Abstract
This thesis presents a comprehensive multi-fidelityframework for the aerodynamic optimization and regional feasibility assessmentof Vertical Axis Wind Turbines (VAWTs), incorporating low-fidelity modeling,high-fidelity simulation, and techno-economic evaluation. The primarycontribution is a modified Double Multiple Stream Tube (DMST) algorithm with anactive variable pitch control strategy that dynamically adjusts blade pitchangles to maintain a near-constant effective angle of attack throughout therotor’s azimuthal cycle. This departs from conventional fixed-pitch orsinusoidal control by directly targeting aerodynamic optimality and maximizinglift-to-drag performance. At TSR = 3, the variable pitch design achieved a254.4% increase in power coefficient (𝐶𝑝) compared to thefixed-pitch baseline (from 0.0436 to 0.1545). A second key novelty is anAI-based predictive model developed using data from the modified DMST solver. ASupport Vector Machine (SVM) regression model with a cubic kernel was trainedon a large dataset spanning multiple blade profiles, TSRs, solidities, andpitching. This model achieved over 95% prediction accuracy, enabling rapidestimation of 𝐶𝑝 across a wide design envelope andsignificantly reducing computation time. High-fidelity CFD simulations using 2DURANS in ANSYS Fluent validated the DMST calculations. The moving referenceframe model coincided with the overset mesh model, confirming its predictiveaccuracy. The final step involved techno-economic analysis of three UAElocations, namely Masdar City, Sir Bani Yas Island, and Fujairah.Weibull-derived wind speed distributions were used to estimate annual energyproduction (AEP) and capacity factors. Fujairah emerged as the most promisingsite, achieving up to 3.70 GWhannually and capacity factors around 43% with all three turbines. Sir Bani Yasalso showed high potential (CF ≈ 24%), whileMasdar City showed limited viability (CF < 8%). Economic modeling over 20years revealed high financial returns for the Vestas V44 at Sir Bani Yas (NPV:$24.34M, IRR: 29.86%) and Fujairah (NPV: $133.85M, IRR: 130.7%). These findingsconfirm the efficacy of variable pitch control and underscore its role inadvancing VAWT deployment in the UAE.
| Date of Award | 2025 |
|---|---|
| Original language | American English |
| Supervisor | Isam Janajreh (Supervisor) |
Keywords
- Vertical Axis Wind Turbines (VAWTs)
- Variable Pitch Control
- Double Multiple Stream Tube (DMST)
- Techno-Economic Assessment
- Support Vector Machine (SVM) Regression
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