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http://hdl.handle.net/11375/23995
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DC Field | Value | Language |
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dc.contributor.advisor | Swartz, Christopher L. E. | - |
dc.contributor.author | Tikk, Alexander | - |
dc.date.accessioned | 2019-03-12T18:53:20Z | - |
dc.date.available | 2019-03-12T18:53:20Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://hdl.handle.net/11375/23995 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.subject | Hydropower/Hydroelectric | en_US |
dc.subject | Uncertainty | en_US |
dc.subject | Linearization | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Optimization | en_US |
dc.subject | Mixed-Integer Nonlinear Programming Problem (MINLP) | en_US |
dc.subject | Mixed-Integer Linear Programming Problem (MILP) | en_US |
dc.subject | Successive Linear Programming (SLP) | en_US |
dc.subject | Piecewise Linear Approximations (PLA) | en_US |
dc.subject | Stochastic | en_US |
dc.subject | Nervousness | en_US |
dc.subject | Rolling Horizon | en_US |
dc.subject | Cascaded Reservoirs | en_US |
dc.subject | Hybrid | en_US |
dc.subject | nonconvex | en_US |
dc.subject | Start-up costs | en_US |
dc.subject | Generators | en_US |
dc.title | Linearization-Based Strategies for Optimal Scheduling of a Hydroelectric Power Plant Under Uncertainty | en_US |
dc.title.alternative | Linearization-Based Scheduling of Hydropower Systems | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Chemical Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
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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