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245 0 0 _aAdvanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems
_cFouzi Harrou, Ying Sun.
020 _a9781838805463
024 8 _ahttp://dx.doi.org/10.5772/intechopen.85999
029 1 _ahttps://library.biblioboard.com/ext/api/media/f5aaa381-0876-428d-8991-f2ae3f6061bd/assets/thumbnail.jpg
040 _aScCtBLL
_cScCtBLL
506 0 _aAccess copy available to the general public.
_fUnrestricted
_2star
700 1 _aHarrou, Fouzi
_eeditor.
700 1 _aSun, Ying
_eeditor.
264 1 _bIntechOpen,
300 _a1 online resource (1 p.)
520 _aFault detection, control, and forecasting have a vital role in renewable energy systems (Photovoltaics (PV) and wind turbines (WTs)) to improve their productivity, ef?ciency, and safety, and to avoid expensive maintenance. For instance, the main crucial and challenging issue in solar and wind energy production is the volatility of intermittent power generation due mainly to weather conditions. This fact usually limits the integration of PV systems and WTs into the power grid. Hence, accurately forecasting power generation in PV and WTs is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. Also, accurate and prompt fault detection and diagnosis strategies are required to improve efficiencies of renewable energy systems, avoid the high cost of maintenance, and reduce risks of fire hazards, which could affect both personnel and installed equipment. This book intends to provide the reader with advanced statistical modeling, forecasting, and fault detection techniques in renewable energy systems.
588 0 _aDescription based on print version record.
590 _aIntechOpen Engineering 2019 - 2021
650 7 _aTechnology & Engineering / Power Resources / Alternative & Renewable
_2bisacsh
650 0 _aTechnology
655 0 _aElectronic books.
758 _iIs found in:
_aKnowledge Unlatched
_1https://openresearchlibrary.org/module/2774bc74-146a-484f-a7ba-ab1d6a09bbfb
856 4 0 _uhttps://openresearchlibrary.org/content/f5aaa381-0876-428d-8991-f2ae3f6061bd
_zView this content on Open Research Library.
_70
999 _c32853
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