Alex Dowling
Title:
Multiscale Systems Engineering for Energy Technology Innovation
Growing worldwide energy demands and concerns for environmental impacts from energy conversion (e.g., CO2 emissions, water availability, air quality, etc.) are driving a paradigm shift in how the world thinks about energy. Creating sustainable energy technologies is an inherently multiscale problem, requiring innovations at the materials, devices, systems, and infrastructures length and timescales. Yet collaboration across these scales is often inhibited by complexity and domain specific models. New systems engineering approaches are needed to accelerate technology innovation by capturing the most important multiscale interactions and integrating expertise from many disciplines.
Part 1 of this seminar investigates the economic incentives for multiscale dynamic flexibility embedded in price signals from electricity markets (infrastructure). Technology specific economic assessment is posed as a large-scale optimization problem: manipulate the energy system control strategy (e.g., mass and energy flows, storage levels) and the market participation schedule in order to maximize revenue subject to system physics and operational limitations. Revenue potentials are estimated for two technologies, large-scale solar thermal electricity generation and utility-scale energy storage, using historical data from California for all of year 2015. Most striking, the analysis finds that a majority (over 60%) of the economic opportunities are available solely through real-time markets and ancillary services, which require fast flexibility (at 15-minute and shorter timescales) to monetize. In contrast, most previous techno-economic studies focus on slower timescales (hour resolutions). Our results indicate that such analyses are misleading, as they undervalue flexibility and economic potential. Moreover, these results highlight opportunities for new materials, devices, and energy systems that can provide fast flexibility.
Investing in energy infrastructures often involves many stakeholders with conflicting priorities for multiple social, technical, economic and environmental objectives. Part 2 of this seminar presents a decision-making framework to compute families of Pareto efficient compromise solutions. Coherent risk metrics are used to shape the distribution of stakeholder satisfactions and interpret the impact of individual stakeholder opinions. Through two applications, selection of combined heat and power conversion technologies to meet multi-energy demands for residential housing complexes and placing infrastructure to process organic waste, we demonstrate how the framework identifies perceptive compromises, helps resolve conflicts, and facilitates targeted negotiations. As energy infrastructures grow in complexity and interdependence, multi-stakeholder conflict resolution will become increasingly important.
Bio:
Alexander (Alex) Dowling is a postdoctoral fellow in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison working with Prof. Victor M. Zavala. He completed his PhD in Chemical Engineering at Carnegie Mellon University under the supervisor of Prof. Lorenz T. Biegler. Dr. Dowling's research seeks to develop systems engineering approaches grounded in firsts principles mathematical modeling and large-scale nonlinear optimization to design and control a broad variety of energy technologies. Applications include advanced separations, electricity generation with CO2 capture, combined heat and power systems, electrochemical energy storage, and large-scale solar thermal energy harvesting. Dr. Dowling's interest in systems engineering dates back to his undergraduate days, during which he raced twice as the Head Strategist of the University of Michigan Solar Car Team (North American Solar Challenge in 2008, World Solar Challenge (Australia) in 2009).
