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001440877 001__ 1440877
001440877 003__ OCoLC
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001440877 019__ $$a1285162413$$a1285238904$$a1285257125$$a1285277234$$a1285784778$$a1294368489
001440877 020__ $$a9783030851286$$q(electronic bk.)
001440877 020__ $$a3030851281$$q(electronic bk.)
001440877 020__ $$z9783030851279
001440877 020__ $$z3030851273
001440877 0247_ $$a10.1007/978-3-030-85128-6$$2doi
001440877 035__ $$aSP(OCoLC)1285167874
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001440877 049__ $$aISEA
001440877 050_4 $$aQA402.5
001440877 08204 $$a519.6$$223
001440877 1001_ $$aSun, Xu Andy.
001440877 24510 $$aRobust optimization in electric energy systems /$$cXu Andy Sun, Antonio J. Conejo.
001440877 260__ $$aCham, Switzerland :$$bSpringer,$$c2021.
001440877 300__ $$a1 online resource (337 pages)
001440877 336__ $$atext$$btxt$$2rdacontent
001440877 337__ $$acomputer$$bc$$2rdamedia
001440877 338__ $$aonline resource$$bcr$$2rdacarrier
001440877 347__ $$atext file
001440877 347__ $$bPDF
001440877 4901_ $$aInternational series in operations research and management science ;$$vv. 313
001440877 504__ $$aIncludes bibliographical references and index.
001440877 5050_ $$aChapter 1: Decision Making under Uncertainty in the Power Sector -- Chapter 2: Static Robust Optimization -- Chapter 3: Adaptive Robust Optimization -- Chapter 4: Distributionally Robust Optimization -- Chapter 5: Hybrid Adaptive Robust Optimization Models -- Chapter 6: Robust Optimization in Short-Term Power System Operations -- Chapter 7: Medium-Term Planning Models -- Chapter 8: Long-Term Planning Models.
001440877 506__ $$aAccess limited to authorized users.
001440877 520__ $$aThis book covers robust optimization theory and applications in the electricity sector. The advantage of robust optimization with respect to other methodologies for decision making under uncertainty are first discussed. Then, the robust optimization theory is covered in a friendly and tutorial manner. Finally, a number of insightful short- and long-term applications pertaining to the electricity sector are considered. Specifically, the book includes: robust set characterization, robust optimization, adaptive robust optimization, hybrid robust-stochastic optimization, applications to short- and medium-term operations problems in the electricity sector, and applications to long-term investment problems in the electricity sector. Each chapter contains end-of-chapter problems, making it suitable for use as a text. The purpose of the book is to provide a self-contained overview of robust optimization techniques for decision making under uncertainty in the electricity sector. The targeted audience includes industrial and power engineering students and practitioners in energy fields. The young field of robust optimization is reaching maturity in many respects. It is also useful for practitioners, as it provides a number of electricity industry applications described up to working algorithms (in JuliaOpt).
001440877 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 22, 2021).
001440877 650_0 $$aRobust optimization.
001440877 650_0 $$aElectrical engineering$$xMathematical models.
001440877 650_0 $$aElectric utilities.
001440877 650_6 $$aOptimisation robuste.
001440877 650_6 $$aGénie électrique$$xModèles mathématiques.
001440877 650_6 $$aServices publics d'électricité.
001440877 655_0 $$aElectronic books.
001440877 7001_ $$aConejo, Antonio J.
001440877 77608 $$iPrint version:$$aSun, Xu Andy.$$tRobust Optimization in Electric Energy Systems.$$dCham : Springer International Publishing AG, ©2021$$z9783030851279
001440877 830_0 $$aInternational series in operations research & management science ;$$vv. 313.
001440877 852__ $$bebk
001440877 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-85128-6$$zOnline Access$$91397441.1
001440877 909CO $$ooai:library.usi.edu:1440877$$pGLOBAL_SET
001440877 980__ $$aBIB
001440877 980__ $$aEBOOK
001440877 982__ $$aEbook
001440877 983__ $$aOnline
001440877 994__ $$a92$$bISE