Operations Research
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


OPERATIONS RESEARCH
Vol. 50, No. 2, March-April 2002, pp. 297-310
DOI: 10.1287/opre.50.2.297.429
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Tseng, C.-L.
Right arrow Articles by Barz, G.
Right arrow Search for Related Content

Short-Term Generation Asset Valuation: A Real Options Approach

Chung-Li Tseng, Graydon Barz

Department of Civil & Environmental Engineering, University of Maryland, College Park, Maryland 20742
Electricity & Natural Gas Practice, McKinsey & Co., Two Houston Center, 909 Fannin, Suite 3500, Houston, Texas 77010

chungli{at}eng.umd.edu
gbarz{at}yahoo.com

This paper discusses using real options to value power plants with unit commitment constraints over a short-term period. We formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit, that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit, and that these commitment decisions, once made, are subject to physical constraints such as minimum uptime and downtime. We also account for the costs associated with starting up and shutting down a unit. Last, we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow Ito processes. Using numerical simulation, we show that failure to consider physical constraints may significantly overvalue a power plant.

Subject classifications: Natural resources: energy; Decision analysis: applications; Finance: investment.
History: Received July 1999; accepted September 2000.







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2002 by INFORMS.