2016 INFORMS Annual Meeting Program

209 / 561

INFORMS Nashville – 2016
209
2 - Implementationof The Genetic Gain Performance Metric
Accelerates Agricultural Productivity
Joseph Byrum, Syngenta, West Des Moines, IA, 50265, United
States, , Craig Davis, Greg Doonan,
Tracy Doubler, Bill Beavis, Von Kaster, Sam Parry, Ronald Mowers
Yield is the most important metric for a farmer, as crop output directly impacts
profitability. We now refer to the rate of increase in the genetic potential for yield
in cultivars as “genetic gain,” and it is measured in bushels per acre (bu/ac). The
challenge was to develop models and methods that provide unbiased estimates of
the genetic components of yield for unbalanced field trials conducted across years.
An algorithm was implemented that minimizes the confounding influence of
unpredictable environmental contributions to estimated yields of varieties
enabling real-time unbiased estimation of performance metrics that are used in
operational decision making and optimization.
MD04
101D-MCC
Optimization for Enhancing Critical
Infrastructure Resilience
Sponsored: Energy, Natural Res & the Environment,
Energy I Electricity
Sponsored Session
Chair: Feng Qiu, Argonne National Laboratory, 9700 S. Cass Avenue,
Lemont, IL, 60439, United States,
Co-Chair: Matteo Spada, Paul Scherrer Institut, OHSA/D19, 5232
Villigen PSI, Villigen PSI, Switzerland,
1 - A Framework For Measuring Infrastructure Resilience Of Energy
Systems Taking Natural Hazards And Technical Failures As
Disruption Triggers
Peter Lustenberger, Paul Scherrer Institut/ETH Zurich, Singapore,
Singapore, Tianyin Sun, Patrick Gasser,
Wansub Kim, Peter Burgherr, Matteo Spada, Stefan Hirschberg
This work first provides a quantifiable and feasible technical resilience definition
and measure specifically for energy systems. Following this definition, we propose
a framework for measuring the technical resilience of both the components
(power plants, substations, refineries, compressor stations etc.) and the network
topology of power grid and oil/gas supply systems by considering probabilistic
disruption triggers of both natural hazards and technical failures as well as
recovery dynamics.
2 - Prioritization Of Infrastructure Resilience Investments
Julia Phillips, Argonne National Laboratory,
Recent events emphasize the importance of the protection and resilience of
systems of critical infrastructure. This talk explores initial research on
prioritization of infrastructure investments for resilience through optimization
considering owner risk profiles. It is hypothesized that owners of different types of
critical infrastructure systems may let their risk tendencies influence how to
allocate funds as opposed to what investments are “optimal” considering
monetary value only. The research community has struggled with the
measurement of resilience. We use a technique of perceived value to assist in
measurement of resilience and prioritization of investment funds.
3 - Wind-participated Power System Restoration
Feng Qiu, Argonne National Laboratory,
Black-start resources, electric generators that can start on their own without
power supply from the grid, are critical initial power sources for power system
restoration. Wind generation, with black-start capability, however, has not been
considered as black-start resources due to its unreliability (variable and
uncertain). As the wind integration continues to grow, wind-participated system
restoration becomes not only a viable but also a valuable solution. In this talk, we
will present an optimization model to incorporate wind in the system restoration.
Wind uncertainty and variability will be addressed to ensure the success of system
restoration.
4 - Repair, Rebuild, Or Replace? Protecting Aging Infrastructure From
Hazards And Threats
David L. Alderson, Naval Postgraduate School,
Jan Brendecke, Kyle Y Lin
We consider an infrastructure system whose function depends on a number of
components that fail randomly according to known rates. Components that are
“new” have a small failure rate and components that are “old” have a larger
failure rate. When a component fails it can be replaced to “new” status or
repaired to “old” status. An “old” component can also be proactively replaced to
“new” status. We formulate and solve a Markov decision process to identify the
optimal replace/repair policies for given system operating costs and discuss
implications for real infrastructure systems.
MD05
101E-MCC
Power System Generation and
Transmission Expansion
Sponsored: Energy, Natural Res & the Environment,
Energy I Electricity
Sponsored Session
Chair: Enzo E Sauma, Pontificia Universidad Catolica de Chile, Vicuña
Mackenna 4860, Macul., Santiago, 7820436, Chile,
1 - Risk-averse Transmission And Generation Planning:
Wecc Case Study
Francisco Munoz, Universidad Adolfo Ibáñez,
, Harry van der Weijde, Benjamin
Field Hobbs, Jean-Paul Watson
We investigate the effects of risk aversion on optimal transmission and
generation expansion planning in a competitive market. To do so, we formulate a
stochastic model which minimizes a weighted average of expected transmission
and generation costs and their conditional value at risk (CVaR), and which can be
shown to have an equivalent solution to a perfectly competitive risk-averse
Stackelberg equilibrium in which a risk-averse transmission planner maximizes
welfare after which risk-averse generators maximize profits.
2 - How Technical Operational Details Affect Generation Expansion In
Oligopolist Markets
Efraim Centeno, Universidad Pontificia Comillas - IIT,
, Sonja Wogrin, Adelaida Nogales
We propose a generation expansion model including an oligopolistic market
representation based on an equilibrium approach. We incorporate the system
states methodology into this generation expansion model allowing us to recover
some chronological information in a LDC framework, thereby more accurately
accounting for start-up and shut-down costs without making use of an hourly
representation of demand. We find that when operational details are considered,
flexible technologies are preferred by the companies in the optimal mix. We also
observe that under perfect competition in comparison with oligopolistic markets,
more base-load plants are built as well as more peaking plants.
3 - Sustainable Transmission Planning In Imperfectly Competitive
Electricity Industries: Balancing Economic Efficiency And
Environmental Outcomes
Afzal S. Siddiqui, Stockholm University, Stockholm, Sweden,
Afzal S. Siddiqui, HEC Montréal, Montréal, QC, H3T 2A7, Canada,
Makoto Tanaka, Yihsu Chen
We address the problem of a TSO that builds a transmission line in order to
maximise social welfare inclusive of the cost of emissions. A TSO in a deregulated
industry can only indirectly influence outcomes via its choice of the transmission
line capacity. Via a bi-level model, we show that this results in less transmission
capacity with limited emissions control if industry is perfectly competitive. A
carbon tax on industry leads to perfect alignment of incentives and maximised
social welfare only under perfect competition. By contrast, a carbon tax actually
lowers social welfare under a Cournot oligopoly as the resulting reduction in
consumption facilitates the further exercise of market power.
4 - Power Capacity Expansion Planning And The Influence Of
Network Payment Schemes
Enzo Sauma, Pontificia Universidad Católica de Chile,
, Diego Bravo, Javier Contreras,
Sebastián de la Torre, José Aguado, David Pozo
We propose a multi-annual transmission expansion planning model seeking to
reduce the total system costs and considering different network payment
schemes. The proposed models are reformulated as Mixed Integer Linear
Programming (MILP) problems. A realistic case study based on the main power
system in Chile is analyzed to illustrate the proposed models. It is shown that
integrating line cost-recovering equations into the Transmission Expansion
Planning model may result into a more realistic and less congested power
network. Also, total system cost is highly related with transmission tariff
discrimination.
MD05