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Stochastic dynamic programming models for reservoir operation optimization
Author(s) -
Stedinger Jery R.,
Sule Bola F.,
Loucks Daniel P.
Publication year - 1984
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr020i011p01499
Subject(s) - inflow , variable (mathematics) , stochastic programming , dynamic programming , state variable , environmental science , computer science , hydrology (agriculture) , mathematical optimization , geology , mathematics , geotechnical engineering , mathematical analysis , oceanography , physics , thermodynamics
Most applications of stochastic dynamic programming have derived stationary policies which use the previous period's inflow as a hydrologic state variable. This paper develops a stochastic dynamic programming model which employs the best forecast of the current period's inflow to define a reservoir release policy and to calculate the expected benefits from future operations. Use of the best inflow forecast as a hydrologic state variable, instead of the preceding period's inflow, resulted in substantial improvements in simulated reservoir operations with derived stationary reservoir operating policies. While these results are for a dam at Aswan in the Nile River Basin, operators of other reservoir systems also have available to them information other than the preceding period's inflow which can be used to develop improved inflow forecasts.