2015 Informs Annual Meeting

MC57

INFORMS Philadelphia – 2015

2 - A Maximal Conditional Covering Location Problem to Relocate Emergency Response Enterprise Units Brian Lunday, Assistant Professor Of Operations Research, Department of Operational Sciences, Grad. Sch. of Engr. & Mgmt., Air Force Institute of Technology, Wright Patterson AFB, OH, 45433, United States of America, Brian.Lunday@afit.edu, Nicholas Paul, Sarah Nurre We analyze the collective effectiveness of three hierarchical tiers within an existing enterprise of Department of Defense units designated to respond to a large-scale emergency (e.g., a chemical, biological, or radiological attack), and we identify their optimal locations via a maximal conditional covering problem formulation with side constraints. Acknowledging fiscal and political restrictions on facility relocations, we apply a multiobjective approach to identify Pareto optimal solutions. 3 - Location of Milk Collection Points for the Blended Milk Collection Problem Vladimir Marianov, Pontificia Universidad Catolica de Chile, Vicuña Mackenna 4860, Macul, Santiago, Chile, marianov@ing.puc.cl, Armin Löer Villagra, Germán Paredes - Belmar, Andrés Bronfman Different qualities of milk are collected from farms, using a heterogeneous truck fleet. Each farm produces single quality milk. Milk can be blended in the trucks, if convenient. The blend takes the quality of its lower quality component. Collection points are located for farthest farms to bring their milk. Trucks visit some of the farms and the collection points. A model is presented and solved using Branch and Cut for small instances. A heuristic is presented to solve a real problem. 4 - Sensor Location Problems: Open Locating-dominating Sets Robin Givens, College of William & Mary, Computer Science Department, McGlothlin 126, Williamsburg, VA, 23185, United States of America, rmgivens@cs.wm.edu, Gexin Yu, Rex Kincaid We consider the problem of fault location via sensors in parallel and multiprocessor networks with the goal of minimizing the number of sensors required throughout the system. We prove the lower bound of the minimum open locating-dominating set size for two different circulant graphs using two proof techniques, the discharging method and Hall’s Theorem. We also provide constructions for the upper bound at the same size. MC57 57-Room 109B, CC Policy Issues in Energy Markets Sponsor: ENRE – Energy II – Other (e.g., Policy, Natural Gas, Climate Change) Sponsored Session Chair: Andrew Liu, Assistant Professor, Purdue University, 315 N. Grant Street, West Lafayette, IN, 47907, United States of America, andrewliu@purdue.edu 1 - Environmental and Economic Performance of Stochastic Market Clearing under High Wind Penetration Ali Daraeepour, PhD Student, Duke University, Box 90328, Duke Using a scaled version of PJM, and generated wind scenarios and demand data from BPA data, this paper explores a comparison of the performance between stochastic and deterministic models for market clearing in terms of total operational costs, wind curtailment, and air emissions. Operating reserves in the deterministic-day-ahead model and Value of Lost Load in the Stochastic-day- ahead model are chosen so that both result in commitments that have the same expected reliability. 2 - Risk and Return under Renewable Support Mechanisms – Towards a Coherent Framework Christoph Weber, Prof., University Duisburg-Essen, Universitaetsstr. 11, Essen, 45117, Germany, Christoph.weber@uni-duisburg-essen.de, Lena Kitzing Risk exposure resulting from renewable support mechanisms such as feed-in tariffs impacts the incentives for investors. We consider multi-stage decision making, including regulatory settings, financing and investment decisions and operations. Both systematic and unsystematic risks are included in a stochastic cash flow approach. The model is applied to a wind park in Germany. Feed-in- tariffs are found to require lower support levels than other support schemes but transfer more risk to society. University, Durham, NC, 27707, United States of America, a.daraeepour@duke.edu, Xin Li, Dalia Patino-Echeverri

3 - A Natural Gas Model for North America: Impact of Cross-border Flows of Natural Gas with Mexico. Felipe Feijoo, Postdoctoral Fellow, Johns Hopkins University Whiting School of Engineering, 3400 N Charles St, Baltimore,

MD, 21218, United States of America, ffeijoo@jhu.edu, Sauleh Siddiqui, Daniel Huppmann, Larissa Sakiyama

Natural gas is becoming an important energy source due to its low environmental impact and price. New regulations in Mexico and Canada will highly affect the North American natural gas market. We present a long-term dynamic partial- equilibrium model that incorporates a range of regulatory measures to study impacts of various policies, assess the costs and benefits from cross-border flows of natural gas and electricity, and quantify the emissions avoided in Mexico through a switch to natural gas. MC58 58-Room 110A, CC Analytics in the Petrochemical and Petroleum Industries III Sponsor: ENRE – Natural Resources II – Petrochemicals and Petroleum Sponsored Session Chair: Bora Tarhan, Research Specialist, ExxonMobil, 22777 Springwoods Village Parkway, Spring, TX, 77389, United States of America, bora.tarhan@exxonmobil.com 1 - Convex Relaxations for Calculating Voltage Stability Margins and Certifying Power Flow Insolvablity Daniel Molzahn, Dow Postdoctoral Fellow, University of Michigan, 1301 Beal Avenue, Room 4234A, Ann Arbor, MI, 48109, United States of America, dan.molzahn@gmail.com, Ian Hiskens, Bernard Lesieutre, Christopher Demarco Ensuring the reliability of electric power systems requires operating with sufficient stability margins. We present a non-convex optimization problem which provides a voltage stability margin. Convex relaxations of this problem upper bound the voltage stability margin and can certify insolvability of the network power flow equations. These relaxations have SOCP and SDP formulations and may include integer constraints to model reactive-power-limited generators. 2 - Inventory and Maintenance Optimization in Oil and Gas Production System Farnaz Ghazi Nezami, Assistant Professor, Kettering University, 1700 University Ave, Flint, MI, 48504, United States of America, fghazinezami@kettering.edu, Prasanna Tamilselvan This research is aiming at developing an optimal spare provisioning policy for an offshore oil and gas production facility to jointly optimize the production system availability and maintenance cost. The proposed policy minimizes the downtime which is a function of subsea intervention equipment lead time and spare parts availability. 3 - Oil Supply Chain Risk Identification in Saudi Arabia Julio Daza, Universidad de Valencia, valencia, Valencia, Spain, julio.daza@uv.es, Mario Ferrer, Ricardo Santa, Alvaro Sierra, Daniel Romero-Rodriguez This investigation has a twofold purpose: to operationalize the constructs of the of Supply-Chain-Risk-Management (SCRM), Supply-Chain-Resilience (SCR) and Supply-Chain-Vulnerability (SCV), and to quantitatively test the nature as well as the strength of the relationship between these three constructs within the context of the oil-industry in the Kingdom of Saudi Arabia.

224