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http://hdl.handle.net/11375/23995
Title: | Linearization-Based Strategies for Optimal Scheduling of a Hydroelectric Power Plant Under Uncertainty |
Other Titles: | Linearization-Based Scheduling of Hydropower Systems |
Authors: | Tikk, Alexander |
Advisor: | Swartz, Christopher L. E. |
Department: | Chemical Engineering |
Keywords: | Hydropower/Hydroelectric;Uncertainty;Linearization;Scheduling;Optimization;Mixed-Integer Nonlinear Programming Problem (MINLP);Mixed-Integer Linear Programming Problem (MILP);Successive Linear Programming (SLP);Piecewise Linear Approximations (PLA);Stochastic;Nervousness;Rolling Horizon;Cascaded Reservoirs;Hybrid;nonconvex;Start-up costs;Generators |
Publication Date: | 2019 |
Abstract: | This thesis examines the optimal scheduling of a hydroelectric power plant with cascaded reservoirs each with multiple generating units under uncertainty after testing three linearization methods. These linearization methods are Successive Linear Programming, Piecewise Linear Approximations, and a Hybrid of the two together. There are two goals of this work. The first goal of this work aims to replace the nonconvex mixed-integer nonlinear program (MINLP) with a computationally efficient linearized mixed-integer linear program (MILP) that will be capable of finding a high quality solution, preferably the global optimum. The second goal is to implement a stochastic approach on the linearized method in a pseudo-rolling horizon method which keeps the ending time step fixed. Overall, the Hybrid method proved to be a viable replacement and performs well in the pseudo-rolling horizon tests. |
URI: | http://hdl.handle.net/11375/23995 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Tikk_Alexander_E_2018Dec_MASc.pdf | 3.3 MB | Adobe PDF | View/Open |
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