The Value of Hydrologic Information in Stochastic Dynamic Programming Models of a Multireservoir System

Reservoir operating policies can be derived using stochastic dynamic programming (SDP) with different hydrologic state variables. This paper considers several choices for such hydrologic state variables for SDP models of the Shasta-Trinity system in northern California, for three different benefit functions. We compare how well SDP models predict their policies will perform, as well as how well these policies performed when simulated. For a benefit function stressing energy maximization, all policies did nearly as well, and the choice of the hydrologic state variable mattered very little. For a benefit function with larger water and firm power targets and severe penalties on corresponding shortages, predicted performance significantly overestimated simulated performance, and policies that employed more complete hydrologic information performed significantly better.

[1]  Barry J. Adams,et al.  Comment on “Error analysis of conventional discrete and gradient dynamic programming” by P. K. Kitanidis and Efi Foufoula‐Georgiou , 1988 .

[2]  S. Gal.  Optimal management of a multireservoir water supply system , 1979 .

[3]  Carlo Piccardi,et al.  Stochastic dynamic programming for reservoir optimal control: Dense discretization and inflow correlation assumption made possible by parallel computing , 1991 .

[4]  John D. C. Little,et al.  The Use of Storage Water in a Hydroelectric System , 1955, Oper. Res..

[5]  J. Stedinger,et al.  Sampling stochastic dynamic programming applied to reservoir operation , 1990 .

[6]  Nathan Buras,et al.  Alternative specifications of state variables in stochastic-dynamic-programming models of reservoir operation , 1991 .

[7]  M. Karamouz,et al.  COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1 , 1987 .

[8]  Joel Max,et al.  Quantizing for minimum distortion , 1960, IRE Trans. Inf. Theory.

[9]  P. R. H. Sales,et al.  Coordinating the Energy Generation of the Brazilian National Hydrothermal Electrical Generating System , 1986 .

[10]  Haralambos V. Vasiliadis,et al.  DEMAND – DRIVEN OPERATION OF RESERVOIRS USING UNCERTAINTY – BASED OPTIMAL OPERATING POLICIES , 1994 .

[11]  William W.-G. Yeh,et al.  Reservoir Management and Operations Models: A State‐of‐the‐Art Review , 1985 .

[12]  Aris P. Georgakakos,et al.  Optimal Stochastic Operation of Salt River Project, Arizona , 1991 .

[13]  Jery R. Stedinger,et al.  HEURISTIC OPERATING POLICIES FOR RESERVOIR SYSTEM SIMULATION , 1991 .

[14]  Rolf A. Deininger,et al.  Generalization of White's Method of Successive Approximations to Periodic Markovian Decision Processes , 1972, Oper. Res..

[15]  Ying Li,et al.  Numerical Solution of Continuous-State Dynamic Programs Using Linear and Spline Interpolation , 1993, Oper. Res..

[16]  J. Stedinger,et al.  Water resource systems planning and analysis , 1981 .

[17]  J. J. Bogardi,et al.  Testing Stochastic Dynamic Programming Models Conditioned on Observed or Forecasted Inflows , 1991 .

[18]  Daniel P. Loucks,et al.  Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation , 1982 .

[19]  S. Yakowitz.  Dynamic programming applications in water resources , 1982 .

[20]  B. F. Sule,et al.  Stochastic dynamic programming models for reservoir operation optimization , 1984 .

[21]  Haralambos V. Vasiliadis,et al.  Bayesian stochastic optimization of reservoir operation using uncertain forecasts , 1992 .

[22]  Dapei Wang,et al.  Optimization of Real‐Time Reservoir Operations With Markov Decision Processes , 1986 .

[23]  Siavash Esmaeil‐Beik,et al.  Optimal Operation of Multipurpose Pool of Elk City Lake , 1984 .

[24]  Daniel P. Louks,et al.  Multiple Reservoir Operation in North America , 1981 .

[25]  Konstantin Staschus,et al.  Computer Simulation of CVP Power Production for Integration With PG&E's Power System , 1989 .

[26]  Roman Krzysztofowicz.  Optimal Water Supply Planning Based on Seasonal Runoff Forecasts , 1986 .

[27]  R. Bras,et al.  Real time adaptive closed loop control of reservoirs with the High Aswan Dam as a case study , 1983 .

[28]  Sharon A. Johnson,et al.  Comparison of two approaches for implementing multireservoir operating policies derived using stochastic dynamic programming , 1993 .