000			03939nam a22004215i 4500
988			_aSpringer_Engineering_2020
999			_c116862 _d116862 _x1
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008			190928s2020 si | s |||| 0|eng d
020			_a9789811502750
024	7		_a10.1007/978-981-15-0275-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK1541 _b2020 EB
100	1		_aS. Dhiman, Harsh _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9672033
245	1	0	_aDecision and Control in Hybrid Wind Farms _cby Harsh S. Dhiman, Dipankar Deb.
250			_a1st ed. 2020.
264		1	_aSingapore _bSpringer Singapore _c2020.
300			_a1 recurso en línea (XXII, 140 páginas) _b64 ilustraciones, 62 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aStudies in Systems Decision and Control _x2198-4182 _v253
490	0		_aEngineering (Springer-11647)
505	0		_aFundamentals of Wind Turbine and Wind Farm Control Systems -- Multi-Criteria Decision Making: An Overview -- Decision Making in Hybrid Wind Farms -- Fuzzy based Decision Making in Hybrid Wind Farms -- Control Applications in Hybrid Wind Farms -- BESS Life Enhancement for Hybrid Wind Farms.
520			_aThis book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint.
650		7	_2embne _9139499 _aCentrales eólicas
700	1		_aDeb, Dipankar _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9670825
776	0	8	_iPrinted edition: _z9789811502743
776	0	8	_iPrinted edition: _z9789811502767
776	0	8	_iPrinted edition: _z9789811502774
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-0275-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aPRE _cm _dz _feng _ggw _h0