2015 Informs Annual Meeting

TD57

INFORMS Philadelphia – 2015

TD57 57-Room 109B, CC Modeling the Economics of Low-Carbon Power Systems Sponsor: ENRE – Energy I – Electricity Sponsored Session Chair: Todd Levin, Energy Systems Engineer, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL, 60439, United States of America, tlevin@anl.gov 1 - Revenue Sufficiency and Resource Adequacy in Systems with Variable Generation Resources Todd Levin, Energy Systems Engineer, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL, 60439, United States of America, tlevin@anl.gov, Audun Botterud An efficient MIP framework is applied to analyze the impact of increasing wind power capacity on generator profitability. The model is executed with hourly time steps on a test case that approximates the ERCOT system for a range of wind capacity levels. We analyze three market policies that support resource adequacy and find that some additional market incentives may be required to ensure long term revenue sufficiency and resource adequacy in systems with significant variable energy resources. 2 - An Approximate Model for Scheduling Energy and Reserve in Renewable-Dominated Power Systems Since most of renewable energies are non-dispatchable, an appropriate schedule of reserves in renewable-dominated power systems is crucial. We propose an alternative formulation that co-optimizes energy and reserve considering the uncertainty involved in demand and renewable production. This formulation requires a significantly smaller number of variables and constraints than the classical stochastic economic dispatch problem. The proposed formulation is tested in a realistic case study. 3 - Hydroelectric Bid Optimization under Uncertainty Andy Philpott, University of Auckland, Engineering Science Department, Private Bag 92019, Auckland, 1025, New Zealand, a.philpott@auckland.ac.nz, Faisal Wahid, Frederic Bonnans, Cedric Gouvernet We consider the problem faced by the operator of a cascade of hydroelectric generating plants offering energy to a wholesale electricity pool market to maximize revenue. Both energy prices and uncontrolled inflows to the reservoirs of the cascade are assumed to be stochastic. We describe a stochastic dynamic programming model that generates an optimal offer for the next period given current observed prices. This is solved using SDDP when value functions are concave or MIDAS when they are not. 4 - Optimal Timing to Invest, Mothball, Reactivate, and Decommission a Coal Power Plant Paul Rebeiz, Doctoral Candidate In Operations Mangement, UCLA Anderson School of Management, 110 Westwood Plaza, Transitioning to a low-carbon economy will require most coal power plants to be replaced by other sources of generation such as wind and solar. We present a dynamic program to solve for the optimal price signals to invest, mothball, reactivate, and decommission a coal power plant. We find that our results are consistent with current industry trends. We conclude with some insights on the effect of renewable energy policy on mothballing and retiring a coal plant. Miguel Carrion, Universidad de Castilla - La Mancha, Av. Carlos III, s/n, Toledo, Spain, miguel.carrion@uclm.es, Rafael Zarate-miñano Los Angeles, CA, 90025, United States of America, paul.rebeiz.1@anderson.ucla.edu, Christian Blanco

4 - On Integrating DEA and AHP for the Facility Layout Design in Manufacturing Systems Toloo Mehdi, Technical University of Ostrava, Ostracew, Czech Republic, mehdi.toloo@vsb.cz Analytic hierarchy process (AHP) is a decomposition multiple-attribute decision making (MADM) method, which can represent human decision making process and help to achieve better judgments based on hierarchy, pair-wise comparisons, judgment scales, allocation of criteria weights and selection of the best alternative from a finite number of variants by calculation of their utility functions. Data envelopment analysis (DEA) is a well-known non-parametric method to evaluate the performance of a set of homogeneous decision making units (DMUs) with multiple inputs and multiple outputs. 5 - The Efficiency of Tunisian Universities: An Application of a Two-Stage Dea Approach

Samir Srairi, Ministry of Higher Education and Scientific Research, 14 Avenue de Tunis, Arian, 2080, Tunisia, srairisamir3@gmail.com

This paper examines the efficiency of eleven universities in Tunisia during the period 2009-2013. Regression analysis suggests that a higher share of professors, a higher number of women in academic staff and a better quality of student in secondary education improve the efficiency of the university.

TD56 56-Room 109A, CC Project Selection, Evaluation and Collaboration Cluster: New Product Development Invited Session Chair: Yaozhong Wu, National University of Singapore, NUS Business Zhijian Cui, Assistant Professor of Operations and Technology Management, IE Business School, Calle de Maria de Molina 12, Madrid, 28006, Spain, Zhijian.Cui@ie.edu, Shijith Payyadak, Dilney Gonçalves In this study, we design several online experiements to compares the efficacy of two commonly observed processes of idea selection: scoring vs. ranking. In scoring process, subjects are asked to evaluate the quality of each idea and give a score while in ranking process, subjects are asked to only rank the ideas according to their prefereces. We find that the choice of idea selection process depends on some contextual factors. 2 - Overvaluation of Process Innovation Ideas Fabian Sting, Erasmus University Rotterdam, Rotterdam, Netherlands, fsting@rsm.nl, Christoph Fuchs, Maik Schlickel Ideas by employees are a vital source for innovation. But are such ideas overvalued by their creators? If so, which ideas in particular? Drawing on a unique data set that comprises the generation, election, and implementation of process improvement ideas of an automotive supplier, we identify antecedents of overvalued ideas. Overvaluation is greater for ideas generated by higher-level employees, collaboratively versus individually, and by employees with previously lower ideation success. 3 - Project Evaluation and Selection via Risk-adjusted Net Present Value Nicholas G. Hall, The Ohio State University, Fisher College of Business, Columbus, OH, United States of America, hall.33@osu.edu, Zhixin Liu, Wenhui Zhao We consider a project with risk that declines over time as its tasks are completed, as reflected in a declining discount rate. The objective is to maximize the NPV of the project. This problem is highly nonlinear, since the discount rate at any point in time is a function of previous scheduling decisions. We solve this model and show that risk-adjusted NPV varies significantly from traditional NPV, and that the use of the risk-adjusted measure significantly improves project selection decisions. 4 - Resource Competitions for Research Projects Pascale Crama, Singapore Management University, 50 Stamford Road, Singapore, 178899, Singapore, pcrama@smu.edu.sg, Anand Nandkumar, Reddi Kotha Academic research is funded by governments, but is often seeded through grants from university administered research funds (UARF) and other charitable institutions. We compare the effectiveness of UARF and other sources of funds in obtaining subsequent federal funding and value creation. We build a parsimonious model that can explain the superior productivity of UARF funding and make recommendations on the ideal way to organize UARF funding. School, Singapore, Singapore, yaozhong.wu@nus.edu.sg 1 - An Experiemental Study of Idea Selection Process

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