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MA9 - EF1: Solar energy
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Presentations | ||
Towards industrial decarbonization via robust solar capacity expansion Massachusetts Institute of Technology, United States of America We present our collaboration with OCP, the world’s largest producers of phosphate and phosphate-based products, in support of a green initiative designed to reduce the company’s greenhouse gas emissions. The proposed robust optimization-based methodology guides the company’s investment in solar panels and batteries, which accounts to over one billion US dollars, as well as their day-to-day operations, and is expected to significantly reduce both the company’s emissions and energy bill. Electric vehicles and solar panels co-adoption via diffusion models 1Gies College of Business, University of Illinois Urbana-Champaing, United States of America; 2Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaing, United States of America; 3Gies College of Business, University of Illinois Urbana-Champaing, United States of America; 4Universidad Pontificia Comillas, Madrid, España Electrification is as a critical enabler of the decarbonization. It is imperative to study the growth in electric vehicles adoption to plan for this impending transformation. Existing EV adoption studies typically ignore the influence of other green technologies. In this paper, we bridge these critical gaps. We employ a dynamic discrete choice model to study these technologies' diffusion. Our work projects adoption and evaluates counterfactual scenarios. Retreat, defend, or attack? Optimal investment decisions in green technology under competition 1University of Calgary, Canada; 2Eindhoven University of Technology; 3KU Leuven Firms that already invest in more sustainable technologies as a proactive measure against changing market dynamics, are likely to gain a significant competitive advantage. We analyze a large focal firm's optimal green investment strategy, accounting for the uncertainty in the competitors' actions and the future green market size. Optimal policy is composed of `Retreat’, `Defend’, and `Attack’ strategies, one of which is optimal based on the problem parameters. We provide managerial insights. |