2015 Informs Annual Meeting

WC63

INFORMS Philadelphia – 2015

WC61 61-Room 111B, CC

We formulate a mixed integer linear program to select renewable technologies such as wind and solar, and conventional technologies such as diesel generators and batteries, to minimize system costs subject to operational, load, and spinning reserve constraints. We use statistical models to generate realizations of load, solar irradiance and wind speed. Solutions from our optimization model prescribe both a procurement and a dispatch strategy for these realizations, with additional realistic data. 2 - Robust Unit Commitment Problem with Valid Inequalities and Computational Study Wei Wang, PhD Student, University of South Florida, 4202 E.Fowler Ave. ENB, Tampa, FL, 33620, United States of America, weiw@mail.usf.edu, Bo Zeng In order to improve the computational performance of robust unit commitment problem, we study the polyhedron of unit commitment problem, derive some valid inequalities and incorporate them into robust formulation. Preliminary computational results will be presented to evaluate their impact. 3 - Integration of Demand Dynamics and Investment Decisions on Distributed Energy Resources Farbod Farzan, Rutgers University, 96 Frelinghuysen Road, Piscataway, Ne, 08901, United States of America, farbod_farzan@yahoo.com, Farnaz Farzan, Mohsen Jafari We coupled investment decisions on distributed generation(DG) with demand side management(DSM). An adaptive model is used for load calculations on a premise that expected dynamical effects due to DSM strategies cannot be captured by forecast models. To demonstrate the effect of coupling of DG investment decisions and DSM, three scenarios(S) are presented. SI is used for benchmarking. Load patterns for PEVs are introduced in SII. SIII is an extended version of SII, where smart devices are adopted 4 - Multi-objective Optimization of Grid-connected Decentralized Energy Systems Ayse Kocaman, Assistant Professor, Bilkent University, Bilkent Universitesi, Endustri Muhendisligi, Ankara, 06800, Turkey, selin.kocaman@bilkent.edu.tr, Ozlem Karsu Along with the transition from fossil fuel based centralized energy systems to decentralized renewable energy systems, decision makers will have to make a choice between using two types of electricity, one of which is less expensive but also associated with high CO2 emissions and the other is clean but more costly. Here, we develop a decision support system that decides on the scales of energy production facilities to be used in the process of moving towards decentralized energy systems.

Optimization under Uncertainty: Integration of Intermittent and Demand Side Resources in Electric Power Systems Sponsor: ENRE – Environment I – Environment and Sustainability Sponsored Session Chair: Lindsay Anderson, Assistant Professor, Cornell University, 316 Riley Robb Hall, Ithaca, NY, 14853, United States of America, landerson@cornell.edu 1 - Chance-constrained Optimal Power Flow with Uncertain Reserves Johanna Mathieu, Assistant Professor, University of Michigan, 1301 Beal Ave, Ann Arbor, MI, 48109, United States of America, jlmath@umich.edu, Bowen Li, Siqian Shen, Yiling Zhang Electric loads can be controlled to help the power grid balance supply and demand, but the amount of reserves available from these resources is uncertain. We investigate optimization methods to dispatch power systems with uncertain reserves. Specifically, we formulate a chance-constrained optimal power flow problem and solve it using various scenario-based and analytical methods. We run experimental studies and compare the performance and computational complexity across the cases. 2 - Strategic Price Bidding in Electricity Markets with Only Renewables Josh Taylor, Assistant Professor, University of Toronto, 10 King’s College Rd., SF 1021C, Toronto, ON, M5S3G4, Canada, josh.taylor@utoronto.ca, Johanna Mathieu Renewables have low marginal-to-fixed costs ratios. In a power system with only renewables, the standard marginal-cost pricing mechanism would simply lead to all prices being equal to zero, which would be unsatisfactory. Motivated by other high-fixed, low-marginal cost industries like software and digital media, we analyze an extension of Bertrand-Edgeworth competition in which renewable producers with random capacities compete through a single, non-physical price to fulfill a random demand. 3 - Optimal Development of Wind Farm with Energy Storage in Micro-grid Community Qing Li, PhD Candidate, Rutgers University, 96 Frelinghuysen Road, CoRE Building, Room 201, Piscataway, NJ, 08854, United States of America, ql78@scarletmail.rutgers.edu, Honggang Wang Wind power has been widely used in micro-grids for local community energy consumptions. While it is clean, sustainable and low operational cost, wind power availability is highly fluctuant. A practical solution to maintain sufficiency is using energy storage. We develop computational models and optimization methods for optimal development and management of wind farm with energy storage. Two- stage optimization framework is proposed to seek and improve the optimal number and placement of turbines. 4 - Social Effects in the Diffusion of Solar Panels: A Dynamic Discrete Choice Approach Sebastian Souyris, PhD Candidate, The University of Texas at Austin, 2110 Speedway Stop B6500, Austin, TX, 78712, United States of America, sebastian.souyris@utexas.edu, Jason A. Duan, Anant Balakrishnan, Varun Rai We study the diffusion of residential solar panels by assuming looking forward households. We propose a dynamic discrete choice model, where the households estimate the return on investment and are influenced by previous spatio-temporal distributed adopters. We project the dynamics of the market; thereby, giving insights about where the developers should focus their customer acquisition efforts and what schedule of incentives would be more efficient to stimulate adoption. WC62 62-Room 112A, CC Distributed Energy Generation Cluster: Energy Systems: Design, Operation, Reliability and Maintenance Invited Session Chair: Alexandra Newman, Professor, Colorado School of Mines, Mechanical Engineering, Golden, CO, 80401, United States of America, anewman@mines.edu 1 - Optimizing A Renewable, Hybrid Distributed Energy Generation System Gavin Goodall, PhD Student, Colorado School of Mines, Golden, CO, 80401, United States of America, ggoodall@mymail.mines.edu

WC63 63-Room 112B, CC Operations Management V Contributed Session

Chair: Ahmed Ghoniem, Isenberg School of Management, UMass Amherst, 121 Presidents Dr., Amherst, MA, 01002, United States of America, aghoniem@isenberg.umass.edu 1 - Performance of Office-based Versus Home-based Call Center Agents: Evidence from Three Industries In Hyojeong Kim, University of Oregon, 2050 Goodpasture Pl, Heron Club Apartment 42, Eugene, OR, 97401, United States of America, hyojeongkim.oregon@gmail.com, Nagesh Murthy We examine the performance of call center agents that work from office vis-à-vis those that work from home. The home-based workers achieve significantly higher call productivity without any loss of call service quality. These differences are accentuated by task complexity and call routing clarity perceived by the agents. 2 - The Research on Modularization Order-picking Policy Based on Combination Forecasting

Shuiyin Zhou, Associate Professor, Huazhong University of Science and Technology, NO. 1037, Luoyu Road, Wuhan, 430074, China, abigale_lm@sina.com, Miao Li

Modularization order-picking policy was proposed to improve the response speed of orders and reduce the cost. The method of determining modules and the process of order-picking were described in detail and mathematic optimal model was established in the article, then algorithms were used to solve the problem. What is more, combination forecasting method was used to get the final module set. The results showed that the policy could improve the efficiency of order- picking effectively.

447