated suite of short-run operational and long-run dynamic capacity expansion models. Decomposition techniques will be used to make the resulting stochastic programming, complementarity, and adaptive robust optimization models tractable. In addition to the direct benefits to the electricity sector, this research will fundamentally advance the fields of computational optimization, energy policy, and energy economics.