000			03454nam a22004335i 4500
650		7	_2embne _aRedes neuronales artificiales _9678664
999			_c120679 _d120679
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003			ES-MaUEC
005			20230102114054.0
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007			cr nn nnnaamaa
008			200509s2020 gw a o |||| 0|eng d
020			_a9783030474430
024	7		_a10.1007/978-3-030-47443-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.87 _b2020 EB
100	1		_aSanchez, Edgar N. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/30760887 _9674893
245	1	0	_aNeural Control of Renewable Electrical Power Systems _cby Edgar N. Sánchez, Larbi Djilali.
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2020
300			_a1 recurso en línea (XXV, 206 páginas) _b218 ilustraciones, 208 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aStudies in Systems Decision and Control _x2198-4182 _v278
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aIntroduction -- Mathematical Preliminaries -- Wind System Modeling -- Neural Control Synthesis -- Experimental Results -- Microgrid Control -- Conclusions and Future Work.
520	3		_aThis book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network. It presents modern control algorithms based on neural identification for different renewable energy sources, such as wind power, which uses doubly-fed induction generators, solar power, and battery banks for storage. It then discusses the use of the proposed controllers to track doubly-fed induction generator dynamics references: DC voltage, grid power factor, and stator active and reactive power, and the use of simulations to validate their performance. Further, it addresses methods of testing low-voltage ride-through capacity enhancement in the presence of grid disturbances, as well as the experimental validation of the controllers under both normal and abnormal grid conditions. The book then describes how the proposed control schemes are extended to control a grid-connected microgrid, and the use of an IEEE 9-bus system to evaluate their performance and response in the presence of grid disturbances. Lastly, it examines the real-time simulation of the entire system under normal and abnormal conditions using an Opal-RT simulator.
988			_aSpringer_Robotics_23062020
700	1		_aDjilali, Larbi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9674894
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729
776	0	8	_iPrinted edition: _z9783030474423
776	0	8	_iPrinted edition: _z9783030474447
776	0	8	_iPrinted edition: _z9783030474454
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-47443-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2020 _dz _eIG _zSI