Uncertainty Analysis of Reservoir Operation
Author: 陳弦韋
Publisher:
Published: 2014
Total Pages:
ISBN-13:
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Author: 陳弦韋
Publisher:
Published: 2014
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Y. Zee Ma
Publisher: AAPG
Published: 2011-12-20
Total Pages: 329
ISBN-13: 0891813780
DOWNLOAD EBOOKAuthor: Rashi Bhushan
Publisher:
Published: 2018
Total Pages: 113
ISBN-13:
DOWNLOAD EBOOKAuthor: Nabeel R. Mishalani
Publisher:
Published: 1987
Total Pages: 192
ISBN-13:
DOWNLOAD EBOOKAuthor: Jaime Collado Moctezuma
Publisher:
Published: 1984
Total Pages: 228
ISBN-13:
DOWNLOAD EBOOKAuthor: Han-Lin Lee
Publisher:
Published: 1987
Total Pages: 188
ISBN-13:
DOWNLOAD EBOOKAuthor: Jianguo Wu
Publisher: Springer Science & Business Media
Published: 2006-07-02
Total Pages: 354
ISBN-13: 1402046634
DOWNLOAD EBOOKThis is the first book of its kind – explicitly considering uncertainty and error analysis as an integral part of scaling. The book draws together a series of important case studies to provide a comprehensive review and synthesis of the most recent concepts, theories and methods in scaling and uncertainty analysis. It includes case studies illustrating how scaling and uncertainty analysis are being conducted in ecology and environmental science.
Author:
Publisher:
Published: 2000
Total Pages:
ISBN-13:
DOWNLOAD EBOOKModeling real-time reservoir operations and developing optimal rules are formidable tasks considering a number of issues that need to be addressed within optimization and simulation models. The issues range from uncertain system inputs to implementation of operating rules in real-time. This dissertation addresses some of these issues that are relevant at different stages of real-time reservoir operation process. These issues are: (i) information uncertainty; (ii) system representation; and (iii) computational intractability. Realtime operation models are developed in the present research for single and multiple reservoir systems while addressing these issues in that order. Uncertainty generally associated with system variables in a variety of forms is a main hurdle in developing a proaches for optimizing reservoir operations. Explicit and implicit stochastic approaches based on traditional probability theory concepts cannot always handle all the uncertain elements of reservoir operation. Approaches to handle imprecise information are required as much as methodologies to address the issue of lack of information. The former issue described as information uncertainty in this thesis is addressed using fuzzy set theory. Mathematical programming models are developed under fuzzy environment to handle imprecise and uncertain components of reservoir operation problem dominated by an economic objective. The concept of 'compromise operating polices' is proposed and its utility is proved. Representation of physical system in mathematical programming formulations affects the extent to which the physics of the problem is captured and nature of the solutions that can be obtained. Tradeoffs between exhaustive representation and optimal solutions can be identified. Operation of a multiple reservoir system is considered to develop formulations of varying degree of system representation. A Mixed Integer Non-Linear Programming (MINLP) Model with binary variables is developed to a speci.
Author: Jinshu Li
Publisher:
Published: 2021
Total Pages: 126
ISBN-13:
DOWNLOAD EBOOKStochastic programming is a mathematical model used to resolve the uncertainty of random variables in optimization problems. In reservoir management and operation, the reservoir inflow is typically regarded as a random variable as it brings most of the operation uncertainty. Although stochastic programming has been successfully applied to many reservoir managements cases, the pursuit of the improvement on its accuracy, efficiency, and applicability never ceases. This dissertation consists of five chapters. The first introductory presents the classical stochastic model and describes the challenges. Then, the second chapter develops a statistical model that focuses on improving the distribution fitting accuracy for the monthly average inflow as the random variable. The third chapter discusses a method aiming at streamflow scenario tree reduction, which is essential for alleviating the computational burden of a two-stage stochastic programming with recourse model. The fourth chapter expands the applicability of stochastic programming model, by introducing a multi-objective, multi-stage stochastic programming with recourse model. The final chapter offers conclusions, discussions, and potential future research opportunities.
Author: Murugesu Sivapalan
Publisher:
Published: 2006
Total Pages: 534
ISBN-13: 9781901502480
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