04201nam 22007815 450 991029962640332120200629162825.03-319-12319-X10.1007/978-3-319-12319-6(CKB)3710000000281316(EBL)1967147(OCoLC)895661112(SSID)ssj0001386781(PQKBManifestationID)11824980(PQKBTitleCode)TC0001386781(PQKBWorkID)11374466(PQKB)11687292(MiAaPQ)EBC1967147(DE-He213)978-3-319-12319-6(PPN)183091248(EXLCZ)99371000000028131620141114d2014 u| 0engur|n|---|||||txtccrSpatio-Temporal Data Analytics for Wind Energy Integration /by Lei Yang, Miao He, Junshan Zhang, Vijay Vittal1st ed. 2014.Cham :Springer International Publishing :Imprint: Springer,2014.1 online resource (86 p.)SpringerBriefs in Electrical and Computer Engineering,2191-8112Description based upon print version of record.3-319-12318-1 Includes bibliographical references.Introduction -- A Spatio-Temporal Analysis Approach for Short-Term Forecast of Wind Farm Generation -- Support Vector Machine Enhanced Markov Model for Short-Term Wind Power Forecast -- Stochastic Optimization based Economic Dispatch and Interruptible Load Management -- Conclusions and Future Works.This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic dispatch (ED) and interruptible load management are investigated as well. Spatio-Temporal Data Analytics for Wind Energy Integration is valuable for researchers and professionals working towards renewable energy integration. Advanced-level students studying electrical, computer and energy engineering should also find the content useful.SpringerBriefs in Electrical and Computer Engineering,2191-8112Renewable energy resourcesData miningEnergy policyEnergy and stateEnergy systemsRenewable and Green Energyhttps://scigraph.springernature.com/ontologies/product-market-codes/111000Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Energy Policy, Economics and Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/112000Energy Systemshttps://scigraph.springernature.com/ontologies/product-market-codes/115000Renewable energy resources.Data mining.Energy policy.Energy and state.Energy systems.Renewable and Green Energy.Data Mining and Knowledge Discovery.Energy Policy, Economics and Management.Energy Systems.333.92Yang Leiauthttp://id.loc.gov/vocabulary/relators/aut909422He Miaoauthttp://id.loc.gov/vocabulary/relators/autZhang Junshanauthttp://id.loc.gov/vocabulary/relators/autVittal Vijayauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910299626403321Spatio-Temporal Data Analytics for Wind Energy Integration2162321UNINA