Energy Management in Hybrid Renewable Systems
DOI:
https://doi.org/10.53591/easi.v2i2.2535Keywords:
Renewable Energy, Efficient Energy Management, Hybrid SystemsAbstract
This document focuses on the analysis of solutions to the need to design the feeding system of a modular and mobile installation in charge of monitoring the water quality of a river. This problem, arising from the proposal of a research project of the Ministry of Science and Innovation of the Government of Spain, aims to supply the consumption caused by both the water acquisition system, thermal conditioning of the facility, electronics, and instrumentation, as well as such as telecommunications equipment to upload measurements to the cloud.
References
Casteleiro-Roca, J. L., Chamoso, P., Jove, E., González-Briones, A., Quintián, H., Fernández-Ibáñez, M. I., ... & Calvo-Rolle, J. L. (2020). Solar thermal collector output temperature prediction by hybrid intelligent model for smartgrid and smartbuildings applications and optimization. Applied Sciences, 10(13), 4644. https://doi.org/10.3390/app10134644
Deshmukh, M. K., & Deshmukh, S. S. (2008). Modeling of hybrid renewable energy systems. Renewable and sustainable energy reviews, 12(1), 235-249. https://doi.org/10.1016/j.rser.2006.07.011
Manwell, J. F. (2004). Hybrid energy systems. En: Encyclopaedia of energy, 3(2004), 215-229. https://doi.org/10.1016/B0-12-176480-X/00360-0
Porras, S., Jove, E., Baruque, B., & Calvo-Rolle, J. L. (2023). A comparative analysis of intelligent techniques to predict energy generated by a small wind turbine from atmospheric variables. Logic Journal of the IGPL, 31(4), 648-663. https://doi.org/10.1093/jigpal/jzac031
Zayas-Gato, F., Jove, E., Casteleiro-Roca, J. L., Quintián, H., Pérez-Castelo, F. J., Piñón-Pazos, A., ... & Calvo-Rolle, J. L. (2023). Intelligent model for active power prediction of a small wind turbine. Logic Journal of the IGPL, 31(4), 785-803. https://doi.org/10.1093/jigpal/jzac040
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Esteban Jove, Antonio Díaz-Longueira, Paula Arcano-Bea, Míriam Timiraos, Álvaro Michelena, Francisco Zayas-Gato, Héctor Quintián, José-Luis Casteleiro-Roca, José Luis Calvo-Rolle
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Contributions published in EASI journal follows the open access license CC BY-NC-ND 4.0 (Creative Commons Attribution-NonCommercial-NoDerivs 4.0). This license empowers you as an author and ensures wide dissemination of your research while still protecting your rights.
For authors:
- Authors retain copyrights without restrictions.
- The Journal obtains a license to publish the first original manuscript.
For readers/users:
Free access and distribution: Anyone can access, download, copy, print, and share the published article freely according to the license CC BY-NC-ND 4.0 terms.
Attribution required: If any third party use the published material, they must give credit to the creator by providing the name, article title, and journal name, ensuring the intellectual property of the author(s), and helps to build the scholarly reputation.
Non-commercial use: only noncommercial use of the published work is permitted. Noncommercial means not primarily intended for or directed towards commercial advantage or monetary compensation by any third party.
No modifications allowed: The content of the published article cannot be changed, remixed, or rebuilt upon the author’s work. This ensures the integrity and accuracy of the research findings.
We encourage you to familiarize yourself with the full license terms:
Attributions:
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
Definitions, scope, and license terms:
https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.en
By publishing under CC BY-NC-ND 4.0, authors contribute to the advancement of scientific knowledge while retaining control over their work. If you have any questions, please don't hesitate to contact the journal editors.
Estadística (Statistics)