2015 Informs Annual Meeting

SA58

INFORMS Philadelphia – 2015

SA58 58-Room 110A, CC Multi-Agent Decision-Making for Smart Grids Operation I Sponsor: ENRE – Energy I – Electricity Sponsored Session Chair: Amin Kargarian, Carnegie Mellon University, 5000 Forbes Ave, Pittuburgh, PA, 15232, United States of America, amin.kargarian@gmail.com 1 - A Fast Distributed Algorithm for Power Optimization Problems Ramtin Madani, Columbia University, 116th St. & Broadway, New York, NY, 10027, United States of America, madani@ee.columbia.edu, Abdulrahman Kalbat, Javad Lavaei This talk aims to develop an efficient numerical algorithm for power optimization problems by leveraging the small treewidth of real-world power grids. To this end, a distributed algorithm is proposed for arbitrary conic programs with a low treewidth, based on the alternating direction method of multipliers (ADMM). The iterations of this algorithm consist of two subproblems, which are highly parallelizable and enjoy closed-form solutions. The algorithm is tested on several power systems. 2 - Demand Response using Supply Function Bidding An abstract market model based on supply function bidding is proposed for demand response to match power supply fluctuations. We characterize the resulting equilibria in competitive and oligopolistic markets and analyze the efficiency of the equilibria. The equilibrium in competitive market maximizes social welfare, and the equilibrium in oligopolistic market has bounded efficiency loss under certain mild assumptions. We also propose distributed algorithms to achieve the equilibria. 3 - Community Storage for Firming Chenye Wu, Postdoctoral Fellow, UC Berkeley, 60 Panoramic Way, Berkeley, CA, 94704, United States of America, wcy@ieee.org, Kameshwar Poolla We analyze the benefit of storage capacity sharing for a set of residential consumers in a community. Each consumer has its own choice of either installing its own storage system or investing in a shared storage system. In the latter case, they must also decide on a scheme to allocate the costs. We formulate the problem as a cooperative game and identify an efficient and stable cost allocation rule. We further show this cost allocation rule induces a weakly incentive compatible mechanism. 4 - Fully Distributed Approach for Optimal Power Flow Calculations Javad Mohammadi, Carnegie Mellon University, Electrical and SA59 59-Room 110B, CC Open Pit Mining Sponsor: ENRE – Natural Resources I – Mining Sponsored Session Chair: Alexandra Newman, Professor, Colorado School of Mines, Mechanical Engineering, Golden, CO, 80401, United States of America, anewman@mines.edu 1 - Open Pit Mine Scheduling with Variants on Inventory Considerations Mojtaba Rezakhah, PhD Student, Colorado School of Mines, Godlen, CO, 80401, United States of America, mrezakha@mymail.mines.edu We present several ways of modeling stockpiling (with and without considering degradation) in open pit mine production scheduling, including (i) individual stockpiles for each block and (ii) binned stockpiles with pessimistic grade estimates. These models are formulated for a currently operational mine and compared to results without stockpiling in order to assess the benefits of stockpiling and to analyze the relationship between milling capacity and stockpiling value. Na Li, Assistant Professor, Harvard University, 33 Oxford St, MD 147, Cambridge, Ma, 02138, United States of America, nali@seas.harvard.edu, Lijun Chen, Munther Dahleh Computer Engineering, CMU, Pittuburgh, PA, 15232, United States of America, jmohamma@andrew.cmu.edu In this talk, we propose a method which enables a fully distributed solution of the DC Optimal Power Flow problem. The approach consists of an iterative procedure that aims at solving the first order optimality conditions in fully distributed manner at both nodal and regional level.

2 - Models for Inventory Allocation of Erratic-demand Spare Parts in a Multi-echelon System Andrea Arias, PhD Student, Universidad Catolica de Valparaiso,

Avda Brasil 2241, Piso 6, Valparaiso, V, 2362807, Chile, andari20@gmail.com, Jimena Pascual, Timothy Matis

Mining industry has processes that are carried out by complex machines with many parts, which are reparable upon failure. We consider a two-level supply chain inventory system for high cost/low demand repairable items. The aim is to determine inventory levels for each item at every warehouse in order to maximize system availability. We will present a comparative study between two approaches used for addressing this problem from which some interesting ideas for further research are proposed. 3 - Operational Flexibility in the Gold Mining Industry Panos Markou, IE Business School, Calle Maria de Moina 12 Bajo, Madrid, 28006, Spain, pmarkou.phd2016@student.ie.edu, Daniel Corsten Gold mining companies are highly exposed to commodity price risks. We examine the effects of using “high-grading” (to combat these risks) on the operational and financial performance of the miners. We find that although high-grading can increase gross margin and profitability, it also increases profit variance and inventory levels. Further, we show that these undesirable effects can be reduced through financial hedging strategies. 4 - Using The Bienstock-Zuckerberg Algorithm for Large-scale, Real-world Mine Planning Problems Alexandra Newman, Professor, Colorado School of Mines, Mechanical Engineering, Golden, CO, 80401, United States of We apply an algorithm that solves the LP relaxation of precedence-constrained knapsack problems to mine planning models which determine when to extract a notional three-dimensional block of ore or waste, or when to commence an activity (e.g., development, extraction) so as to maximize net present value, subject to spatial precedence constraints and resource bounds. A simple heuristic provides good integer-feasible solutions. Real-world instances from various settings provide compelling results. SA60 60-Room 111A, CC Evaluating Student Learning Sponsor: INFORM-ED Sponsored Session Chair: Sadan Kulturel-Konak, Professor, Pennsylvania State University, Berks Campus, Reading, PA, 19609, United States of America, sadan@psu.edu 1 - Assessing Students’ Global Awareness Sadan Kulturel-Konak, Professor, Pennsylvania State University, Berks Campus, Reading, PA, 19609, United States of America, sadan@psu.edu Students are expected to become increasingly globally aware in order to be better prepared for a career in an international knowledge-based society. We define global awareness knowledge, skills and abilities (KSA) that need to be met for a student to be proficient in global awareness and define an assessment framework based on the Model of Domain Learning (MDL). The preliminary findings for the effectiveness of the proposed global awareness interest assessment will be presented. 2 - A Web-based Peer Evaluation Tool for Professional Skills Assessment Abdullah Konak, Professor, Penn State Berks, Tulpehocken Road, P.O. Box 7009, Reading, PA, 19610, United States of America, konak@psu.edu We introduce the Peer Evaluation & Assessment Resource (PEAR), which is a web-based solution that was created to efficiently assess the teamwork skills of students through peer and self-evaluations. The PEAR application allows instructors to form teams and choose a rubric to assess their teamwork skills and contributions. In addition to built-in PEAR rubrics, instructors can also create custom rubrics based on the Model of Domain Learning to better suit their specific courses. America, anewman@mines.edu, Marcos Goycoolea, Eduardo Moreno, Daniel Espinoza, Andrea Brickey

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