Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Does renewable energy renew the endeavor in energy efficiency?
Amrou Awaysheh1, Christopher Chen2, Owen Wu2
1Kelley School of Business, Indiana University, Indianapolis, IN, United States of America; 2Kelley School of Business, Indiana University, Bloomington, IN, United States of America
We examine whether and how renewable energy (RE) adoption can increase or decrease energy efficiency (EE) improvement. Using site-level data, we estimate the impact of changes in RE usage and in the acquisition approach on the EE. We find that using RE to meet 10% more of a site's energy demand led to an additional 2.0% improvement in EE. While purchasing RE credits or entering into power purchase agreements led to gains in EE, installing on-site RE generators had no effect.
Urban mining, critical material scarcity, and the renewable energy transition
Serasu Duran1, Clara Carrera2, Atalay Atasu2, Luk N Van Wassenhove2
1Haskayne School of Business, University of Calgary, AB, Canada; 2INSEAD, Fontainebleau, France
Clean energy technologies require large amounts of critical metals and minerals, the demand for which is skyrocketing as the global energy sector rapidly shifts towards renewable energy. The scarcity of critical materials may prevent governments from reaching their ambitious clean energy targets and jeopardize the profitability of the renewable energy sector. Inspired by this challenge, we investigate mechanisms that can address the impact of scarcity on the renewable energy transition momentum.
The role of driver behavior in moving the electric grid to zero emissions
Leann Thayaparan, Georgia Perakis
MIT, United States of America
The ability to produce electricity when renewables allow and store it for later demand is crucial for emissions reduction. Electric Vehicles (EVs) could provide distributed energy storage to the electric grid through optimal charging and discharging, however, highly complex, non-linear driver behavior must be accounted for. In this work we collaborate with an American EV manufacturer to combine machine learning with optimization to model driver behavior to size the capacity of EV energy storage.
Dynamic valuation and optimal control of a battery under performance degradation
Joonho Bae, Roman Kapuscinski, John Silberholz
Ross School of Business, University of Michigan, United States of America
Quantifying the operating cost of a battery has been considered a key challenge for economic profitability in the battery literature/industry. One key modeling difficulty is that the cost is realized through different types of performance degradation. This work takes an analytical approach to compare the optimal dynamic policy under different degradation models (capacity-degradation-only, efficiency-degradation-only, and correlated degradation).
