Wind farm layout optimization (WFLO) is the design of wind turbine layout, subject to various financial and engineering objectives and constraints. The first topic of this thesis focuses on solving two variations of WFLO that have different analytical aerodynamic models, and illustrate deep integration of the wake models into mixed-integer programs and constraint programs. Formulating WFLO as MIP and CP enables more quantitative analysis than previous studies could do with heuristics, and allows the practitioners to use an off-the-shelf optimization solver to tackle the WFLO problem. The second topic focuses on another version of WFLO that has two competing objectives: minimization of noise and maximization of energy. A genetic algorithm (NSGA-II) is used. Under these two objectives, solutions are presented to illustrate the flexibility of this optimization framework in terms of supplying a spectrum of design choices with different numbers of turbines and different levels of noise and energy output.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/35706 |
| Date | 17 July 2013 |
| Creators | Zhang, Yun |
| Contributors | Amon, Cristina |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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