Power-Electronic Systems for the Grid Integration of Renewable Energy Sources: A Survey

Carrasco, J.M.; Franquelo, Leopoldo G.; Bialasiewicz, J.T.; Galván, E.; Guisado, R.C.P.; Prats, Ma.A.M.; Leon, Jose I.; Moreno-Alfonso, Narciso

doi:10.1109/tie.2006.878356

Cited by 3,447 publications

(1,445 citation statements)

References 48 publications

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“…9 shows the results. One of the result curves is for the neural controller, another is for a tuned PI conventional GCC controller (Luo et al, 2009;Carrasco et al, 2006;Dannehl et al, 2009), and a third is for a "direct-current vector control" structure (DCC, (Li et al, 2010(Li et al, , 2011). The PI controllers were tuned until the controller performance was acceptable (Li et al, 2011).…”

Section: Comparison Of Neural Controller With Conventional Standard Amentioning

confidence: 99%

“…Typical converter configurations containing a GCC include: 1) a dc/dc/ac converter for solar, battery and fuel cell applications (Figueres et al, 2009;Wang and Nehrir, 2007), 2) a dc/ac converter for STATCOM applications (Luo et al, 2009;Carrasco et al, 2006), and 3) an ac/dc/ac converter for wind power and HVDC applications (Carrasco et al, 2006;Xu and Wang, 2007;Mullane et al, 2005;Pena et al, 1996;Rabelo et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances

Fairbank¹,

Li²,

Fu³

et al. 2014

Neural Networks

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractWe present a recurrent neural-network (RNN) controller designed to solve the tracking problem for control systems. We demonstrate that a major difficulty in training any RNN is the problem of exploding gradients, and we propose a solution to this in the case of tracking problems, by introducing a stabilization matrix and by using carefully constrained context units. This solution allows us to achieve consistently lower training errors, and hence allows us to more easily introduce adaptive capabilities. The resulting RNN is one that has been trained off-line to be rapidly adaptive to changing plant conditions and changing tracking targets.The case study we use is a renewable-energy generator application; that of producing an efficient controller for a three-phase grid-connected converter. The controller we produce can cope with random variation of system parameters and fluctuating grid voltages. It produces tracking control with almost instantaneous response to changing reference states, and virtually zero oscil-$ This work was supported in part by the U.S. National Science Foundation under Grant EECS 1059265/1102159, the Mary K. Finley Missouri Endowment, and the Missouri S&T Intelligent Systems Center.Email addresses: michael.fairbank@virgin.net (Michael Fairbank), sli@eng.ua.edu (Shuhui Li), xfu@crimson.ua.edu (Xingang Fu), E.Alonso@city.ac.uk (Eduardo Alonso), dwunsch@mst.edu (Donald Wunsch) Preprint submitted to Neural Networks September 23, 2013 lation. This compares very favorably to the classical proportional integrator (PI) controllers, which we show produce a much slower response and settling time. In addition, the RNN we propose exhibits better learning stability and convergence properties, and can exhibit faster adaptation, than is achievable with adaptive critic designs.

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Section: Comparison Of Neural Controller With Conventional Standard Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances

Fairbank¹,

Li²,

Fu³

et al. 2014

Neural Networks

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“…It provides proper regulation against oversaturation of the magnetic circuit and reduces the magnetizing current. J-C Dai [4] et al has proposed a practical model of direct-driven permanent magnet synchronous generator (PMSG) wind turbines based on neural network. A new technique of wind rotor back propagation and aerodynamic characteristic is described using four layer neural networks.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integration STATCOM PWM Improved Approach to Control Stability in Wind Power System

sha¹,

pi²

2014

IJAREEIE

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ABSTRACT:In this paper a PWM based wind turbine model is been presented with three wind turbines. The presented system is able to provide the system stability in case of varying voltage generation because of varying speed of wind turbine as well as capable to handle the fault over the system. To provide the stability over the system, the statcom based model is been presented in this work. The presented model is been developed in Simulink environment. The analysis of the work is been in terms of voltage analysis in statcom based and statcom less wind turbine model. The obtained results show that the presented system is effective enough to provide the stability over the system.

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“…Actually as stated in [12], floating offshore wind turbines have no specific standards. The type of power transmission technology for offshore depends on the distance from the floating platforms to onshore: for shorter distances, below 60 km alternate current (AC) are reported as a favorable option, but for longer distances direct current (DC) is required [13]. The transmission might become too expensive [14] for faraway exploitation from shore.…”

Section: Introductionmentioning

confidence: 99%

“…A variable speed wind turbine having a PMSG needs an electronic full-power converter to convert the electric energy from a non-constant frequency into a constant one to be injected into an electric grid [18]. So, power converters are extremely important for the operation at variable speed [13]. Better power quality waveform [26], decreasing of THD [27], is possible by the increase on the number of voltage levels on the power converter.…”

Section: Introductionmentioning

confidence: 99%

Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter

et al. 2016

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This paper is on a wind energy conversion system simulation of a transient analysis due to a blade pitch control malfunction. The aim of the transient analysis is the study of the behavior of a back-to-back multiple point clamped five-level full-power converter implemented in a wind energy conversion system equipped with a permanent magnet synchronous generator. An alternate current link connects the system to the grid. The drive train is modeled by a three-mass model in order to simulate the dynamic effect of the wind on the tower. The control strategy is based on fractional-order control. Unbalance voltages in the DC-link capacitors are lessen due to the control strategy, balancing the capacitor banks voltages by a selection of the output voltage vectors. Simulation studies are carried out to evaluate not only the system behavior, but also the quality of the energy injected into the electric grid. © 2015 Elsevier Ltd. All rights reserved.Keywords: Wind energy; five-level power converter; drive train; fractional-order control; simulation. IntroductionEnvironmental problems such as global warming and habitat preservation have to be faced by the society in nowadays in order to achieve a sustainable development. One of the causes for the global warming is said to be the increase on the level of CO 2 in the atmosphere due to fossil fuel burning [1]. However, nowadays fossil fuel burning is needed for supplying the majority of the energy demand [2]. Research and development is on the way to achieve lower pollutants emissions on conversion of energy to convenient forms of usage in order to achieve a sustainable development. Conversion of energy from renewable energy sources are in nowadays a political attractive option [3] and a wind energy conversion system (WECS) is an economically viable exploitation [4], experiencing a significant expansion [5,6]. Although, onshore WECS deployments are cheaper than offshore ones, new suitable available onshore sites for deployments are becoming scarce, particularly in Europe [7]. So, the offshore WECS is becoming a further attractive option.

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Power-Electronic Systems for the Grid Integration of Renewable Energy Sources: A Survey

Cited by 3,447 publications

References 48 publications

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances

An Integration STATCOM PWM Improved Approach to Control Stability in Wind Power System

Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter

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