2016 INFORMS Annual Meeting Program

WC04

INFORMS Nashville – 2016

2 - Incremental Methods For Additive Convex Cost Optimization Mert Gurbuzbalaban, Postdoctoral Researcher, MIT, 176 Elm St #1, Building 32, Cambridge, MA, 02140, United States, mert.gurbuzbalaban@gmail.com, Asuman Ozdaglar, Pablo Parrilo Motivated by machine learning problems over large data sets and distributed optimization over networks, we consider the problem of minimizing the sum of a large number of convex functions. We develop and study incremental methods for solving such problems, in particular for the random reshuffling method we provide a sharp convergence result that answers an open question. 3 - Virtual Casted Supply Chain For Information Sharing Mahamaya Mohanty, Research Scholar, IITDelhi, Shaheed Jeet Singh Marg, New Delhi, 110016, India, mahamayamohanty@gmail.com, Ravi Shankar Cloud computing creates a multiplier effect in IT, supply in service chain management with an intersection of virtualization and cloud where both fit together. The cloud is a virtualization of resources that maintains and manages itself as well as plays a vital role in making the overall system cost-effective, enhanced flexibility, and sharing information with availability of resources thus improving agility and enhancing flexibility. This article focuses on designing a virtualized environment that is used to address a variety of business goals aimed at improving efficiency and reducing costs of operation and maintenance of physical servers. WC04 101D-MCC Power System Operation Models for Ramping Scarcity Mitigation Sponsored: Energy, Natural Res & the Environment, Energy I Electricity Sponsored Session Chair: Masood Parvania, University of Utah, 50 S. Central Campus Drive, Salt Lake City, UT, 84112, United States, masood.parvania@utah.edu 1 - Ramping Deliverability Enhancement Through Flexible Transmission Mostafa Ardakani-Sahraei, University of Utah, Salt Lake City, UT, United States, mostafa.ardakani@utah.edu Proxy reserve constraints are employed within electricity market models in an attempt to attain reliability in the face of uncertain load and element failures. However, due to the complexities of the transmission network, the available reserve, and specifically ramping capabilities, may not be deliverable to the desired location. This talk discusses how flexibilities of the transmission network can be exploited to enhance ramping deliverability. The results confirm the effectiveness of the proposed method in improving reliability and reducing reliability costs. 2 - Explicit And Implicit Mechanisms For Ensuring Reserve And Ramping Capability Erik Ela, EPRI, eela@epri.com In this presentation, we will present the central needs for operating reserve which are used to meet variability and uncertainty. We compare the performance of explicitly scheduled reserve, which is done through reserve inequality constraints to meet the associated impact, with the implicitly scheduled operating reserve, that in which the reserve is scheduled inherently by advanced scheduling applications. We review case studies to compare performance in terms of efficiently procuring sufficient capacity and ramp capability. 3 - Definition And Valuation Of Continuous-time Ramping Trajectory In Power Systems Operation Masood Parvania, University of Utah, masood.parvania@utah.edu The current discrete-time power system operation models imply that generating units shall follow piecewise constant generation trajectories. This means that the units’ ramping is modeled as the finite difference between the consecutive generation samples. The discrete-time generation schedules and the resulting rampings do not fully utilize the units’ flexibility to compensate the faster variations of net-load, which may lead to ramping scarcity events. In this presentation, we introduce a novel unit commitment model that schedules for continuous-time generation and ramping trajectories, opening the door for continuous-time valuation of ramping trajectories in power system operation.

4 - Wind Ramping Product For Power System Ramping Scarcity Mitigation Venkat Krishnan, NREL, Venkat.Krishnan@nrel.gov Golden, CO, 80401, United States, Venkat.Krishnan@nrel.gov, Bri-Mathias Hodge, Anthony Florita This talk will investigate the potential of wind power to provide ramping service and the importance of ramp event forecasting. Forecasting mid-term (day-ahead and intra-day) and short-term wind ramp events efficiently will be the basis of managing and dispatching wind in a co-optimized energy and ramp service markets. There are two aspects to this: 1) efficient wind forecasting platforms- developed using big-data information processing technologies; and 2) wind ramp event forecasting algorithm- based on optimized swinging door algorithm (OpSDA) and dynamic programming. WC05 101E-MCC Spatial optimization Sponsored: Energy, Natural Res & the Environment II Forestry Sponsored Session Chair: Nahid Jafari, University of Florida, Gainesville, FL, United States, jnahid@hotmail.com 1 - Fine-scale Spatial Targeting Of Surveillance To Minimize Costs Of Invasive Species Introduction Across Large Landscapes Rebecca Epanchin-Niell, Resources for the Future, Epanchin-Niell@rff.org Early detection of new invasive species populations can reduce costs and damages by allowing control when populations are smaller and less costly. This talk presents a bioeconomic modeling approach to optimally target invasive species surveillance at fine spatial scales (1 km2) to minimize total costs from invasions and surveillance. The model accounts for spatial-temporal interdependencies arising from invasion spread and surveillance costs. We apply the model to surveillance for gypsy moth in the northwestern US. 2 - Analyzing Trade-offs Between Fire Prevention And Suppression In The Republic Of Korea Yohan Lee, Yeungnam University, yohanlee76@gmail.com This study explores the spatial tradeoff between the number of initial attack firefighting resources and the level of fire prevention efforts mitigating the probability of human-made fires in the Republic of Korea. To examine the spatial trade-off, we utilize a hybrid system that combines a scenario-based, standard- response optimization model with a stochastic simulation model. A mixed policy that includes fire suppression and fire prevention efforts works better than a single dominant policy such as a strong fire suppression policy, in particular, with the consideration of spatial allocations because returns to effort in fire prevention policy is dependent on the location of fires. 3 - Spatial Control Of The Argentine Black And White Tegu. An Approach Using Linear Programming Julien Martin, United States Geological Survey, 7920 NW 71 Street, Gainesville, FL, 32653, United States, julienmartin@usgs.gov, Mathieu Bonneau, Fred A. Johnson, Brian Smith, Christina M. Romagosa We propose to frame spatial control of tegu in south Florida as a linear programming optimization problem. This formulation with a discrete reaction- diffusion model permits calculation of an optimal control strategy that minimizes the remaining number of tegus for a fixed cost or that minimizes the control cost to achieve containment. We compute the optimal strategy for a range of possible model parameters and discuss the best strategy to use in practice as a function of the risk attitude of the decision maker. 4 - Robust Spatial Optimization For The Invasive Species Management Nahid Jafari, University of Florida, nahid.jafari@ufl.edu The problem of invasive species management concerns modeling the pattern of spread of the invasive, estimation of control costs, spatial design of the control effort, and accounting for uncertainties in model parameters. Robust optimization constructs a solution that is feasible for any realization of the uncertainty in a given uncertainty set (achieves the best worst-case objective function value). Given the computational efficiency of robust optimization, we are developing a spatial-optimization model to select sites for efficiently controlling invasive species to minimize their ecological damage, as well as to minimize the costs given limited financial resources.

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