000779104 000__ 03207cam\a2200517Mi\4500
000779104 001__ 779104
000779104 005__ 20230306142911.0
000779104 006__ m\\\\\o\\d\\\\\\\\
000779104 007__ cr\nn\nnnunnun
000779104 008__ 170121s2017\\\\nyu\\\\\ob\\\\000\0\eng\d
000779104 019__ $$a972394821$$a972572666$$a974651048$$a981029241$$a981819145
000779104 020__ $$a9781493967681$$q(electronic book)
000779104 020__ $$a1493967681$$q(electronic book)
000779104 020__ $$z9781493967667
000779104 0247_ $$a10.1007/978-1-4939-6768-1$$2doi
000779104 035__ $$aSP(OCoLC)ocn969640309
000779104 035__ $$aSP(OCoLC)969640309$$z(OCoLC)972394821$$z(OCoLC)972572666$$z(OCoLC)974651048$$z(OCoLC)981029241$$z(OCoLC)981819145
000779104 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dIDEBK$$dOCLCF$$dUAB$$dOCLCQ$$dNJR$$dYDX$$dUPM$$dCNCGM$$dVT2$$dIOG
000779104 049__ $$aISEA
000779104 050_4 $$aTK1005
000779104 050_4 $$aQC71.82-73.8
000779104 08204 $$a621.042
000779104 1001_ $$aHuang, Yuping.
000779104 24510 $$aElectrical power unit commitment :$$bdeterministic and two-stage stochastic programming models and algorithms /$$cYuping Huang, Panos M. Pardalos, Qipeng P. Zheng.
000779104 260__ $$aNew York, NY :$$bSpringer,$$c2017.
000779104 300__ $$a1 online resource (98 pages).
000779104 336__ $$atext$$btxt$$2rdacontent
000779104 337__ $$acomputer$$bc$$2rdamedia
000779104 338__ $$aonline resource$$bcr$$2rdacarrier
000779104 347__ $$atext file$$bPDF$$2rda
000779104 4901_ $$aSpringerBriefs in Energy
000779104 504__ $$aIncludes bibliographical references.
000779104 5050_ $$aIntroduction -- Deterministic Unit Commitment Models and Algorithms -- Two-Stage Stochastic Programming Models and Algorithms -- Nomenclature -- Renewable Energy Scenario Generation.
000779104 506__ $$aAccess limited to authorized users.
000779104 520__ $$aThis volume in the SpringerBriefs in Energy series offers a systematic review of unit commitment (UC) problems in electrical power generation. It updates texts written in the late 1990s and early 2000s by including the fundamentals of both UC and state-of-the-art modeling as well as solution algorithms and highlighting stochastic models and mixed-integer programming techniques. The UC problems are mostly formulated as mixed-integer linear programs, although there are many variants. A number of algorithms have been developed for, or applied to, UC problems, including dynamic programming, Lagrangian relaxation, general mixed-integer programming algorithms, and Benders decomposition. In addition the book discusses the recent trends in solving UC problems, especially stochastic programming models, and advanced techniques to handle large numbers of integer- decision variables due to scenario propagation.
000779104 588__ $$aDescription based on print  version record.
000779104 650_0 $$aElectric power$$xMathematical models.
000779104 650_0 $$aDeterminants.
000779104 7001_ $$aPardalos, P. M.$$q(Panos M.),$$d1954-
000779104 7001_ $$aZheng, Qipeng P.
000779104 77608 $$iPrint version:$$aHuang, Yuping.$$tElectrical Power Unit Commitment : Deterministic and Two-Stage Stochastic Programming Models and Algorithms.$$dBoston, MA : Springer US, ©2017$$z9781493967667
000779104 830_0 $$aSpringerBriefs in energy.
000779104 852__ $$bebk
000779104 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-1-4939-6768-1$$zOnline Access$$91397441.1
000779104 909CO $$ooai:library.usi.edu:779104$$pGLOBAL_SET
000779104 980__ $$aEBOOK
000779104 980__ $$aBIB
000779104 982__ $$aEbook
000779104 983__ $$aOnline
000779104 994__ $$a92$$bISE