Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MA46

4 - A Bound Strengthening Method for Optimal Transmission Switching in Power Systems Salar Fattahi, University of California-Berkeley, Berkeley, CA, 94702, United States, Javad Lavaei, Alper Atamturk This paper studies the optimal transmission switching (OTS) problem for power systems. Most of the existing methods for the problem are based on first converting the OTS into a mixed-integer linear program (MILP) or quadratic program (MIQP), and then iteratively solving a series of its convex relaxations. In this work, it is shown that finding the strongest big-M inequalities to be used in an MILP or MIQP formulation of the OTS is NP-hard. Despite the difficulty of obtaining the strongest bounds in general, a simple bound strengthening method is presented to strengthen the convex relaxation of the problem. Remarkable improvements in the performance of the solvers are achieved compared to other methods. n MA46 North Bldg 228B The Water-Energy-Food Nexus Sponsored: Energy, Natural Res & the Environment/Energy Sponsored Session Chair: Alexandra M. Newman, Colorado School of Mines, Golden, CO, 80401, United States 1 - Designing River Basin Storage using Optimization Andy Burrow, Colorado School of Mines, Golden, CO, 80401, United States, Alexandra M. Newman The ways in which a growing population increases hydrologic demand are often evaluated using simulation models. This research uses data produced by the State of Colorado’s Stream Simulation Model as input to an optimization model to determine the flow of unappropriated water so as to minimize the cost of water shortage mitigation while adhering to constraints that force the physical and topographical structures of the river. Solutions combine upstream pumping and new storage in existing reservoirs, as well as storage in new surface and subsurface reservoirs. 2 - Integrated Modeling of Food-energy-water Nexus in Ethiopia Siram Sankaranarayanan, Johns Hopkins University, Baltimore, MD, United States, Ying Zhang, Jess Carney, Benjamin Zaitchik, Sauleh Ahmad Siddiqui We present an integrated partial equilibrium model to understand the effects of interventions to improve food, energy, and water security in Ethiopia. We have a food model, which computes the equilibrium land allocated for various crops, and details of the food supply chain each year. This is coupled with an energy model, which models power generation, transmission and consumption. These models are coupled through prices and quantities along their supply chains. The model can be used to assess shifts in welfare under various policies. We run the model under improved irrigation capabilities, which might reduce power generation from hydel plants and understand the difference in welfare. 3 - Optimizing Water Distribution Operation for Providing Energy Demand Flexibility Konstantinos Oikonomou, University of Utah, Salt Lake City, UT, United States, Masood Parvania This talk will present a model to optimize the operation of water distribution systems (WDSs) for providing energy flexibility to power systems operation. The proposed model optimizes the operation of pumps and tanks for minimizing the operation cost of WDS, given the expected water demand and electricity prices of the next day. The proposed model then calculates and offers the feasible flexible energy capacity of WDS to the power system operator. The proposed model takes into account the hydraulic operating constraints of water networks, thus ensuring deliverability of the WDS energy flexibility. 4 - Optimal Control of a Single Wave-energy Converter Mertcan Yetkin, Lehigh University, Bethlehem, PA, United States, Frank E. Curtis, Lawrence V. Snyder, Sudharsan Kalidoss This research proposes a generic optimal control formulation for a single wave- energy converter (WEC) from an operations research perspective. Our model adds hard and soft constraints on the motion of the WEC in order to promote safe operation of the device. The hydrodynamic coefficients of the system are estimated using simulation. The resulting problem is formulated as a quadratic program (QP) with a non-convex objective function. We demonstrate the trade- off between the safe operation of the device and the power generated. Finally, the optimal control policy is compared to some classical control strategies to illustrate the improvement in the performance.

n MA47 North Bldg 229A Joint Session Tutorial/HAS: Optimization of Sequential Decision Making for Chronic Diseases: From Data to Decisions Emerging Topic Session Chair: Esma S. Gel, Arizona State University, School of Computing, Informatics and, Decision Systems Engineering, Tempe, AZ, 85287- 8809, United States 1 - Optimization of Sequential Decision Making for Chronic Diseases: From Data to Decisions Brian T. Denton, University of Michigan, University of Michigan, Ann Arbor, MI, 48109-2117, United States Rapid advances in medical interventions for chronic diseases such as cardiovascular disease, cancer, and diabetes have made it possible to detect diseases at early stages and tailor treatment pathways to individual patients based on their risk factors including gender, race/ethnicity, and disease-specific factors. However, the large number of relevant risk factors to be considered, combined with uncertainty in future health outcomes and treatment side effects, makes optimizing these decisions challenging. Randomized trials are the gold standard for selecting treatment interventions but the large number of possible decisions and their high cost makes these trials infeasible. Data-driven operations research methods are showing great promise in helping patients and medical doctors improve decisions about health interventions. Observational data that is now routinely collected in many health systems is a valuable resource for fitting and validating stochastic models for chronic diseases. Moreover, optimization methods for sequential decision making, including Markov decision processes, partially observable Markov decision processes, and reinforcement learning methods, exploit these models to optimize treatment policies that can balance competing criteria such as the harms and benefits associated with treatment of chronic diseases. This tutorial provides an introduction to some of the most commonly used approaches for using raw data for the purpose of optimizing sequential treatment policies. Special attention is paid to the challenges associated with using observational data and the influence of model parameter uncertainty in this context. n MA48 North Bldg 229B Empirical Research in Sustainability Sponsored: Energy, Natural Res & the Environment Environment & Sustainability Sponsored Session Chair: Kejia Hu, Vanderbilt University, Nashville, TN, 37215, United States 1 - An Analysis of Time-based Pricing in Retail Electricity Markets Asligul Serasu Duran, Haskayne School of Business, University of Calgary, Calgary, AB, Canada, Baris Ata, Ozge Islegen We empirically evaluate the short-term effects of time-based tariffs on the electricity demand, consumer welfare, retailers and the environment. We find that focusing on the peak-load reduction, one can design a flexible time-of-use (TOU) tariff that is simple and predictable yet performs as well as real-time pricing (RTP) given a fixed time horizon for evaluation. The annual electricity bills of consumers decrease only slightly after switching to time-based tariffs, but there can be significant volatility in month to month bills. In contrast, retailers see less volatility in their profits under more flexible tariffs. The environmental impact depends on the electricity market under study. 2 - Retailer Strategies to Encourage Reduced Packaging Adoption Olga Pak, 105 Carolina Ridge Drive, Columbia, SC, 29229, United States, Michael Galbreth, Mark Ferguson For manufacturers, the reduction of product packaging is associated with marketing/product positioning risks, like diminished product visibility and lower perceived value. In this paper, we explore the tools retailers can use to mitigate such concerns, and, thus, convince manufacturers to make packaging more operationally efficient and sustainable.

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