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Title:Decision support system for reservoir operation using analytical modeling results
Author(s):Zhao, Qiankun
Advisor(s):Cai, Ximing
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Analytical reservoir operation rules
Decision support system
System of reservoirs in parallel
Effective forecast horizon
Abstract:This study applies an analytical approach to solving reservoir operation problems, in particular, developing an algorithm to search for the optimal solution for a system of reservoirs in parallel, establishing procedures to determine the effective forecast horizon, and demonstrating the practical applications of the derived rules. Based on these, a decision support system for reservoir operation is developed. More specifically, the analytical work of this thesis includes two parts. In the first part, a multi-stage optimization model is set up to derive the properties of optimal release decisions for a system of reservoirs in parallel with a single demand site; following that an algorithm is developed using the analytical results. In the second part, the properties of the optimal solution for a single water supply reservoir under uncertain forecast are derived, and these properties are then used to develop criteria and procedures to determine the effective forecast horizon, which can inform reservoir managers in the actual use of inflow forecast. Finally, a prototype reservoir operation decision support system is developed based on the analytical results. This system is to illustrate the applications of analytically derived reservoir operation rules to guide real-world reservoir operations. Through the system, users can use a graphical user interface (GUI) to upload data, execute model, and visualize the results. As a conclusion, being different from most existing studies using numerical models, this thesis shows the capabilities of the analytical approaches in providing information for real-world reservoir operation problems.
Issue Date:2017-12-11
Type:Text
URI:http://hdl.handle.net/2142/99526
Rights Information:Copyright 2017 Qiankun Zhao
Date Available in IDEALS:2018-03-13
2020-03-14
Date Deposited:2017-12


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