Informs Annual Meeting 2017

TA79

INFORMS Houston – 2017

2 - Understanding the Decision Making in a Long-term Electric Power Sector Capacity Expansion Models Kelly Eurek, National Renewable Energy Laboratory, Golden, CO, United States, Kelly.Eurek@nrel.gov Long-term capacity expansion model are used for exploring the potential evolution of the electric power sector. Often formulated using linear and mixed integer optimization, these models choose the mix of technologies that minimize the cost to reliability balance supply and demand of electricity. This presentation highlights a method for understanding the decision making in NREL’s Regional Energy Deployment System (ReEDS) capacity expansion model. 3 - Stochastic Transmission Expansion Planning: Computational Challenges Mohammad Majidi-Qadikolai, The University of Texas at Austin, 1616 Guadalupe UTA 2.304, Austin, TX, 78701, United States, majidi_mohammad@yahoo.com, Ross Baldick Increasing uncertainties in future generation generation mix, output of high penetration intermittent resources, contribution of demand response and energy storage capacity significantly increase complexities of transmission expansion planning (TEP), and traditional experienced based methods may not be efficient anymore. Stochastic programming can be used to model and integrate these uncertainties into TEP decision making process. Being computationally expensive is the main drawback of this method. In this work we proposed a generalized decomposition framework that allows us to solve a two-stage stochastic TEP problem with security constraints for real-size problems. 4 - Using Multihorizon Stochastic Programming to Analyze the Potential Trade-off Between Demand Response and Transmission Asgeir Tomasgard, Norwegian University of Science and Technology, Dept. of industrial economics, Alfred getz vei 3, Trondheim, 7491, Norway, asgeir.tomasgard@iot.ntnu.no, Christian Skar, Hector Maranon-Ledesma The objective of this work is to analyse to what demand response (DR) can contribute to the transition to an European low emission power system. The capabilities of DR are studied through the multi horizon stochastic programming model EMPIRE, an electricity sector model with a time span of 30 years and hourly market clearing. The model includes uncertainty at the operational level and energy economics dynamics at a strategic level. The investment-operation DR module models several classes of shiftable and curtailable loads in residential, commercial, industrial and transport sectors for 31 European countries. 380B Design Engineering Contributed Session Chair: Rhythm Wadhwa, NTNU, Gjoevik, Norway, rhythmwadhwa@hotmail.com 1 - Finding Patterns in Pareto Optimal Solutions and its Applications Abhinav Gaur, Doctoral Candidate, Michigan State University, 428 S Shaw Lane, East Lansing, MI, 48824, United States, gaurabhi@msu.edu, Kalyanmoy Deb Multi-objective optimization (MOO) problems lend themselves to not one but a set of optimal solutions also called Pareto-optimal (PO) solutions. Such P.O. solutions carry information on patterns that make these solutions concurrently optimal for multiple objectives. Discovering such patterns from the P.O. solutions is called `Innovization’ or innovation through optimization. Some of the uses of carrying out an Innovization exercize are discovering design principles for the MOO design problem, automatically discovering optimization heuristics for a problem and, expediting black box MOO algorithms. 2 - Redundancy Allocation of Standby Components in Repairable K-out-of-N Systems In system design process, standby redundancy is a widely-used technique to improve system reliability and availability. In this paper, we investigate the repairable K-out-of-N system with both warm and cold standby redundancy. In the proposed system, each component can be in failure, cold, warm and active states and the components are assumed to be repairable. The systems are modeled by continuous time Markov chain (CTMC) and the system long run availability is derived. Furthermore, optimal number of warm standby is studied by considering system availability and average long run cost. Illustrative examples are also given to show the applications of the proposed model. Hanlin Liu, City University of Hong Kong, Hong Kong, hanlinliu2-c@my.cityu.edu.hk, Rui Peng, Min Xie TA78B

3 - An Incentive Mechanism to Improve Engineering Design Process under Requirement Based Engineering Design Soodabeh Yazdani, PhD Student, George Mason University,

4400 University Dr, Fairfax, VA, 22030, United States, syazdan2@masonlive.gmu.edu, Edward Huang, Daniel Lin

Large-scale complex engineering systems are mostly carried out by requirement based engineering design where project manager at higher levels flow-down requirements and design resources to design teams at lower levels. Under this scheme, incentive alignment and efficient resource allocation are crucial factors in the success of design outcome. This paper explores economics incentives to control and improve the system-level design outcome. A mathematical framework by using mechanism design theory is proposed to analyze the effect of incentives on system wide design outcome. 4 - Determining Decoupling Points in a Network Associated with Different Design Preferences using Exploration of the Solution Space Lin Guo, Graduate Research Assistant, University of Oklahoma, 202 W. Boyd Street, Room 218, Norman, OK, 73019, United States, lin.guo@ou.edu, Reza Alizadeh, Janet Katherine Allen, Farrokh Mistree In this paper, we propose an approach using exploration of the solution space of a multi-goal compromise Decision Support Problems model to determine the decoupling points of a three-echelon supply chain. Facing different design preferences of the supply chain, the goals should be satisfied in different degree, and the change of the design preference may take place rapidly, which requires the decoupling points flexible enough to be moved through the supply chain. 5 - Axiomatic Design in Early Product Design a Case of Outdoor Sports Equipment 381B JOINT ENRE/Petro/OR Oil: Logistics and Supply Chain Optimization in Petrochemical/Petroleum Industry Sponsored: Energy, Natural Res & the Environment, Natural Resources Petrochemicals Sponsored Session Chair: Arul Sundaramoorthy, BP, BP, Naperville, IL, 60563, United States, arul.sundaramoorthy@bp.com 1 - Batch Scheduling of Multi-Product Pipeline Networks Sander J. Vlot, ORTEC, Zoetermeer, Netherlands, Sander.Vlot@ortec.com In this research, we propose a novel method for scheduling pipeline networks. The method consists of a planning and a scheduling phase that are coupled in a hierarchical decomposition scheme. In the planning phase, global transportation volumes are determined for each pipeline. In the scheduling phase, we use the planning output to generate complete schedules. Both phases are based on discrete-time MILP formulations. The method is successfully tested on two case studies involving up to 4 products, 8 pipelines, 8 tank farms, 2 supply locations, and 5 demand locations. The proposed method is flexible in terms of network configurations, supply and demand requirements, and cost structures. 2 - A Mixed-complementarity Approach to Assess the Potential Gain from Intra-regional Electricity Transmission Utilizing the GCC Interconnector David Wogan, Research Associate, King Abdullah Petroleum Studies and Research Center, P.O. Box 88550, Riyadh, 11672, Saudi Arabia, david.wogan@kapsarc.org The GCC Interconnector links the electricity systems of the six countries of the Gulf Cooperation Council. Potential economic and technical gains could be real- ized by utilizing the Interconnector to deliver electricity from lower-cost sources across the region. We formulate a bottom-up mixed-complementarity problem to capture market distortions that arise from subsidized fuel prices for power and water producers. We assess the impact on volume of transmission and marginal costs of supply and demand by considering electricity production for domestic consumption at administered prices and for export to the Interconnector at prices reflecting fuel opportunity costs. Rhythm Wadhwa, Professor, NTNU, Teknologiveien 22, Gjoevik, 2821, Norway, rhythmwadhwa@hotmail.com The paper presents the application of Axiomatic design for the early product development of outdoor sporting equipment. The design parameters were used to decouple the functional and customer requirements. The product developed after multiple iterations and was field tested. The results of the simulation and field trials have been compared and discussed. TA79

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