Long term infrastructure investments under uncertainty in the electric power sector using approximate dynamic programming techniques

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Seelhof, Michael

Advisor dc:contributor.advisor

• Mort Webster.

• Engineering Systems Division.
• System Design and Management Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/90724

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/90724