Using analogs ensembles and genetic algorithm to handle uncertainty in a microgrid
| Autor: | Calderon-Obaldia, Fausto, Migan-Dubois, Anne, Badosa, Jordi, Bourdin, Vincent |
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| Přispěvatelé: | Migan, Anne, Laboratoire Génie électrique et électronique de Paris (GeePs), CentraleSupélec-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Universidad de Costa Rica (UCR), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Design
analogs ensemble microgrids energy management system [SPI.NRJ]Engineering Sciences [physics]/Electric power battery management [PHYS.COND.CM-MS] Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci] [SPI.TRON] Engineering Sciences [physics]/Electronics [SPI.TRON]Engineering Sciences [physics]/Electronics Operation and Performance Subtopic 3: Operation PV Systems and Storage -Modelling [PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci] genetic algorithm Performance and Maintenance of PV Systems uncertainty [SPI.NRJ] Engineering Sciences [physics]/Electric power |
| Zdroj: | 37th European Photovoltaic Solar Energy Conference and Exhibition (Eu-PVSEC) 37th European Photovoltaic Solar Energy Conference and Exhibition (Eu-PVSEC), Sep 2020, Lisbon, Portugal |
| Popis: | International audience; In this work, a novel approach to deal with the PV forecast uncertainty during the energy management of a microgrid is presented. A novel adaptation of an analogs ensembles method allows to obtain a Sharpness indicator that is correlated with the PV forecast uncertainty. This indicator can be used to dynamically restrict the usable battery capacity when doing the day-ahead optimal scheduling using a genetic algorithm. This permits to deal with the PV uncertainty internally within the microgrid. This gives a total certainty to the grid operator about the power needs of the microgrid one day in advance. In this way, in a big scale, the uncertainty caused by a higher penetration of renewable energy sources in the national grid could be highly reduced. The main results of a real study-case are presented and the limitations of the method for its implementation are also discussed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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