This paper presents and compares four types of stochastic dynamic programming (SDP) for on‐line reservoir operation, relying on observed or forecasted inflows. The models are different because of the assumptions regarding the inflow in the next time period. If this inflow is known (or a forecast is possible with 100% reliability) models with expected value of the future returns are possible (present returns are deterministic). Otherwise, a simple forecast based on conditional probabilities is necessary, and present and future returns are random. The objective is to maximize expected annual hydropower generation. In a case study of the Feitsui Reservoir in Taiwan, SDP models appear to provide efficient long‐term operating policies. The simulation of on‐line operation of the reservoir reveals that the SDP model that relies on the observed inflows of the preceeding time step provides the best performance. Nevertheless, under different hydrological regimes this finding might be not universal, but dependent up...
[1]
R. Harboe,et al.
Generation of operating rules with stochastic dynamic programming and multiple objectives
,
1988
.
[2]
William W.-G. Yeh,et al.
Reservoir Management and Operations Models: A State‐of‐the‐Art Review
,
1985
.
[3]
George L. Nemhauser,et al.
Introduction To Dynamic Programming
,
1966
.
[4]
Stuart E. Dreyfus,et al.
Applied Dynamic Programming
,
1965
.
[5]
S. Yakowitz.
Dynamic programming applications in water resources
,
1982
.
[6]
Ian C. Goulter,et al.
Practical implications in the use of stochastic dynamic programming for reservoir operation
,
1985
.