An Enhanced Decomposition Algorithm for Multistage Stochastic Hydroelectric Scheduling

Abstract

Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems. Stochastic programming, Hydroelectric scheduling, Large-scale Systems.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA278706

Entities

People

  • David P. Morton

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Computer Programming
  • Decomposition
  • Demographic Cohorts
  • Energy
  • Energy Production
  • Flow Network
  • Iterations
  • Linear Programming
  • Mathematical Programming
  • Operations Research
  • Optimization
  • Probability
  • Probability Distributions
  • Reservoirs
  • Simplex Method

Readers

  • Combustion and Flow Dynamics.
  • Military Engineering.
  • Operations Research