Informs 2015

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INFORMS Philadelphia – 2015
338
TC57
57-Room 109B, CC
Long-Term Electric Power System Planning Models
Sponsor: ENRE – Energy I – Electricity
Sponsored Session
Chair: Ramteen Sioshansi, Associate Professor, The Ohio State
University, Integrated Systems Engineering, 1971 Neil Avenue,
Columbus, OH, 43210, United States of America,
1 - Optimizing Storage Operations in Longer-term Power
System Models
Sonja Wogrin, Comillas Pontifical University, Calle Alberto
Aguilera 23, Madrid, Spain,
David Galbally, Javier Reneses
In a rapidly changing power system the proper characterization of storage
behavior becomes an increasingly important issue. We propose a new formulation
to capture storage behavior in medium- and long-term power system models that
use a load duration curve. In such models the chronology among individual hours
is lost; our approach addresses related shortcomings and is able to accurately
replicate hourly evolution of storage levels while keeping computational time
tractable.
2 - Multi-stage Investment in Renewable Energies via Linear
Decision Rules
Maria Ruth Dominguez Martin, Universidad de Castilla -
La Mancha, Av. Carlos III, s/n, Toledo, Spain,
Miguel Carrion, Antonio Conejo
Investment in generating capacity involves high uncertainty. In the real world,
these decisions are usually made in several stages. We propose a multi-stage
investment model to transform a thermal-based power system into a renewable-
dominated one. We consider the uncertainty of the demand growth and the
investment costs, as well as the variability of the renewable power production
throughout the year.
3 - Impact of Unit Commitment Constraints on Generation Expansion
Decisions under Wind Uncertainty
Jalal Kazempour, Technical University of Denmark, Department
of Electrical Engineering, Kgs. Lyngby, 2800, Denmark,
, Amin Nasri, Antonio Conejo
Most of available generation expansion decision-making tools in the literature
neglect a number of unit commitment (UC) constraints, e.g., on/off commitment
status, ramping limits and minimum production level of thermal units. This study
analyzes the impact of those constraints on generation expansion decisions in
power systems with significant wind power integration. To this end, a two-stage
stochastic programming problem is proposed and solved using a decomposition
technique.
4 - Stochastic Generation and Transmission Investment
Planning Model
Yixian Liu, The Ohio State University, 210 Baker Systems Bldg.,
1971 Neil Ave., Columbus, OH, 43210, United States of America,
Ramteen Sioshansi
Increasing electricity demand makes it necessary to expand the capacity of the
current electrical grid. We propose a multi-stage stochastic linear programming
model to seek an optimal investment plan in generators, storage devices and
transmission lines in a long time horizon. Multiple uncertainties are considered
involving both investment and dispatch decisions. The model is large in scale and
may take excessive computational time to be solved. Decomposition methods will
be applied to solve it.
TC58
58-Room 110A, CC
Electricity and System Resilience
Sponsor: ENRE – Energy I – Electricity
Sponsored Session
Chair: Valerie Thomas, Professor, Georgia Institute of Technology,
755 Ferst Drive, NW, Atlanta, GA, United States of America,
1 - Stochastic Model for Assessment of Thermoelectric Power
Generation Drought Risk under Climate Change
Royce Francis, George Washington University, 800 22nd St. NW
B1850, Washington, DC, 21212, United States of America,
Behailu Bekera
The objective of this article is to propose a stochastic method for analyzing
drought risk to the thermoelectric power generation infrastructure sector due to
its heavy reliance on freshwater availability. In particular, this article proposes a
thermoelectric drought characterization framework from which a stochastic
drought risk assessment model is constructed from the thermoelectric power
sector’s operational perspective.
2 - Portfolio Approach for Optimal Rooftop Solar Arrays Selection for
Distributed Generation
Olufemi Omitaomu, Senior Research Scientist, Oak Ridge
National Laboratory, 1 Bethel Valley Road, MS-6017, Oak Ridge,
TN, 37831, United States of America,
Xueping Li
We present a portfolio selection approach that consider thousands of buildings
with different solar energy potential and that are being considered for utility-scale
distributed power generation. Our approach uses Markowitz mean-variance
portfolio selection model to select suitable rooftops by identifying a combination
of buildings that will maximize solar energy outputs and minimize system
variability. Our approach is implemented using some real data-sets.
TC59
59-Room 110B, CC
Impacts of Climate Change
Sponsor: ENRE – Environment II – Forestry
Sponsored Session
Chair: Chris Lauer, Oregon State, Portland, OR,
United States of America,
1 - Planning Forest Harvesting under Climate Change:
A Stochastic Optimization Model
Jordi Garcia, Researcher, Instituto Superior de Agronomia,
Universidade de Lisboa, Portugal, Tapada da Ajuda., Lisbon,
Portugal, Andres Weintraub,
Cristobal Pais, Joanna Bachmatiuk
In this paper we consider a medium term forest planning problem in the presence
of uncertainty due to climate change. For each time period the forest planner
must decide which areas to cut in order to maximize expected net profit. A
multistage stochastic model using 32 climate scenarios was developed and solved
to determine optimal harvesting decisions under uncertainty. The stochastic
solutions were compared to the solution of a deterministic model where an
average climate scenario was used.
2 - Will Climate Change Induced Effects Cause Harm to Value Chains
of the Bio-based Industry?
Peter Rauch, Pd, BOKU, Feistmantelstrasse 4, Wien, 1180,
Austria,
Uncertainty increasingly affects ecosystems and storms and bark beetle
infestations are the main causes of forest damage. Risks and their impacts on
value chains of the bio-based industry are evaluated by a System Dynamics model
of the Austrian wood supply including a stochastic simulation of risk agents.
Results provide insights on probabilistic future wood supply security for sawlogs,
pulpwood resp. energy wood and reveal a contra-intuitive system effect for the
climate change scenario.
3 - Multiobjective Optimization to Study the Impact of Climate
Change on the Joint Provision of Ecosystem Services
Nick Kullman, Masters Student, University of Washington,
360 Bloedel Hall, Seattle, WA, United States of America,
Sventlana Kushch, Sandor Toth
Climate change has been shown to alter the provision of forest ecosystem services
such as carbon sequestration and wildfire mitigation. Less understood is how
climate change will alter the tradeoffs among ecosystem services acquired
simultaneously. We present a scenario-based multi-objective mathematical
programming method to study these changes on the joint provision of ecosystem
services in the Deschutes National Forest.
4 - Incorporating Acclimation and Feedback into Reserve Selection
During Climate Change
Austin Phillips, University of Washington, Seattle, WA, United
States of America, Sandor Toth,
Robert Haight
Climate change threatens many species, and conservation in such a dynamic
setting is challenging. We developed a mixed integer reserve selection model that
pairs population dynamics and sequential selection in a nonlinear feedback loop.
The model accounts for species’ ability to acclimate, as well as disperse, to track
suitable conditions. We explore optimal management strategies to facilitate
species’ survival as they disperse and acclimate in response to warming.
TC57