Ensemble Forecasting Applied to Power Systems
Modern 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 managi...
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| Egile Nagusiak: | , |
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| Formatua: | Online |
| Hizkuntza: | ingelesa |
| Argitaratua: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Gaiak: | |
| Sarrera elektronikoa: | 44795 |
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| _version_ | 1869516362181771264 |
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| author | Bracale, Antonio Falco, Pasquale De |
| author_browse | Bracale, Antonio Falco, Pasquale De |
| author_facet | Bracale, Antonio Falco, Pasquale De |
| author_sort | Bracale, Antonio |
| collection | Directory of Open Access Books |
| description | Modern 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. |
| format | Online |
| id | doab-20.500.12854ir-46473 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-464732024-04-11T15:11:27Z Ensemble Forecasting Applied to Power Systems Bracale, Antonio Falco, Pasquale De TA1-2040 T1-995 forecast combination solar energy electricity price forecasting calibration window heuristic algorithm deep learning electric load forecasting smart grids hierarchical load forecasting predictive distribution solar PV solar farm microgrid energy management lower and upper bound estimation solar power prediction interval prediction kernel density estimation average probability forecast probabilistic forecasting forecasting distributed energy resources photovoltaic power conditional predictive ability clearness index Fourier series combining forecasts weather station combination distributed generation clear sky index extreme learning machine ensemble methods pinball score autoregression thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Modern 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. 2021-02-11T12:37:31Z 2021-02-11T12:37:31Z 2020-04-07 23:07:09 2020 book 44795 9783039283132 9783039283125 https://directory.doabooks.org/handle/20.500.12854/46473 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/2072 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-313-2 10.3390/books978-3-03928-313-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039283132 9783039283125 134 open access |
| spellingShingle | TA1-2040 T1-995 forecast combination solar energy electricity price forecasting calibration window heuristic algorithm deep learning electric load forecasting smart grids hierarchical load forecasting predictive distribution solar PV solar farm microgrid energy management lower and upper bound estimation solar power prediction interval prediction kernel density estimation average probability forecast probabilistic forecasting forecasting distributed energy resources photovoltaic power conditional predictive ability clearness index Fourier series combining forecasts weather station combination distributed generation clear sky index extreme learning machine ensemble methods pinball score autoregression thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Bracale, Antonio Falco, Pasquale De Ensemble Forecasting Applied to Power Systems |
| title | Ensemble Forecasting Applied to Power Systems |
| title_full | Ensemble Forecasting Applied to Power Systems |
| title_fullStr | Ensemble Forecasting Applied to Power Systems |
| title_full_unstemmed | Ensemble Forecasting Applied to Power Systems |
| title_short | Ensemble Forecasting Applied to Power Systems |
| title_sort | ensemble forecasting applied to power systems |
| topic | TA1-2040 T1-995 forecast combination solar energy electricity price forecasting calibration window heuristic algorithm deep learning electric load forecasting smart grids hierarchical load forecasting predictive distribution solar PV solar farm microgrid energy management lower and upper bound estimation solar power prediction interval prediction kernel density estimation average probability forecast probabilistic forecasting forecasting distributed energy resources photovoltaic power conditional predictive ability clearness index Fourier series combining forecasts weather station combination distributed generation clear sky index extreme learning machine ensemble methods pinball score autoregression thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TA1-2040 T1-995 forecast combination solar energy electricity price forecasting calibration window heuristic algorithm deep learning electric load forecasting smart grids hierarchical load forecasting predictive distribution solar PV solar farm microgrid energy management lower and upper bound estimation solar power prediction interval prediction kernel density estimation average probability forecast probabilistic forecasting forecasting distributed energy resources photovoltaic power conditional predictive ability clearness index Fourier series combining forecasts weather station combination distributed generation clear sky index extreme learning machine ensemble methods pinball score autoregression thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | 44795 |
| work_keys_str_mv | AT bracaleantonio ensembleforecastingappliedtopowersystems AT falcopasqualede ensembleforecastingappliedtopowersystems |