Application of Neural Networks for Predicting Energy Production From Hybrid Power Systems Considering the Influence of Stohastic Weather Changes Cover

.blurhash-client-img { display: none !important; }

Application of Neural Networks for Predicting Energy Production From Hybrid Power Systems Considering the Influence of Stohastic Weather Changes

B&H Electrical Engineering

Volume 18 (2024): Issue 2 (December 2024)

By: Adin Memić, Maja Muftić Dedović, Nedis Dautbašić and Medina Kapo

Open Access

|Dec 2024

Authors

Adin Memić

amemic1@etf.unsa.ba

Faculty of Electrical Engineering University of Sarajevo, Bosnia and Herzegovina

Faculty of Electrical Engineering University of Sarajevo, Bosnia and Herzegovina

Maja Muftić Dedović

Faculty of Electrical Engineering University of Sarajevo, Bosnia and Herzegovina

Nedis Dautbašić

Faculty of Electrical Engineering University of Sarajevo, Bosnia and Herzegovina

Medina Kapo

Faculty of Electrical Engineering University of Sarajevo, Bosnia and Herzegovina

DOI: https://doi.org/10.2478/bhee-2024-0006 | Journal eISSN: 2566-3151 | Journal ISSN: 2566-3143

Journal RSS Feed

Language: English

Submitted on: May 15, 2024

Accepted on: Jul 7, 2024

Published on: Dec 21, 2024

Published by: Bosnia and Herzegovina National Committee CIGRÉ

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

hybrid power plant,

neural network,

machine learning,

renewable sources,

solar power plant,

Related subjects:

Computer sciences,

Computer sciences, other,

Electrical engineering,

Fundamentals of electrical engineering,

Mechanical engineering,

Mechatronics and automotive

© 2024 Adin Memić, Maja Muftić Dedović, Nedis Dautbašić, Medina Kapo, published by Bosnia and Herzegovina National Committee CIGRÉ
This work is licensed under the Creative Commons Attribution 4.0 License.

Previous article Volume 18 (2024): Issue 2 (December 2024)Next article