Robust stochastic optimization for reservoir operation

Limeng Pan, Mashor Housh, Pan Liu, Ximing Cai, Xin Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Optimal reservoir operation under uncertainty is a challenging engineering problem. Application of classic stochastic optimization methods to large-scale problems is limited due to computational difficulty. Moreover, classic stochastic methods assume that the estimated distribution function or the sample inflow data accurately represents the true probability distribution, which may be invalid and the performance of the algorithms may be undermined. In this study, we introduce a robust optimization (RO) approach, Iterative Linear Decision Rule (ILDR), so as to provide a tractable approximation for a multiperiod hydropower generation problem. The proposed approach extends the existing LDR method by accommodating nonlinear objective functions. It also provides users with the flexibility of choosing the accuracy of ILDR approximations by assigning a desired number of piecewise linear segments to each uncertainty. The performance of the ILDR is compared with benchmark policies including the sampling stochastic dynamic programming (SSDP) policy derived from historical data. The ILDR solves both the single and multireservoir systems efficiently. The single reservoir case study results show that the RO method is as good as SSDP when implemented on the original historical inflows and it outperforms SSDP policy when tested on generated inflows with the same mean and covariance matrix as those in history. For the multireservoir case study, which considers water supply in addition to power generation, numerical results show that the proposed approach performs as well as in the single reservoir case study in terms of optimal value and distributional robustness.

Original languageAmerican English
Pages (from-to)409-429
Number of pages21
JournalWater Resources Research
Volume51
Issue number1
DOIs
StatePublished - Jan 2015
Externally publishedYes

Keywords

  • hydropower
  • linear decision rule
  • multiple-reservoir
  • reservoir operation
  • stochastic optimization

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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