You are in:Home/Publications/Computational Design Scheme for Wind Turbine Drive-Train Based on Lagrange Multipliers

Ass. Lect. Mohamed Shehata Saleh Khalil :: Publications:

Title:
Computational Design Scheme for Wind Turbine Drive-Train Based on Lagrange Multipliers
Authors: Mohammed Saleh, Ayman Nadaa, Ahmed El-Betar, and Ahmed El-Assal
Year: 2017
Keywords: Nonholonomic systems, Lagrange multipliers, Wind Turbine Drive-Trains.
Journal: Jornal of Energy
Volume: 2017
Issue: Not Available
Pages: 16
Publisher: Hindawi
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

The design optimization of wind turbines and their subsystems will make them more attractive and competitive as an ideal alternative for energy. This paper proposed a design procedure for one of these subsystems, which is the Wind- Turbine Drive-Train (WTDT). The design of the WTDT is based on the load assumptions and can be considered as the most important parameter for increasing the eciency of energy generation. In industry, these loads are supplemented by expert assumptions and are extrapolated by static manipulations to calculate the local load in the design of transmission elements, e.g. gears, bearings, and shafts. In contrary, in this work, the multibody system approach is used to estimate the static as well as dynamic loads based on the Lagrange multipliers. Lagrange multipliers are numerical parameters associated with the holonomic and non-holonomic constraints assigned in the drive-train model. The proposed scheme includes, computational manipulations of kinematic constraints, mapping the generalized forces into Cartesian respective, and enactment of velocity-based constrains. Based on the dynamic model and the obtained forces, the design process of a planetary stage of WTDT is implemented with trade-o 's optimization in terms of gearing parameters. A wind turbine of 1.4 Megawatts nominal power is introduced as an evaluation study of the proposed procedure, in which, the main advantage is the systematic nature of designing complex systems in motion.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus