001444361 000__ 03840cam\a2200589\a\4500
001444361 001__ 1444361
001444361 003__ OCoLC
001444361 005__ 20230310003706.0
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001444361 008__ 220212s2022\\\\si\\\\\\ob\\\\000\0\eng\d
001444361 019__ $$a1296166739$$a1296265583
001444361 020__ $$a9789811689659$$q(electronic bk.)
001444361 020__ $$a9811689652$$q(electronic bk.)
001444361 020__ $$z9811689644
001444361 020__ $$z9789811689642
001444361 0247_ $$a10.1007/978-981-16-8965-9$$2doi
001444361 035__ $$aSP(OCoLC)1296427254
001444361 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dYDX$$dGW5XE$$dN$T$$dOCLCO$$dOCLCF$$dOCLCQ$$dIAC$$dOCLCQ$$dSFB$$dUKAHL$$dOCLCQ$$dSEA
001444361 049__ $$aISEA
001444361 050_4 $$aHD9502.A2
001444361 08204 $$a333.79$$223
001444361 1001_ $$aLiu, Hui,$$d1983-
001444361 24510 $$aBig data in energy economics /$$cHui Liu, Nikolaos Nikitas, Yanfei Li, Rui Yang.
001444361 260__ $$aSingapore :$$bSpringer,$$c2022.
001444361 300__ $$a1 online resource (275 pages)
001444361 336__ $$atext$$btxt$$2rdacontent
001444361 337__ $$acomputer$$bc$$2rdamedia
001444361 338__ $$aonline resource$$bcr$$2rdacarrier
001444361 4901_ $$aManagement for professionals
001444361 504__ $$aIncludes bibliographical references.
001444361 5050_ $$aPreface -- Chapter 1 Introduction -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 3 Big Data Analysis of Energy Economics in Coal Market -- Chapter 4 Big Data Analysis of Energy Economics in Wind Power Market -- Chapter 5 Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market -- Chapter 6 Big Data Analysis of Power Market Energy Economics -- Chapter 7 Big Data Management of Smart City Energy Conservation and Emission Reduction -- Chapter 8 Optimization Analysis of Clean Energy Transformation -- Chapter 9 Global Energy Internet Green and Low-Carbon Energy Economic Innovation.
001444361 506__ $$aAccess limited to authorized users.
001444361 520__ $$aThis book combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and costbenefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure. This book provides an important reference for professionals in related fields such as smart energy, smart economy, energy Internet, artificial intelligence, energy economics and policy.
001444361 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 23, 2022).
001444361 588__ $$aDescription based on print version record.
001444361 650_0 $$aPower resources$$xEconomic aspects.
001444361 650_0 $$aBig data.
001444361 650_6 $$aRessources énergétiques$$xAspect économique.
001444361 650_6 $$aDonnées volumineuses.
001444361 655_0 $$aElectronic books.
001444361 7001_ $$aNikitas, Nikolaos.
001444361 7001_ $$aLi, Yanfei.
001444361 7001_ $$aYang, Rui.
001444361 77608 $$iPrint version:$$aLiu, Hui.$$tBig Data in Energy Economics.$$dSingapore : Springer Singapore Pte. Limited, ©2022$$z9789811689642
001444361 830_0 $$aManagement for professionals.
001444361 852__ $$bebk
001444361 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-8965-9$$zOnline Access$$91397441.1
001444361 909CO $$ooai:library.usi.edu:1444361$$pGLOBAL_SET
001444361 980__ $$aBIB
001444361 980__ $$aEBOOK
001444361 982__ $$aEbook
001444361 983__ $$aOnline
001444361 994__ $$a92$$bISE