Day‐ahead scheduling of a hybrid renewable energy system based on generation forecasting using a deep‐learning approach

Day‐ahead scheduling of a hybrid renewable energy system based on generation forecasting using a deep‐learning approach

Abstract A significant amount of electricity in numerous regions worldwide is used for lighting roads, squares, and other public spaces. Renewable energy can contribute notably to electricity usage for public lighting. This paper focuses on the day‐ahead scheduling of a hybrid renewable energy syste...

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Bibliographic Details
Main Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Dimitra Pappa, Vasilis Pitsilis, Constantinos Makropoulos, Konstantinos Manolitsis
Format: Article
Language:English
Published: Wiley 2023-05-01
Series:Energy Science & Engineering
Subjects:
day‐ahead scheduling
generation forecasting
hybrid renewable energy system
long short‐term memory
Online Access:https://doi.org/10.1002/ese3.1413

Internet

https://doi.org/10.1002/ese3.1413

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