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Low Voltage Grid Operation Scheduling Considering Forecast Uncertainty

Comunicació presentada a: 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)

A model for day-ahead scheduling of batteries and branch switches in the low voltage grid, considering forecasts uncertainties, is proposed. The objective is to reduce the energy losses of the distribution lines and avoid critical events such as congestions or over and under-voltages in the local network. Simulations of different day-ahead situations are performed with a modified particle swarm optimisation algorithm. The results show that critical events are avoided and energy self-consumption within the local network is increased

This work has been developed under the European project RESOLVD of the Horizon 2020 research and innovation program (topic LCE-01-2016-2017) and grant agreement N773715

© Martínez Álvarez F., Troncoso Lora A., Sáez Muñoz J., Quintián H., Corchado E. (eds). 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019): SOCO 2019. (Advances in Intelligent Systems and Computing, vol. 950), p. 493-502

Springer

Author: Ferrer, Albert
Torrent-Fontbona, Ferran
Colomer Llinàs, Joan
Meléndez i Frigola, Joaquim
Abstract: Comunicació presentada a: 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)
A model for day-ahead scheduling of batteries and branch switches in the low voltage grid, considering forecasts uncertainties, is proposed. The objective is to reduce the energy losses of the distribution lines and avoid critical events such as congestions or over and under-voltages in the local network. Simulations of different day-ahead situations are performed with a modified particle swarm optimisation algorithm. The results show that critical events are avoided and energy self-consumption within the local network is increased
This work has been developed under the European project RESOLVD of the Horizon 2020 research and innovation program (topic LCE-01-2016-2017) and grant agreement N773715
Format: application/pdf
Citation: https://doi.org/10.1007/978-3-030-20055-8_47
ISBN: 978-3-030-20054-1 (versió paper)
978-3-030-20055-8 (versió electrònica)
Document access: http://hdl.handle.net/10256/16678
Language: eng
Publisher: Springer
Collection: Versió postprint del document publicat a: https://doi.org/10.1007/978-3-030-20055-8_47
Contribucions a Congressos (D-EEEiA)
info:eu-repo/grantAgreement/EC/H2020/773715
Is part of: © Martínez Álvarez F., Troncoso Lora A., Sáez Muñoz J., Quintián H., Corchado E. (eds). 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019): SOCO 2019. (Advances in Intelligent Systems and Computing, vol. 950), p. 493-502
Rights: Tots els drets reservats
Subject: Baixa tensió -- Congressos
Low voltage systems -- Congresses
Enginyeria elèctrica -- Congressos
Electrical engineering -- Congresses
Energia -- Emmagatzematge -- Congressos
Energy storage -- Congresses
Title: Low Voltage Grid Operation Scheduling Considering Forecast Uncertainty
Type: info:eu-repo/semantics/conferenceObject
Repository: DUGiDocs

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