2016 INFORMS Annual Meeting Program

MB11

INFORMS Nashville – 2016

4 - Demand Response Resource Quantification With Detailed Building Energy Models Elaine Thompson Hale, Senior Engineer, National Renewable Energy Laboratory, Golden, CO, United States, elaine.hale@nrel.gov, Henry Horsey, Noel Merket, Brady Stoll, Ambarish Nag Demand response is a broad suite of technologies that enables operational changes in electrical load in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult— we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable. MB10 103C-MCC Energy Models: Diversity and Complementarity Sponsored: Energy, Natural Res & the Environment, Energy II Other Sponsored Session Chair: Denis Lavigne, Royal Military College St-Jean, St-Jean-sur-Richelie, QC, Canada, denis.lavigne@cmrsj-rmcsj.ca 1 - OSeMOSYS And LEAP Energy Modeling Using an Extended UTOPIA Model Denis Lavigne, Professor, Royal Military College St-Jean, C.P. 100, succ. Bureau-chef, Richelain, QC, J0J 1R0, Canada, denis.lavigne@cmrsj-rmcsj.ca Energy Models have been used extensively for decades. Leaders and decision makers need to have a basic understanding of such tools to gain insight on the existing (and future) energy systems and their different components. OSeMOSYS (optimization) and LEAP (simulation) offer a package with a smooth learning curve, allowing non-experts and low-budget organizations the possibility to use powerful yet simple software to make coherent analyses. An extended version of OSeMOSYS’ UTOPIA model will be presented as a study example that can easily be performed and a link with LEAP will be proposed. 2 - Complementarity Modeling Of Electricity And Renewable Energy Credit Markets To Inform Effective Renewable Energy Policy Formation Kristen R. Schell, Postdoctoral Fellow, University of Michigan, Ann Arbor, MI, United States, krschell@umich.edu Joao Claro, Manuel Loureiro To date, 84% of the world’s countries have instituted a renewable energy target, or Renewable Portfolio Standard (RPS). Despite this global prevalence, policy design and target implementation varies widely. This study combines complementarity modeling of the electricity and renewable energy credit markets with generation expansion planning to meet an RPS, to assess the impacts different RPS policy designs have on social welfare, renewable energy investment, electricity prices and greenhouse gas emissions. The policy recommendations move toward optimal policy design to minimize externalities. 3 - The Application Of Promethee With Prospect Theory - opportunities And Challenges The Application Of Promethee With Prospect Theory In The Context Of Energy Sector Management Jutta Geldermann, Prof. Dr., Georg-August-University Goettingen, Platz der Goettinger Sieben 2, Goettingen, 37073, Germany, jgelder@gwdg.de, Katharina Stahlecker, Nils Lerche The incorporation of elements from Prospect Theory into PROMETHEE enables the decision maker to integrate reference dependency as well as to express loss aversion. To illustrate occurring opportunities and challenges of the developed approach, the results of an application concerning the identification of a sustainable bioenergy concept as well as the feedback from decision makers are presented. Additionally, potential approaches concerning a corresponding sensitivity analysis and the consideration of risk or uncertainty are discussed. Furthermore, the applicability of the developed approach for long-term decision support in energy systems analysis will be discussed.

4 - Multi-stage Investment Decisions In Renewable Generating Capacity: Comparison Of Different Approaches Maria Ruth Dominguez Martin, PhD, University of Castilla - La Mancha, Avenida Carlos III, s/n, Toledo, 45071, Spain, Ruth.Dominguez@uclm.es, Miguel Carrion, Antonio J. Conejo Renewable generating capacity needs to be significantly increased in power systems if the effects of global warming are to be mitigated. Moreover, due to the high uncertainty involved in long-term planning exercises, investment decisions are usually made in several stages as uncertainty unfolds over time. In this work we propose a multi-stage stochastic-programming investment model in renewable generating capacity, and apply different approaches to solve it. Specifically, we solve the proposed problem using stochastic programming under both multi-stage and rolling window frameworks, and linear decision rules, and compare the results with the deterministic approach. MB11 104A-MCC Network Optimization Models and Applications II Sponsored: Optimization, Network Optimization Sponsored Session Chair: Jose Luis Walteros, University at Buffalo, SUNY, 413 Bell Hall, Buffalo, NY, 14213, United States, josewalt@buffalo.edu 1 - Integer Programming Models For Bipartitioning A Graph Enforcing Structure Constraints Chrysafis Vogiatzis, North Dakota State University, chrysafis.vogiatzis@ndsu.edu In this talk, we consider the problem of partitioning a graph into two distinct subgraphs, where one of the subgraphs satisfies a structural property. In literature, it is common to bipartition a graph using a normalized cut criterion; this well-studied problem leads to the creation of two similarly weighted subgraphs. There exist cases though, when one of the partitions needs to possess a certain structure or “motif”. We investigate some structures, and propose ways to formulate and solve the problem. Computational results are also presented. 2 - Computing The Maximum Lifetime Flow Of A Network With Short Node Lifetimes Hugh Medal, Mississippi State University, hugh.medal@msstate.edu We study an extension of the maximum flow problem in which nodes have a limited amount of energy available and energy is consumed when the node sends or receives flow. The objective is to maximize the total s-t flow over the lifetime of the network, i.e., until node energy depletions result in a cutset. We present a polynomial-time algorithm as well as computational results. 3 - A Stochastic Programming Approach For Selecting Inland Waterway Maintenance Projects Khatereh Ahadi, University of Arkansas, Fayetteville, AR, United States, kahadi@uark.edu, Kelly Sullivan We consider the problem of selecting a budget-limited subset of maintenance actions to maximize the expected tonnage of commodities that can be transported through the system. Our model incorporates uncertainty due to shoaling and unpredictable water conditions. Due to the maritime transportation network’s size, along with the variety of commodities transported via waterway, the maintenance project selection problem is large and complex, and small gains in efficiency can have a significant economic impact. We model this problem as a stochastic programming model, develop solution approaches, and analyze computational results. 4 - Convoy Formation Process Azar Sadeghnejad Barkousaraie, University at Buffalo (SUNY), Buffalo, NY, United States, azarsade@buffalo.edu, Rajan Batta, Moises Sudit A motor convoy may consist of hundreds of vehicles organized together for the purpose of control and secure movement. Besides specific constraints of convoy routing, length of a convoy, as a single transportation unit, shall not be neglected, which differentiates it from other transportation problems. Convoy formation process addresses an essential decision on how to constitute convoys and plan their movements on limited number of routes. The purpose of this research is to show the effect of convoy length on its movement and how it can be manipulated to better satisfy specific constraints of convoy movement problem.

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