2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
185
4 - Balancing Diagnostic And Resolution Efforts In A Nonprofit
Service Delivery Organization
Priyank Arora, Georgia Institute of Technology,
800 W Peachtree St NW, Atlanta, GA, 30308, United States,
, Morvarid Rahmani,
Karthik Ramachandran
This paper studies service design of a nonprofit organization (NPO) that aims to
maximize overall utility delivered to its clients. We examine how the NPO should
balance levels of effort between diagnostic and resolution stages of its service
delivery, in the presence of client heterogeneity and resource constraint. Our
analytical model is based on secondary data collected from an NPO working
towards empowerment of victims of domestic violence.
MC09
103B-MCC
Nonlinear Optimization Problems for Power Systems
Invited: Energy Systems Management
Invited Session
Chair: Javad Lavaei, University of California, Berkeley, 4121
Etcheverry, Berkeley, CA, 94720, United States,
1 - Power System State Estimation With A Limited Number
Of Measurements
Ramtin Madani, University of California, Berkeley, Berkeley, CA,
United States, , Javad Lavaei,
Ross Baldick
This work is concerned with the power system state estimation (PSSE) problem,
which aims to find the unknown operating point of a power network based on a
given set of measurements. We develop a set of convex programs with the
property that they all solve the non-convex PSSE problem in the case of noiseless
measurements if the voltage angles are relatively small. This result is then
extended to a general PSSE problem with noisy measurements, and an upper
bound on the estimation error is derived. The objective function of each convex
program has two terms to account for the non-convexity of the power flow
equations and estimate the noise levels. The proposed technique is demonstrated
on a 9000-bus network.
2 - Stochastic Unit Commitment With Topology Control Recourse For
Renewables Integration
Jiaying Shi, University of California, Berkeley, Berkeley, CA,
94720, United States, Shmuel S Oren
We propose a two-stage stochastic unit commitment formulation with topology
control recourse decisions for power systems with renewables integration. We
investigate applying progressive hedging algorithm to solve this problem.
Preliminary test results on both IEEE 118 system and central European system
show that such capability of controlling the system configuration actively through
switching transmission lines can help improve the efficiency of unit commitment.
3 - A Strong Semidefinite Programming Relaxation Of The Unit
Commitment Problem
Javad Lavaei, University of California-Berkeley, Berkeley, CA,
United States, , Morteza Ashraphijuo,
Salar Fattahi, Alper Atamturk
The unit commitment (UC) problem aims to find an optimal schedule of
generating units subject to the demand and operating constraints for an electricity
grid. We develop a strengthened semidefinite program (SDP) based on first
deriving certain valid quadratic constraints and then relaxing them to linear
matrix inequalities. These valid inequalities are obtained by the multiplication of
the linear constraints of the UC problem. The performance of the proposed
convex relaxation is evaluated on several hard instances of the UC problem. By
solving a single convex problem, globally optimal integer solutions are obtained in
most of the experiments that we have conducted.
4 - Optimal Distributed Control Of Power Systems
Salar Fattahi, University of California, Berkeley, Berkeley, CA,
United States, , Abdulrahman Kalbat,
Javad Lavaei
This talk is concerned with the optimal distributed control of power systems
under input disturbance and measurement noise. This optimal control problem is
highly nonlinear and NP-hard. In this work, we design an efficient computational
method that transforms the optimal centralized controller to a near-optimal
distributed controller. We also study how the connectivity of its underlying
communication network affects the optimal performance of the stochastic power
system under control. As a case study, the proposed technique is used to design a
distributed primary frequency controller for the IEEE 39-Bus New England test
System.
MC10
103C-MCC
Food, Energy, Water and Extreme Events
Sponsored: Energy, Natural Res & the Environment, Energy II Other
Sponsored Session
Chair: Sauleh Ahmad Siddiqui, Johns Hopkins University, 3400 N.
Charles St., Latrobe Hall 205, Baltimore, MD, 21218, United States,
Co-Chair: Craig Bakkar, Johns Hopkins University, 3400 N. Charles St.,
Baltimore, MD, 21218, United States,
1 - Mixed Complementarity Modelling In Food Systems
Sauleh Ahmad Siddiqui, Johns Hopkins University,
3400 N. Charles St., Latrobe Hall 205, Baltimore, MD, 21218,
United States, , Craig Bakkar
We are developing a new food systems model investigate the impacts of climate
change. This model is designed to build upon past climate-food research by
modelling the entire food supply chain, connecting more fully with energy and
water sector models, and capturing shock propagation. Our model uses a
microeconomic Mixed Complementarity Problem (MCP) formulation and a new
MCP decomposition method that both reduces wall clock time to solution and
increases the size of solvable problems.
2 - Post-disaster Distribution Systems Restoration
Yushi Tan, University of Washington, 185 Stevens Way,
Seattle, WA, 98195, United States, Feng Qiu
We investigate the problem of repairing a distribution network after a natural
disaster. Such a post-disaster restoration is identified as an NP-hard variant of a
job scheduling problem, in which crew are dispatched to repair the damaged lines
in a way that minimizes the total harm caused by the outages. We implement a
time-indexed ILP formulation with valid inequalities as a benchmark. Two
practical methods are also proposed to solve the problem: a conversion algorithm
and a linear-relaxation-based list scheduling algorithm. Worst case bounds are
analyzed for both algorithms. Numerical results validate the effectiveness of the
proposed methods.
3 - Nonlinear Optimization Of Water Supply Network Pumping Plans
In A Deregulated Electricity Market
Maxime Fender, Optimization Consultant, Artelys, 2001
Boulevard Robert-Bourassa, Suite 1700, Montreal, QC, H3A 2A6,
Canada,
Within the context of deregulated electricity markets, electro-intensive companies
are encouraged to optimize their electricity consumption patterns. This talk
presents a study led by Artelys showing how a water distribution network
operator, facing varying electricity wholesale market prices, can minimize its
water pumping costs. This MINLP (nonlinear pressure loss constraints in pipes /
OnOff pumps binary variables) has been solved using an iterative process
composed of a linear relaxation and a continuous nonlinear optimization solved
respectively by FICO Xpress-Optimizer and Artelys Knitro.
MC11
104A-MCC
Network Vulnerability and Criticality
Sponsored: Optimization, Network Optimization
Sponsored Session
Chair: Chrysafis Vogiatzis, Assistant Professor, North Dakota State
University, CIE 202K, P.O. Box 6050, Fargo, ND, 58108, United States,
1 - Critical Arcs Detection In Influence Networks
Colin P. Gillen, University of Pittsburgh, Pittsburgh, PA, 15261,
United States, Alexander Veremyev,
Oleg A Prokopyev, Eduardo Pasiliao
The influence maximization (MAXINF) problem chooses an optimal set of seed
nodes to maximize the propagation of influence (cascading behavior) in a
network. Given a set of seed nodes and the linear threshold model, our work
proposes to determine which edges - e.g. relationships in a social network - are
most critical to the influence propagation process. NP-completeness of the
problem is proved. Naïve time-dependent and time-independent mixed-integer
programming (MIP) models are stated. An improved MIP-based exact algorithm
and a heuristic are proposed, and computational results presented.
MC11