Uncertainty Analysis of Reservoir Operation: The Stochastic Process Model of Reservoir Water Level
Date Issued
2014
Date
2014
Author(s)
Chen, Hsien-Wei
Abstract
A totally different reservoir operation rule is proposed here. In this study, the operation rule is obtained by modeling the stochastic process of future water levels instead of the traditional optimization modeling approaches. This involves (1) the derivation of statistical properties of bivariate gamma random variables, especially, this study gives an important rule that the random variable obtained by adding or subtracting a pair of gamma random variables is still approximately a gamma random variable, (2) extending bivariate gamma random variables to gamma time series to model the inflow time series, and establishing the modeling and simulation procedure of gamma time series, (3) establishing the gamma time series model for future reservoir water levels via the water balance between inflows and outflows and the statistical properties of bivariate gamma random variables, (4) the final operation rule is simply given by evaluating the probabilities of the occurrence of risk water levels via simulating realizations from the gamma time series model of the future water level.
Once the final operation rule is established, the rule itself is well-defined and easy-to-implement. It is able to combine long term, short term, and multi-goals operations to one optimization because the probability mechanism has been given. The only needed material for the analysis is the inflow data, thus, it can also be applied to estimate the required storage size to fulfill needs before building a new reservoir.
Subjects
雙變數伽碼分佈
分佈轉換
伽碼時間數列
序率過程
序率模擬
頻率因子
Type
thesis
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