Informs 2015

449 / 552

INFORMS Philadelphia – 2015
447
WC61
61-Room 111B, CC
Optimization under Uncertainty: Integration of
Intermittent and Demand Side Resources in
Electric Power Systems
Sponsor: ENRE – Environment I – Environment and Sustainability
Sponsored Session
Chair: Lindsay Anderson, Assistant Professor, Cornell University,
316 Riley Robb Hall, Ithaca, NY, 14853, United States of America,
1 - Chance-constrained Optimal Power Flow with Uncertain Reserves
Johanna Mathieu, Assistant Professor, University of Michigan,
1301 Beal Ave, Ann Arbor, MI, 48109, United States of America,
, Bowen Li, Siqian Shen, Yiling Zhang
Electric loads can be controlled to help the power grid balance supply and
demand, but the amount of reserves available from these resources is uncertain.
We investigate optimization methods to dispatch power systems with uncertain
reserves. Specifically, we formulate a chance-constrained optimal power flow
problem and solve it using various scenario-based and analytical methods. We run
experimental studies and compare the performance and computational
complexity across the cases.
2 - Strategic Price Bidding in Electricity Markets with
Only Renewables
Josh Taylor, Assistant Professor, University of Toronto, 10 King’s
College Rd., SF 1021C, Toronto, ON, M5S3G4, Canada,
Johanna Mathieu
Renewables have low marginal-to-fixed costs ratios. In a power system with only
renewables, the standard marginal-cost pricing mechanism would simply lead to
all prices being equal to zero, which would be unsatisfactory. Motivated by other
high-fixed, low-marginal cost industries like software and digital media, we
analyze an extension of Bertrand-Edgeworth competition in which renewable
producers with random capacities compete through a single, non-physical price to
fulfill a random demand.
3 - Optimal Development of Wind Farm with Energy Storage in
Micro-grid Community
Qing Li, PhD Candidate, Rutgers University, 96 Frelinghuysen
Road, CoRE Building, Room 201, Piscataway, NJ, 08854, United
States of America, Honggang Wang
Wind power has been widely used in micro-grids for local community energy
consumptions. While it is clean, sustainable and low operational cost, wind power
availability is highly fluctuant. A practical solution to maintain sufficiency is using
energy storage. We develop computational models and optimization methods for
optimal development and management of wind farm with energy storage. Two-
stage optimization framework is proposed to seek and improve the optimal
number and placement of turbines.
4 - Social Effects in the Diffusion of Solar Panels: A Dynamic Discrete
Choice Approach
Sebastian Souyris, PhD Candidate, The University of Texas at
Austin, 2110 Speedway Stop B6500, Austin, TX, 78712, United
States of America, Jason A. Duan,
Anant Balakrishnan, Varun Rai
We study the diffusion of residential solar panels by assuming looking forward
households. We propose a dynamic discrete choice model, where the households
estimate the return on investment and are influenced by previous spatio-temporal
distributed adopters. We project the dynamics of the market; thereby, giving
insights about where the developers should focus their customer acquisition
efforts and what schedule of incentives would be more efficient to stimulate
adoption.
WC62
62-Room 112A, CC
Distributed Energy Generation
Cluster: Energy Systems: Design, Operation, Reliability and
Maintenance
Invited Session
Chair: Alexandra Newman, Professor, Colorado School of Mines,
Mechanical Engineering, Golden, CO, 80401, United States of America,
1 - Optimizing A Renewable, Hybrid Distributed Energy
Generation System
Gavin Goodall, PhD Student, Colorado School of Mines,
Golden, CO, 80401, United States of America,
We formulate a mixed integer linear program to select renewable technologies
such as wind and solar, and conventional technologies such as diesel generators
and batteries, to minimize system costs subject to operational, load, and spinning
reserve constraints. We use statistical models to generate realizations of load, solar
irradiance and wind speed. Solutions from our optimization model prescribe both
a procurement and a dispatch strategy for these realizations, with additional
realistic data.
2 - Robust Unit Commitment Problem with Valid Inequalities and
Computational Study
Wei Wang, PhD Student, University of South Florida, 4202
E.Fowler Ave. ENB, Tampa, FL, 33620, United States of America,
, Bo Zeng
In order to improve the computational performance of robust unit commitment
problem, we study the polyhedron of unit commitment problem, derive some
valid inequalities and incorporate them into robust formulation. Preliminary
computational results will be presented to evaluate their impact.
3 - Integration of Demand Dynamics and Investment Decisions on
Distributed Energy Resources
Farbod Farzan, Rutgers University, 96 Frelinghuysen Road,
Piscataway, Ne, 08901, United States of America,
Farnaz Farzan, Mohsen Jafari
We coupled investment decisions on distributed generation(DG) with demand
side management(DSM). An adaptive model is used for load calculations on a
premise that expected dynamical effects due to DSM strategies cannot be captured
by forecast models. To demonstrate the effect of coupling of DG investment
decisions and DSM, three scenarios(S) are presented. SI is used for benchmarking.
Load patterns for PEVs are introduced in SII. SIII is an extended version of SII,
where smart devices are adopted
4 - Multi-objective Optimization of Grid-connected Decentralized
Energy Systems
Ayse Kocaman, Assistant Professor, Bilkent University, Bilkent
Universitesi, Endustri Muhendisligi, Ankara, 06800, Turkey,
Ozlem Karsu
Along with the transition from fossil fuel based centralized energy systems to
decentralized renewable energy systems, decision makers will have to make a
choice between using two types of electricity, one of which is less expensive but
also associated with high CO2 emissions and the other is clean but more costly.
Here, we develop a decision support system that decides on the scales of energy
production facilities to be used in the process of moving towards decentralized
energy systems.
WC63
63-Room 112B, CC
Operations Management V
Contributed Session
Chair: Ahmed Ghoniem, Isenberg School of Management, UMass
Amherst, 121 Presidents Dr., Amherst, MA, 01002, United States of
America,
1 - Performance of Office-based Versus Home-based Call Center
Agents: Evidence from Three Industries In
Hyojeong Kim, University of Oregon, 2050 Goodpasture Pl,
Heron Club Apartment 42, Eugene, OR, 97401, United States of
America, Nagesh Murthy
We examine the performance of call center agents that work from office vis-à-vis
those that work from home. The home-based workers achieve significantly higher
call productivity without any loss of call service quality. These differences are
accentuated by task complexity and call routing clarity perceived by the agents.
2 - The Research on Modularization Order-picking Policy Based on
Combination Forecasting
Shuiyin Zhou, Associate Professor, Huazhong University of
Science and Technology, NO. 1037, Luoyu Road, Wuhan,
430074, China, , Miao Li
Modularization order-picking policy was proposed to improve the response speed
of orders and reduce the cost. The method of determining modules and the
process of order-picking were described in detail and mathematic optimal model
was established in the article, then algorithms were used to solve the problem.
What is more, combination forecasting method was used to get the final module
set. The results showed that the policy could improve the efficiency of order-
picking effectively.
WC63