001469949 000__ 03914cam\\22006377a\4500
001469949 001__ 1469949
001469949 003__ OCoLC
001469949 005__ 20230803003354.0
001469949 006__ m\\\\\o\\d\\\\\\\\
001469949 007__ cr\un\nnnunnun
001469949 008__ 230624s2023\\\\sz\\\\\\o\\\\\000\0\eng\d
001469949 019__ $$a1385447850
001469949 020__ $$a9783031291005$$q(electronic bk.)
001469949 020__ $$a303129100X$$q(electronic bk.)
001469949 020__ $$z3031290992
001469949 020__ $$z9783031290992
001469949 0247_ $$a10.1007/978-3-031-29100-5$$2doi
001469949 035__ $$aSP(OCoLC)1385454934
001469949 040__ $$aEBLCP$$beng$$cEBLCP$$dYDX$$dGW5XE$$dEBLCP$$dOCLCF
001469949 049__ $$aISEA
001469949 050_4 $$aTK3091
001469949 08204 $$a621.319$$223/eng/20230628
001469949 1001_ $$aXie, Le.
001469949 24510 $$aData science and applications for modern power systems /$$cLe Xie, Yang Weng, Ram Rajagopal.
001469949 260__ $$aCham :$$bSpringer,$$c2023.
001469949 300__ $$a1 online resource (446 p.).
001469949 336__ $$atext$$btxt$$2rdacontent
001469949 337__ $$acomputer$$bc$$2rdamedia
001469949 338__ $$aonline resource$$bcr$$2rdacarrier
001469949 4901_ $$aPower Electronics and Power Systems
001469949 500__ $$aDescription based upon print version of record.
001469949 5050_ $$aBig Data Challenges in Power Systems -- Challenges and Opportunities in Utility Data -- Wholesale Markets Data Deluge -- Distribution System Data Operation -- Synchrophasor Data Analytics -- Smart Meter and its Implications -- Deep Learning in Power Markets -- Data-driven Planning in Electric Energy Systems -- Common Information Model for Unifying Data Sets -- Inference and Business for Aggregators Non-intrusive Load Monitoring -- Utility Business Model in the Era of Big Data -- Data Security Services for Utilities.
001469949 506__ $$aAccess limited to authorized users.
001469949 520__ $$aThis book offers a comprehensive collection of research articles that utilize datain particular large data setsin modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid. Presents a comprehensive review of data sciences for the power industry; Contains state-of-the-art research articles; Provides practical algorithms and case studies.
001469949 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 28, 2023).
001469949 650_0 $$aElectric power distribution$$xData processing.
001469949 650_0 $$aBig data.
001469949 655_0 $$aElectronic books.
001469949 7001_ $$aWeng, Yang.
001469949 7001_ $$aRajagopal, Ram.
001469949 77608 $$iPrint version:$$aXie, Le$$tData Science and Applications for Modern Power Systems$$dCham : Springer International Publishing AG,c2023$$z9783031290992
001469949 830_0 $$aPower electronics and power systems (Springer)
001469949 852__ $$bebk
001469949 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-29100-5$$zOnline Access$$91397441.1
001469949 909CO $$ooai:library.usi.edu:1469949$$pGLOBAL_SET
001469949 980__ $$aBIB
001469949 980__ $$aEBOOK
001469949 982__ $$aEbook
001469949 983__ $$aOnline
001469949 994__ $$a92$$bISE