2015 Informs Annual Meeting

SA62

INFORMS Philadelphia – 2015

SA62 62-Room 112A, CC Optimization Models for Bioenergy Production and Delivery Sponsor: ENRE – Environment I – Environment and Sustainability Sponsored Session Chair: Mohammad Roni, Computational Energy Analyst, Idaho National Laboratory, P.O. Box 1625,, Idaho Falls, ID, 83401, United States of America, mohammad.roni@inl.gov 1 - Economic, Environmental and Social Optimization of an Integrated Bioenergy and Biofuel Supply Chain A multi-objective optimization model is proposed for the network design and strategic planning of integrated bioenergy and biofuel supply chains using forestry by-products as feedstock. The objectives of the model are to maximize the NPV, maximize the GHG emissions savings, and maximize the number of direct jobs created. The model was applied to a case study in British Columbia, and a set of Pareto-optimal solutions was obtained using the augmented ?-constraint (AUGMECON) method. 2 - Analyzing Stranded Biomass Resource: Regional Case Study in the United States of America Mohammad Roni, Computational Energy Analyst, Idaho National Laboratory, P.O. Box 1625,, Idaho Falls, ID, 83401, United States of America, mohammad.roni@inl.gov, Ross Hays, Damon Hartley, Erin Searcy National assessment such as Billion Ton Study has projected biomass resources to meet biofuel production targets. But resources are often inaccessible because of unfavorable economics—labeled as “stranded resources”. This study quantifies stranded resources under conventional and proposed distributed depot based supply design. A mixed integer, linear programming is formulated to quantify the stranded resource. We perform a regional case study based on agricultural residues and energy crops. 3 - Potential Savings and Cost Allocations for Forest Fuel Transportation in Sweden Mario Guajardo, Assistant Professor, NHH Norwegian School of Economics, Helleveien 30, Bergen, 5045, Norway, Mario.Guajardo@nhh.no, Patrik Flisberg, Mikael Frisk, Mikael Ronnqvist Efficient logistics is crucial to make forest fuels a competitive source of bioenergy. By using optimization models and a decision support system, we study alternatives to lower the costs in a case that accounts for all forest fuel transport operations in Sweden. This involves 200,000 transports of about 6.1 million tons of forest biomass. We identify potential savings of about 22%. As one of the alternatives is collaboration, we test cost allocation methods based on cooperative game theory. 4 - GIS-Based Allocation of Lignocellulosic Biorefineries and Depots Daniela S. Gonzales, Texas A&M University, College Station, TX, United States of America, anielasofiagonzales@gmail.com, Stephen W. Searcy Our objective was to determine the structure of the likely biomass feedstock supply chain that will develop in the US based on the DOE concept of an advanced uniform feedstock format; the predicted availability of biomass (presented in the 2011 Billion Ton Study Update), the geographic location of suitable lands for biomass (based on the 2011 National Land Cover Data), and the transportation infrastructure. We use ArcGIS tools to identify the location of biorefineries and depots in the US. Taraneh Sowlati, University of British Columbia, 2931-2424 Main Mall, Vancouver, BC, V6T1Z4, Canada, taraneh.sowlati@ubc.ca, Claudia Cambero

3 - Use of Pretesting to Assess Retention of Prerequisite Knowledge Jill Wilson, Northwestern University, 2145 Sheridan Rd., Room C211, Evanston, IL, 60208, United States of America, jill.wilson@northwestern.edu, Karen Smilowitz, Barry Nelson We describe a pretest assessment scheme designed to test student retention of knowledge obtained in prerequisite courses. Although useful in documenting continuous improvement for ABET accreditation, pretests most importantly help identify students who are unprepared for the current course and help faculty to identify course-wide deficiencies that need remediation. We describe content of pretests, details of implementation, and insights gleaned from data collected in the first two years. 4 - Georgia Tech’s Systematic Approach to Improving PhD Students’ Academic Job Talks and Interviews Judith Norback, judith.norback@isye.gatech.edu, Alan Erera Our goal is improving the academic job talks and interviews of IE/OR PhD candidates currently on the job market. We describe the systematic work done to identify instructional activities for the students. The seven steps we took were: 1) observing PhD student INFORMS talks, 2) interviewing faculty to identify what they expect in an excellent talk, 3) conducting a workshop where each student gives a brief presentation and receives feedback from a presentation expert, 4) holding oral skills meetings for instruction and practice, and 5) having a faculty panel discussion of how to conduct interviews. 6) Finally, once a student has arranged an interview, they give a practice talk to their advisers and the presentation expert, and 7) the expert joins them in a final oral skills meeting. Preliminary feedback from students and faculty, and instructional materials, will be shared. SA61 61-Room 111B, CC Electricity Markets and Renewable Power Sponsor: ENRE – Energy I – Electricity Sponsored Session Chair: Nur Sunar, Assistant Professor, University of North Carolina, Kenan-Flagler School of Business, Chapel Hill, NC, United States of America, Nur_Sunar@kenan-flagler.unc.edu 1 - Stochastic Co-Optimization Framework for Renewable Power Generation Shijie Deng, Georgia Inst of Tech, 755 Ferst Dr, Atlanta, GA, United States of America, sd111@gatech.edu, Anthony Papavasiliou We proposes a stochastic programming framework for solving the optimal scheduling problem faced by a renewable power producer that simultaneously participates in multiple markets. Specifically, the renewable-generator participates in both the electricity spot market and the ancillary services market as a price taker. Numerical case studies on the advantages of the proposed strategy for a wind-generator to hedge market uncertainties are carried out with a set of realistic parameters. 2 - Lessons from Large Scale Transmission Planning using Stochastic Programming in WECC Qingyu Xu, Johns Hopkins University, 3400 North Charles Street, Baltmore, MD, 21218, United States of America, qxu25@jhu.edu, Saamrat Kasina, Jonathan Ho, Pearl Donohoo-vallett, Yueying Ouyang, Benjamin Hobbs A 21-zone model and a 300-bus model of the western North America interconnection are used to optimize transmission and generation investment and production, facing uncertain economic, regulatory and climate scenarios. The stochastic optima show very different patterns of transmission/generation investment compared to deterministic solutions. The economic impacts of various model simplifications are compared, including the network, number of scenarios, and generator unit commitment. 3 - Supply Function Bidding with Uncertain Supply and Demand: Electricity Markets and Renewable Power Nur Sunar, Assistant Professor, University of North Carolina, Kenan-Flagler School of Business, Chapel Hill, NC, United States of America, Nur_Sunar@kenan-flagler.unc.edu, John Birge Motivated by high penetration of renewables into electricity generation mix, we introduce and analyze a supply function competition model with both supply and demand uncertainty. Using the ODE theory, we characterize a supply function equilibrium, and analyze the implications of different penalty schemes and subsidy for equilibrium day-ahead market clearing price, production schedules and actual production quantities of generators. We also calibrate our model based on MISO’s data.

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