000			02928nam a22003135i 4500
001			239300
003			ES-VaUE
005			20240306114316.0
007			cr nn 008mamaa
008			211108s2021 sz | o |||| 0|eng d
020			_a9783030851286
024	7		_a10.1007/978-3-030-85128-6 _2doi
040			_aES-VaU _bspa _cES-VaU _dES-VaU
050		4	_aT57.6-.97 _b2021 EB
100	1		_aSun, Xu Andy. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	0	0	_aRobust Optimization in Electric Energy Systems _cby Xu Andy Sun, Antonio J Conejo
250			_a1st ed. 2021.
264		1	_aCham _c2021 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aInternational Series in Operations Research & Management Science _x2214-7934 _v313
505	0		_aChapter 1: Decision Making under Uncertainty in the Power Sector -- Chapter 2: Static Robust Optimization -- Chapter 3: Adaptive Robust Optimization -- Chapter 4: Distributionally Robust Optimization -- Chapter 5: Hybrid Adaptive Robust Optimization Models -- Chapter 6: Robust Optimization in Short-Term Power System Operations -- Chapter 7: Medium-Term Planning Models -- Chapter 8: Long-Term Planning Models.
520			_aThis book covers robust optimization theory and applications in the electricity sector. The advantage of robust optimization with respect to other methodologies for decision making under uncertainty are first discussed. Then, the robust optimization theory is covered in a friendly and tutorial manner. Finally, a number of insightful short- and long-term applications pertaining to the electricity sector are considered. Specifically, the book includes: robust set characterization, robust optimization, adaptive robust optimization, hybrid robust-stochastic optimization, applications to short- and medium-term operations problems in the electricity sector, and applications to long-term investment problems in the electricity sector. Each chapter contains end-of-chapter problems, making it suitable for use as a text. The purpose of the book is to provide a self-contained overview of robust optimization techniques for decision making under uncertainty in the electricity sector. The targeted audience includes industrial and power engineering students and practitioners in energy fields. The young field of robust optimization is reaching maturity in many respects. It is also useful for practitioners, as it provides a number of electricity industry applications described up to working algorithms (in JuliaOpt).
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-85128-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Business_2021
999			_c239300 _d239300