Model Predictive Control of DFIG-Based Wind Power Generation Systems
| atmire.migration.oldid | 804 | |
| dc.contributor.advisor | Malik, Om | |
| dc.contributor.advisor | Westwick, David | |
| dc.contributor.author | Soliman, Mostafa | |
| dc.date.accessioned | 2013-04-12T17:41:35Z | |
| dc.date.available | 2013-06-15T07:01:51Z | |
| dc.date.issued | 2013-04-12 | |
| dc.date.submitted | 2013 | en |
| dc.description.abstract | Novel control strategies that improve the cost effectiveness of wind energy conversion systems are proposed in this thesis. The main focus is on grid-connected variable-speed variable-pitch wind turbines equipped with doubly fed induction generators (DFIGs). At the wind turbine control level, a multivariable control strategy based on model predictive control techniques is proposed. The proposed strategy is formulated for the whole operating region of the wind turbine, i.e., both partial and full load regimes. The pitch angle and generator torque are controlled simultaneously to maximize energy capture, mitigate drive train dynamic loads, and smooth the power generated while reducing the pitch actuator activity. This has the effect of improving the efficiency and the power quality of the electrical power generated, and increasing the life expectancy of the installation. Extensive simulation studies show that the proposed control strategy provides superior performance when compared to classical control strategies commonly used in the litterature. For applications having fault tolerant control requirements, such as offshore wind farms, a new wind turbine control strategy based on adaptive subspace predictive control is proposed. In contrast with subspace predictive control algorithms previously proposed in the literature, the proposed strategy ensures offset-free tracking. The effectiveness of the proposed strategy is illustrated by simulating a wind turbine under normal operation and a fault in the hydraulic pitch system. Another control problem considered in this thesis is the design of the generator control system to ensure fault ride through for DFIG-based wind turbines. This requirement is dictated by recent grid codes, and it necessitates that the DFIG should be connected to the grid and capable of providing reactive power support during large voltage dips. This is challenging for DFIG-based wind turbines due to their partially rated power converters. In this thesis, a novel control strategy, based on using model predictive control and a dynamic series resistance protection scheme, is proposed to ensure fault ride through requirement. | en_US |
| dc.identifier.citation | Soliman, M. (2013). Model Predictive Control of DFIG-Based Wind Power Generation Systems (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26967 | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/26967 | |
| dc.identifier.uri | http://hdl.handle.net/11023/601 | |
| dc.language.iso | eng | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | en |
| dc.publisher.place | Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | Engineering--Electronics and Electrical | |
| dc.subject.classification | Model Predictive Control | en_US |
| dc.subject.classification | Wind power generation | en_US |
| dc.title | Model Predictive Control of DFIG-Based Wind Power Generation Systems | |
| dc.type | doctoral thesis | |
| thesis.degree.discipline | Electrical and Computer Engineering | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Doctor of Philosophy (PhD) | |
| ucalgary.item.requestcopy | true |