2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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MC58
Music Row 6- Omni
Energy VII
Contributed Session
Chair: Par Holmberg, Associate Professor, Research Insitute of Industrial
Economics (IFN), Grevgatan 34, Stockholm, SE10215, Sweden,
1 - Electricity Resource Capacity Expansion With Distributed Energy
Resources: A New MILP Formulation
Jesse D Jenkins, PhD Candidate, Massachusetts Institute of
Technology, Cambridge, MA, 02139, United States,
Conventional electricity capacity expansion models do not properly consider
distributed energy resources (DERs), including distributed generation, storage and
demand response. DERs provide locational benefits—e.g. loss mitigation,
congestion relief, network capacity deferral—which must be considered along
with the costs of different unit scales. In this new MILP formulation, conventional
generation and DER investments are made across several transmission zones and
distribution voltage levels subject to power flow constraints, network
reinforcement costs, losses, and operational constraints capturing reserves, ramp
rates, and unit commitment constraints for thermal generators.
2 - Price Projections For Ancillary Services Markets Under
Hypothetical Future Scenarios
Todd Levin, Energy Systems Engineer, Argonne National
Laboratory, 9700 S. Cass Ave, Bldg 362, Lemont, IL, 60439,
United States, , Zhi Zhou
We forecast broad future ancillary service price trends in U.S. power markets by
first identifying a set of key parameters that influence prices. Baseline models are
then developed and calibrated based on historical data and current regional
characteristics. We then utilize AURORAxmp to model hourly dispatch in each
region and forecast the impact of changes in these inputs, such as electricity
demand, fuel prices, renewable penetration levels, and availability of AS supply.
Finally, we identify correlations to broadly project price trends under hypothetical
future scenarios, e.g. increased wind penetration, decreased natural gas prices,
and increased supply of flexible generation resources.
3 - An Efficient Integer L-shaped Method For A Two-stage
Self-healing Power Grid Problem
Amir Golshani, PhD Candidate, University of Central Florida,
Orlando, FL, United States,
Wei Sun, Qipeng Zheng
When a power system enters an emergency state, the self-healing process is
initiated by system operators to bring the system back to its normal condition.
This presentation proposes a two-stage self-healing optimization problem with a
set of practical constraints containing integer variables in both stages. To solve the
proposed problem, the integer L-shaped algorithm together with an efficient
optimality cut based on the physical characteristics of power system will be
presented. Standard IEEE test system is used to demonstrate the effectiveness of
the proposed algorithm and optimality cut.
4 - Toward Cost-efficient And Reliable Unit Commitment
Under Uncertainty
Hrvoje Pandzic, Faculty of Electrical Engineering and Computing
University of Zagreb, Unska 3, Zagreb, 10000, Croatia,
, Yury Dvorkin, Ting Qiu, Yishen Wang,
Daniel Kirschen
This presentation will describe a new improved interval unit commitment
formulation that combines some aspects of stochastic and interval formulations.
A systematic and rigorous assessment of the cost and reliability performance of
the improved interval, interval, stochastic and robust unit commitment will be
demonstrated as well.
5 - Price Instability In Multi-unit Auctions
Par Holmberg, Associate Professor, Research Insitute of Industrial
Economics (IFN), Grevgatan 34, Stockholm, SE10215, Sweden,
Edward James Anderson
We consider a uniform-price procurement auction with indivisible units and
private costs. We solve for a Bayesian Nash equilibrium and show that the
equilibrium has a price instability in the sense that a minor change in a supplier’s
realized cost can result in a drastic change in the market price. The price
instability is reduced as the size of indivisible units decreases for a given total
production capacity. In the limit, where the size of units approaches zero and
costs are almost surely common knowledge, the Bayesian equilibrium converges
to a pure-strategy NE without price instability, the Supply Function Equilibrium
(SFE).
MC59
Cumberland 1- Omni
Freight Network Design
General Session
Chair: James F Campbell, University of Missouri-St Louis, Saint Louis,
MO, TBD, United States,
1 - Strategic Design For Delivery With Drones And Trucks
James F Campbell, University of Missouri-St Louis, St. Louis, MO,
United States, , Donald C. Sweeney II,
Juan Zhang
Our research develops continuous approximation models for the strategic design
of drone and hybrid truck-drone delivery systems. We consider aerial and
ground-based drones that can be launched from fixed or relocatable facilities, or
from trucks. In contrast to discrete VRP-based optimization models, we treat the
demand for deliveries as a continuous spatial density over a region. Analytical
results and illustrations assess the economic and service performance from using
the best mix of drones and trucks, and provide strategic managerial insights.
Results show how using drones in conjunction with trucks alters the optimal
delivery strategy and can facilitate lower cost and faster deliveries.
2 - A Quantitative Model For Truck Parking And Hours Of
Service Regulations
Sarah G Nurre, University of Arkansas, 425 W. Louise Street,
Fayetteville, AR, 72701, United States,
Truck parking and hours-of-service (HOS) regulations are consistently reported as
two of the top concerns in the trucking industry. Parking shortages are a function
of inadequate capacity and changes to HOS regulations requiring drivers to stop
frequently and for longer periods. We develop a network-based optimization
model which determines the best times and locations for stopping along a set of
truck routes while adhering to system-wide HOS regulations, network, and
scheduling constraints. We present the results and insights deduced from
experiments run using historical truck route data.
MC60
Cumberland 2- Omni
Methodological Advances and Empirical Discoveries
in Travel and Activity Choice Modeling
Sponsored: TSL, Urban Transportation
Sponsored Session
Chair: Sayeeda B. Ayaz, UMass Amherst, UMass Amherst, Amherst,
MA, 01003, United States,
1 - Bike Route Choice Modeling Without Choice Sets Of Paths:
Estimation, Prediction And Accessibility Measure
Maelle Zimmermann, Université de Montreal,
We estimate a link-based bike route choice model in a real network which does
not require to sample any choice set of paths, similar to the recursive logit (RL)
model formulated by Fosgerau (2013). We provide numerical estimation results,
and we show the advantages of this approach in the context of prediction by
focusing on two applications of the model: i) simulation of bike traffic flows; ii)
measuring bike accessibility. Compared to the path-based approach which
requires to generate choice sets, the RL model proves to make significant gains in
computational time and to avoid paradoxical results discussed in previous works,
e.g. in Nassir (2014).
2 - A Random Utility Based Estimation Framework For The
Household Activity Pattern Problem
Zhiheng Xu, University at Buffalo, Buffalo, NY, United States,
, Jee Eun Kang, Roger Chen
We develop an estimation framework for the Household Activity Pattern Problem
(HAPP) based on random utility theory. The estimation procedure is based on the
realization that travelers’ complex activity-travel pattern decisions form a
continuous path in space-time. The proposed framework is comprised of choice
set generation, choice set individualization, and multinomial logit estimation
procedures.
3 - Looking-ahead Route Choice Behavior Based On Driving
Simulator And Pc-based Experiments
Sayeeda B. Ayaz, University of Massachusetts Amherst, Marston
139, 130 Natural Resources Rd, Amherst, MA, 01003, United
States, , Hengliang Tian, Song Gao,
Donald Fisher
We study drivers’ route choice behavior with real-time traffic information based
on driving simulator and PC-based experiments. A looking-ahead route choice
refers to a decision taking into account future diversion possibilities at
downstream nodes based on real-time information not yet available at the time of
MC58