Long term infrastructure investments under uncertainty in the electric power sector using approximate dynamic programming techniques
Name
891139083-MIT.pdf
Description
Full printable version
Size
19.48 MB
Format
Adobe PDF
Checksum (MD5)
6fc26960393ebc99545690297cd2b4b7
Author(s)
Seelhof, Michael
Advisor(s)
Mort Webster.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
A computer model was developed to find optimal long-term investment strategies for the electric power sector under uncertainty with respect to future regulatory regimes and market conditions. The model is based on a multi-stage problem formulation and uses approximate dynamic programming techniques to find an optimal solution. The model was tested under various scenarios. The model results were analyzed with regards to the optimal first-stage investment decision, the final technology mix, total costs, the cost of ignoring uncertainty and the cost of regulatory uncertainty.
Description
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 179-183).
Subjects
Engineering Systems Division.
System Design and Management Program.
MIT Department
System Design and Management Program.
Massachusetts Institute of Technology. Engineering Systems Division
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