2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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4 - Demand Response Resource Quantification With Detailed
Building Energy Models
Elaine Thompson Hale, Senior Engineer, National Renewable
Energy Laboratory, Golden, CO, United States,
, 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,
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,
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,
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,
, 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,
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,
1 - Integer Programming Models For Bipartitioning A Graph Enforcing
Structure Constraints
Chrysafis Vogiatzis, North Dakota State University,
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,
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, , 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, , 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.
MB11