INFORMS 2021 Program Book

INFORMS Anaheim 2021

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6 - Building an Approach to DEI-Informed Research in OR/Analytics Michael P. Johnson, University of Massachusetts-Boston, Boston, MA, 02125-3393, United States, Tayo Fabusuyi The goal of this project is to develop principles by which researchers in OR/analytics may integrate ideas about diversity, equity and inclusion, racial and social justice and antiracism into research ideas that span application areas, disciplinary modes and analytic methods. 7 - “Now What?” A Mid-Career Faculty Colloquium for Underrepresented Groups Illya V. Hicks, Rice University, Houston, TX, 77005-1827, United States, Julie Ivy, Maria Mayorga The tenure track can be complex for faculty, this is particularly true for mid- career faculty, for underrepresented minority faculty and for women of color faculty [3]. While significant attention is paid to preparing faculty to begin a tenure track faculty career and to some extent to attain tenure, less attention has been paid to mid-career faculty who are post-tenure associate professors seeking to be promoted to full professor. This ambiguity can be even more taxing for underrepresented faculty. The objective of this project is to empower underrepresented minority mid-career faculty in operations research and management science to navigate the promotion and tenure track to facilitate their successful promotion. Our project will develop and host a mini-professional development workshop for underrepresented minority faculty who are late stage assistant professors and associate professors modeled after the NSF-funded ACW: Academic Career Workshop for Underrepresented Junior Faculty and Senior Graduate Students workshop. 8 - Stimulating Participation of underrepresented Groups in INFORMS Editorial Boards Alice E. Smith, Auburn University, Auburn, AL, 36849, United States This project aims to increase the diversity of participants in journal editor activities, with an emphasis on INFORMS journals. Journals, as the main outlet for scholarly publications, are hallmarks of careers in academia and research. Participation is crucial to the advancement and sharing of knowledge, as editors and reviewers provide the key input and decision making in the dissemination of research. This talk will cover the objectives and the activities of this project, which include a webinar in May and a planned panel at the annual conference. 9 - Computational Thinking and Equity an Online Tapia Camp for 7-12th Graders Paul Hand, Northeastern University, Boston, MA, United States, Richard Tapia, Juan Pablo Vielmo, Leticia Velazquez This virtual camp was developed by the Tapia Center and Google’s Operations Research Team, and funded by INFORMS DEI. Participants will learn computational thinking skills and design their own algorithm for an important societal challenge: college admissions. The 7th-12th graders will analyze how equitable and fair their algorithm is in deciding which students are allowed to enroll in which colleges. They will interact with college students and STEM Operations Research professionals. MC40 CC Room 211B In Person: Machine Learning for Power Systems General Session Chair: Kyri Baker, University of Colorado-Boulder, Boulder, CO, 80309, United States 1 - Learning a Good Chance-Constraint Approximation From Data: a Tuning-based Approach to Chance-Constrained Optimal Power Flow Line Roald, University of Wisconsin Madison, Los Alamos, NM, United States, Ashley Hou Chance constrained optimization is a popular approach to ensure secure and economic operations of power systems with renewable energy. Chance constrained optimization can be challenging and typically involves a trade-off between solution quality (solution cost and feasibility guarantees) and numerical tractability (e.g., number of considered scenarios). In this talk we describe a tuning-based approach which utilizes intentionally simplistic chance-constraint formulations combined with data-driven tuning to obtain high quality solutions at low computational effort. We further discuss why a naïve implementation of such methods does not provide probabilistic performance guarantees, and propose a two-step approach with a solution generation step and solution verification step to restore such guarantees. 2 - Speeding Up Power Systems Optimization Problems with Deep Learning Kyri Baker, University of Colorado Boulder, 1111 Engineering Dr., UCB 428, Boulder, CO, 80309, United States, Mostafa Mohammadian As more fast-fluctuating renewable energy is being introduced into power grid operations, the need for computationally efficient solutions to optimize the

operation of these resources is increasing. In this talk, we discuss ways that neural networks can be used to greatly speed up AC optimal power flow (OPF), distributed DC OPF, and economic dispatch problems with inter-temporal constraints, pursuing optimality while preserving feasibility of the resulting solutions.

MC41 CC Room 212A

In Person: Quantitative Modeling of Non-cost Outcomes in Energy Systems Planning Models General Session Chair: Neha Patankar, Princeton University 1 - Demand Side Risk Management For Electricity Supply Shmuel S. Oren, Professor of the Graduate School, University of California, Berkeley, Berkeley, CA, United States The proliferation of distributed resources and renewables into the electricity supply mix and growing demand side participation in the power system requires new market mechanisms for integrating demand flexibility into the power market. We propose Virtual Power Plants (VPP) consisting of a portfolio of flexible demand resources controlled by edge technologies and dispatched according to priority service contracts. We describe the construction of a supply function for such VPPs which will be offered in the wholesale markets for energy and reserves. 2 - On Efficient Aggregation of Distributed Energy Resources Zuguang Gao, University of Chicago, Chicago, IL, 60637, United States, Khaled Alshehri, John R. Birge The rapid expansion of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Due to the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper an efficient aggregation model where a profit-maximizing aggregator procures electricity from DERs, and sells them in the wholesale market. The interaction between the aggregator and the DER owners is modeled as a Stackelberg game: the aggregator adopts two-part pricing by announcing a participation fee and a per-unit price of procurement for each DER owner, and the DER owner responds by choosing her payoff- maximizing energy supplies. We show that our proposed model preserves full market efficiency. 3 - Land Use Trade-offs in Decarbonization Of Electricity Generation in the American West Neha Patankar, Princeton University Land use availability conflicts may present critical non-cost related bottlenecks to least-cost portfolios for electricity decarbonization. This study employs a spatially- temporally- and operationally resolved electricity system capacity expansion model and the modeling to generate alternatives (MGA) technique to generate a set of diverse technology portfolios to reach zero-carbon electricity supply in the Western Interconnection, all with similar costs. The methods demonstrated in this study are well suited to evaluate other non-cost related trade-offs and multiple system-wide objectives of a decarbonized electricity system such as reducing air pollution or achieving regional equity in renewables-related employment. MC42 CC Room 212B In Person: OR/MS and the Public Sector Contributed Session Chair: Justin T. Huang, University of Michigan Ross School of Business, Ann Arbor, MI, 48104-1754, United States 1 - Coalition Formation and Cost Allocation in Humanitarian Supply Chain Collaboration in humanitarian supply chains may lead to higher quality services and significant cost savings. To achieve these benefits, two main questions must be answered: who should cooperate with whom and how should the savings be allocated among cooperative partners to ensure stability? We address these questions by (1) proposing and testing heuristics to identify coalition structures that minimize total social cost, and (2) identifying allocation mechanisms that belong to the coalition structure core. The results provide insights for managing humanitarian operations. 2 - Practical Redistricting for Missouri Using Recombination Kiera Dobbs, University of Illinois at Urbana-Champaign, Urbana, IL, United States, Rahul Swamy, Ian Griffith Ludden, Douglas M. King, Sheldon H. Jacobson Over the past decade, numerous optimization methods have been presented to create fair district plans. Since states will redraw their districts in 2021, it is critical Sogand Sabahfar, PhD Student, Kansas State University, Manhattan, KS, United States, Jessica Heier Stamm

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