RESERVOIR OPERATING RULES GENERATED BY DETERMINISTIC AND STOCHASTIC OPTIMIZATION
Abstract
The development of reservoir operating rules by deterministic and stochastic optimization is investigated in this study. The deterministic model (DPR) consists of an algorithm that cycles through a dynamic program, a regression analysis and a simulation. In this model, the correlation between the general operating rules and the optimal deterministic operation is being increased by going through an iterative process. The stochastic model (SDP) is a stochastic dynamic program which requires a discrete lag-one Markov process as the streamflow descriptor. The optimization models are preceded by a comprehensive statistical analysis of streamflow series and are followed by a real-time reservoir operation simulation model. Several tests and comparisons are performed for annual and monthly time steps to evaluate the models. Single and multiple reservoir systems are considered; different streamflow characteristics and reservoir sizes are employed. Statistical analyses to evaluate the general operating rules are performed. The results of the evaluations show the significant value of the deterministic model proposed in this study for the operation of reservoir of different sizes and the effectiveness of the stochastic model for the operation of small reservoirs.
Degree
Ph.D.
Subject Area
Civil engineering
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