LEADER 02331nam 2200373 450 001 9910674047203321 005 20230623042429.0 035 $a(CKB)4100000011302139 035 $a(NjHacI)994100000011302139 035 $a(EXLCZ)994100000011302139 100 $a20230623d2020 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aEnsemble Forecasting Applied to Power Systems /$fAntonio Bracale, Pasquale De Falco. editor 210 1$a[Place of publication not identified] :$cMDPI - Multidisciplinary Digital Publishing,$d2020. 215 $a1 online resource (134 pages) 311 $a3-03928-312-X 330 $aModern power systems are affected by many sources of uncertainty, driven by the spread of renewable generation, by the development of liberalized energy market systems and by the intrinsic random behavior of the final energy customers. Forecasting is, therefore, a crucial task in planning and managing modern power systems at any level: from transmission to distribution networks, and in also the new context of smart grids. Recent trends suggest the suitability of ensemble approaches in order to increase the versatility and robustness of forecasting systems. Stacking, boosting, and bagging techniques have recently started to attract the interest of power system practitioners. This book addresses the development of new, advanced, ensemble forecasting methods applied to power systems, collecting recent contributions to the development of accurate forecasts of energy-related variables by some of the most qualified experts in energy forecasting. Typical areas of research (renewable energy forecasting, load forecasting, energy price forecasting) are investigated, with relevant applications to the use of forecasts in energy management systems. 606 $aForecasting$xMethodology 606 $aForecasting$xStudy and teaching 615 0$aForecasting$xMethodology. 615 0$aForecasting$xStudy and teaching. 676 $a303.49 702 $aDe Falco$b Pasquale 702 $aBracale$b Antonio 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910674047203321 996 $aEnsemble Forecasting Applied to Power Systems$93059533 997 $aUNINA