2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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4 - Operational Transparency With Investors
William Schmidt, Cornell University,
Ananth Raman
There is abundant evidence that operational disruptions are damaging to firm
value. This depends not only on characteristics of the firm and its supply chain
but also the level of operational transparency with investors. While the former
has been widely studied, little is known about the implications of operational
transparency. We examine this issue by taking advantage of an exogenous
regulatory shock. A well-defined set of firms was excluded from fully complying
with the new rules, creating a natural quasi-experiment which we exploit. Our
research suggests that credible transparency with investors can alleviate over 50%
of the loss in market value from operational disruption announcements.
SD28
201B-MCC
Energy Operations and Policy
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Ozge Islegen, Kellogg School of Management, Evanston, IL,
United States,
1 - The Economics Of Residential Solar PV Adoption
Ozge Islegen, Kellogg School of Management, o-
, Basak Kalkanci
Given the new policies, federal and state incentives, we show how net metering
rules, rate plans and options to finance solar projects affect the adoption of
residential solar PV.
2 - Remuneration Of Flexibility Using Operating Reserve Demand
Curves: A Case Study Of Belgium
Anthony Papavasiliou, CORE, UCL,
Yves Smeers
We investigate an energy-only market design, referred to as operating reserve
demand curves (ORDC), that rewards flexibility by adjusting the real-time energy
price to a level that reflects the value of capacity under conditions of scarcity. We
test the performance of the mechanism by developing a model of the Belgian
electricity market. We verify that (i) none of the existing combined cycle gas
turbines of the Belgian market can cover their investment costs, and (ii) the
introduction of ORDC restores economic viability for most combined cycle gas
turbines in the Belgian market.
3 - Robust Supply Function Equilibrium In Renewable
Energy Markets
Yuanzhang Xiao, Northwestern University, Evanston, IL, United
States, , Chaithanya Bandi,
Ermin Wei
We consider a market where energy suppliers submit supply functions and bid to
fulfill inelastic demand. Suppliers have renewable energy generation (with zero
cost) and conventional energy generation (with variable costs). Each supplier
performs robust optimization against worst-case realizations of its renewable
energy generation and opponents’ costs of conventional energy generation. We
analyze the resulting robust supply function equilibrium and its efficiency.
4 - An Analysis Of Demand Response Programs In The Wholesale
Electricity Market
Asligul Serasu Duran, Kellogg School of Management, Evanston,
IL, 60208, United States, ,
Baris Ata, Ozge Islegen
This project explores the impact of the participation and compensation of demand
response (DR) providers in the wholesale electricity market on the generation
portfolio, electricity prices and social welfare. Specifically, we model a supply
function equilibrium for generators and DR providers. Then, we analyze the
change in the generation portfolio, and in the welfare of the market participants
due to varying compensation rates of DR providers.
SD29
202A-MCC
Energy Resource Valuation, Investment
and Management
Sponsored: Manufacturing & Service Oper Mgmt, Sustainable
Operations
Sponsored Session
Chair: Owen Wu, Associate Professor, Indiana University, 1309 E. 10th
Street, Bloomington, IN, 47405, United States,
1 - Valuing Distributed Energy Resources In Electricity System
Planning: Locational Benefits And Economies Of Unit Scale
Jesse Jenkins, Massachusetts Institute of Technology,
Distributed energy resources (DERs), including distributed generation, storage,
and demand response, create new options for the provision of electricity services.
Employing a new MILP formulation of the electricity capacity planning problem,
this work evaluates the value of DERs and how they compete with conventional
resources. Tradeoffs between “locational benefits” of DERs—e.g. loss mitigation,
network capacity deferral, constraint mitigation—and economies of unit scale are
considered, and cases where DERs are economically attractive contributors to a
least-cost system mix are presented.
2 - Combined Heat And Power Production – Valuing Flexible
Operation In An Uncertain Environment
Christoph Weber, University Duisburg-Essen,
CHP provides an efficient means of converting fuels into power and heat. At the
same time operation of CHP units is restricted by thermodynamical and technical
constraints and subject to the double uncertainty of power prices and heat
demand. The contribution explores the impact of operational flexibility both in
the CHP unit (extraction condensing vs. backpressure turbines) and in the system
configuration (back-up heat boiler). Analytical results are derived and a
numerical application is presented.
3 - Economic Feasibility Of Compressed Air Energy Storage Under
Market Uncertainty
Reinhard Madlener, Director FCN, Full Professor of Energy Econ &
Mgt, RWTH Aachen University, Mathieustrasse 10, Aachen, 52074,
Germany, , Eide Hammann,
Christoph Hilgers
In light of increased levels of intermittent renewable electricity generation, energy
storage is one option to balance supply and demand and thus to support the
security of power supply. Compressed air energy storage (CAES) is a large-scale
technology that has received considerable attention in recent years. As
conventional CAES uses natural gas as an auxiliary fuel operators are exposed to
price risks on two commodity markets. The more advanced adiabatic version, in
contrast, features higher cycle efficiencies but at the downside of higher capital
outlays. We apply real options analysis to investigate the economic viability of
both technology variants in an uncertain market environment.
4 - Merchant Energy Trading In A Network
Selva Nadarajah, University of Illinois at Chicago, ,
Nicola Secomandi
We formulate the merchant trading of energy on a network of storage and
transport assets as a Markov decision problem. We overcome the intractability of
this model by applying linear optimization in novel ways for approximate
dynamic programming: (i) Iterative extensions of least squares Monte Carlo
techniques based on value/continuation function approximations (V/CFAs) that
are separable/non-separable and piecewise linear concave in the storage
inventory levels; (ii) an extended reoptimization heuristic; and (iii) a perfect
information dual bound based on a separable and linear VFA. We compare these
methods on realistic natural gas instances, highlighting near-optimal methods.
SD29