R: Stochastic Dynamic Programming (Deprecated function; use...

sdp {reservoir}

R Documentation

Stochastic Dynamic Programming (Deprecated function; use 'sdp_supply' instead)

Description

Derives the optimal release policy based on storage state, inflow class and within-year period.

Usage

sdp(Q, capacity, target, S_disc = 1000, R_disc = 10, Q_disc = c(0, 0.2375,
  0.475, 0.7125, 0.95, 1), loss_exp = 2, S_initial = 1, plot = TRUE,
  tol = 0.99, rep_rrv = FALSE)

Arguments

`Q`	time series object. Net inflows to the reservoir.
`capacity`	numerical. The reservoir storage capacity (must be the same volumetric unit as Q and the target release).
`target`	numerical. The target release constant.
`S_disc`	integer. Storage discretization–the number of equally-sized storage states. Default = 1000.
`R_disc`	integer. Release discretization. Default = 10 divisions.
`Q_disc`	vector. Inflow discretization bounding quantiles. Defaults to five inflow classes bounded by quantile vector c(0.0, 0.2375, 0.4750, 0.7125, 0.95, 1.0).
`loss_exp`	numeric. The exponent of the penalty cost function–i.e., Cost[t] <- ((target - release[t]) / target) ^ loss_exp). Default value is 2.
`S_initial`	numeric. The initial storage as a ratio of capacity (0 <= S_initial <= 1). The default value is 1.
`plot`	logical. If TRUE (the default) the storage behavior diagram and release time series are plotted.
`tol`	numerical. The tolerance for policy convergence. The default value is 0.990.
`rep_rrv`	logical. If TRUE then reliability, resilience and vulnerability metrics are computed and returned.

Value

Returns a list that includes: the optimal policy as an array of release decisions dependent on storage state, month/season, and current-period inflow class; the Bellman cost function based on storage state, month/season, and inflow class; the optimized release and storage time series through the training inflow data; the flow discretization (which is required if the output is to be implemented in the rrv function); and, if requested, the reliability, resilience, and vulnerability of the system under the optimized policy.

References

Loucks, D.P., van Beek, E., Stedinger, J.R., Dijkman, J.P.M. and Villars, M.T. (2005) Water resources systems planning and management: An introduction to methods, models and applications. Unesco publishing, Paris, France.