SBIR-STTR Award

Optimal capacity expansion under uncertainty
Award last edited on: 11/22/2002

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$49,631
Award Phase
1
Solicitation Topic Code
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Principal Investigator
James Smallwood

Company Information

Applied Decision Analysis Inc

2710 Sand Hill Road
Menlo Park, CA 94025
   (415) 854-7101
   N/A
   N/A
Location: Single
Congr. District: 18
County: San Mateo

Phase I

Contract Number: 9160155
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
1991
Phase I Amount
$49,631
Capacity expansion refers to the process of adding facilities to meet a rising demand for services or products. The goal of the research is to develop a precise mathematical model (based on a piecewisedeterministic Markov process) for the uncertainties in capacity expansion planning, and to study the construction of optimal plans with this framework by means of stochastic control theory. To provide a concrete context for the work, researchers plan to direct the research toward the specific capacity expansion plans faced by electric utilities. The research goal is being achieved by: (1) formulating a representative class of capacity expansion problems using demand and completion time data from electric utilities; (2) determining optimal controls or investment strategies for these problems using analytic and numerical techniques; and (3) implementing these optimization techniques on a computer and generating a set of clear, illustrative examples of their effectiveness.The potential commercial application as described by the awardee: An optimization technique for generation expansion planning would have direct application to determining reserve margins, adopting new technologies, selecting unit sizes, and ensuring reliability. In addition, such a technique would provide important leverage for addressing complex capacity expansion problems in other industries.

Phase II

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
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Phase II Amount
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