Large band simulation of the wind speed for real time wind turbine simulators

“…Step 1.1 Data Profiles: Collect wind farm parameters and create a complete set of wind speed data with wind speed emulation techniques [41]. Here, the low and medium mean wind speeds v m range from 4 m/s to 7 m/s with the sampling step of 0.2 m/s, the sampling period of 20 min, and the integral length scale as 100.…”

Section: Improved Atg Controlmentioning

confidence: 99%

An Improved Adaptive-Torque-Gain MPPT Control for Direct-Driven PMSG Wind Turbines Considering Wind Farm Turbulences

et al. 2016

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Maximum power point tracking (MPPT) plays an important role in increasing the efficiency of a wind energy conversion system (WECS). In this paper, three conventional MPPT methods are reviewed: power signal feedback (PSF) control, decreased torque gain (DTG) control, and adaptive torque gain (ATG) control, and their potential challenges are investigated. It is found out that the conventional MPPT method ignores the effect of wind turbine inertia and wind speed fluctuations, which lowers WECS efficiency. Accordingly, an improved adaptive torque gain (IATG) method is proposed, which customizes adaptive torque gains and enhances MPPT performances. Specifically, the IATG control considers wind farm turbulences and works out the relationship between the optimal torque gains and the wind speed characteristics, which has not been reported in the literature. The IATG control is promising, especially under the ongoing trend of building wind farms with large-scale wind turbines and at low and medium wind speed sites.

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“…Fourier analysis, wavelet analysis, and other data driven methods are the classical approaches (Kusiak et al, 2009b;Kusiak and Zhang, 2010;Landberg, 1999;Lei et al, 2009). Sometimes, methods from artificial intelligence realm are developed as well (Mohandes et al, 2004;Monfared et al, 2007;Nichita et al, 2002). The mentioned prediction methods are applied for power systems control and management (Damousis et al, 2004;Kusiak et al, 2009a;Song, 2009, 2010;Kusiak and Zheng, 2009;Kusiak et al, 2009c;.…”

Section: Motivationsmentioning

confidence: 99%

“…In order to develop fault detection and validate fault detection methods, it is necessary to develop a reliable wind model, representing the most crucial components of the system input load. Such a model should be an integral part of a wind turbine cybernetic model (Bystryk and Sullivan, 2011;Conant and Ashby, 1970;Nichita et al, 2002). We intended both to increase the understanding of the wind variability and also to be able to generate data, which are otherwise hard or even impossible to measure, like for example data from very strong wind with gusts from a longer time and of a chaotic, non-repetitive pattern.…”

Section: Introductionmentioning

confidence: 99%