COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION¹

Abstract

Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag‐one Markov process. To test the usefulness of both models in generating reservoir operating rules, real‐time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.

Reservoir Operating Rule Optimization for California’s Sacramento Valley

“…Implicit stochastic optimization, a more sophisticated application of deterministic methods, optimizes over a long representative hydrology that is based on historical record or created from synthetic streamflow generators (Jettmar and Young 1975;Lund and Ferreira 1996). Implicit stochastic optimization can yield better results than its explicit counterpart because it can more accurately represent of other aspects of the problem (Karamouz and Houck 1987).…”

Performance evaluation of an irrigation system under some optimal operating policies

“…Use of stochastic dynamic programming (SDP) for deriving optimal operating policies has become popular in recent years (e.g., Stedinger et al, 1984;Esmaeil-Beik & Yu, 1984;Goulter & Tai, 1985;and Karamouz & Houck, 1987). In the context of reservoir operating policies for irrigation alone, Dudley and his associates (Dudley & Burt, 1973;Dudley et al, 1971aDudley et al, , 1971bDudley et al, , 1972Dudley, 1988) have contributed a very useful sequence of models, aimed at developing optimal short-, intermediate-and long-run irrigation policies.…”

Operating Rules from HEC-PRM Results for the Missouri River System: Development and Preliminary Testing

“…Explicitly stochastic optimization methods, for example, typically require an explicit stochastic model of streamflows, which is typically elusive. There is even some work to suggest that the rules produced by implicit stochastic optimization are superior to those produced by explicit stochastic optimization under some circumstances (Karamouz and Houck, 1987).…”