Bio-Inspired Strategies for Minimizing Distortion in DC-AC Converters
DOI:
https://doi.org/10.53591/easi.v2i2.2654Keywords:
Efficiency improvement, Renewable energy systems, Bio-inspired optimization, Power convertersAbstract
The global shift towards sustainable energy sources, such as solar and wind power, underscores the critical role of power converters in renewable energy systems. These converters are essential in the process of converting direct current (DC) generated from renewable sources into alternating current (AC), suitable for use in homes and distribution through the grid. The efficiency and performance of these converters have far-reaching implications for the effective integration of renewable energy into the existing grid infrastructure. However, conventional control methods often fall short in optimizing DC-AC converters to adapt dynamically to changing environmental conditions and varying load demands. This letter aims to provide a holistic view of research on bio-inspired optimization strategies and their impact on minimizing distortion, maximizing efficiency, and enhancing the overall reliability of DC-AC converters within renewable energy systems
References
Owusu, P. A., & Asumadu-Sarkodie, S. (2016). A review of renewable energy sources, sustainability issues and climate change mitigation. Cogent Eng, 3(1). https://doi.org/10.1080/23311916.2016.1167990
Tomin, N., et al. (2022). Design and optimal energy management of community microgrids with flexible renewable energy sources. Renew Energy, 183, 903–921. https://doi.org/10.1016/J.RENENE.2021.11.024
Pop, C. B., et al. (2022). Review of bio-inspired optimization applications in renewable-powered smart grids: Emerging population-based metaheuristics. Energy Reports, 8, 11769–11798. https://doi.org/10.1016/J.EGYR.2022.09.025
Faris, H., Aljarah, I., Al-Betar, M. A., & Mirjalili, S. (2018). Grey wolf optimizer: A review of recent variants and applications. Neural Comput Appl, 30(2), 413–435. https://doi.org/10.1007/S00521-017-3272-5/FIGURES/9
Aguila-Leon, J., Vargas-Salgado, C., Chiñas-Palacios, C., & Díaz-Bello, D. (2023a). Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms. Expert Syst Appl, 211, 118700. https://doi.org/10.1016/J.ESWA.2022.118700
Águila-León, J., Lucero-Tenorio, M., Díaz-Bello, D., Vargas-Salgado, C., & Vega-Gómez, C. (2023b). Bio-inspired Multiobjective Optimization Approach for Total Harmonic Distortion Reduction in a DC-AC Power Converter. In 2023 IEEE Conference on Technologies for Sustainability, SusTech 2023 (pp. 80–85). https://doi.org/10.1109/SUSTECH57309.2023.10129638
Kummara, V. G. R., et al. (2019). A Comprehensive Review of DC–DC Converter Topologies and Modulation Strategies with Recent Advances in Solar Photovoltaic Systems. Electronics, 9(1), 31. https://doi.org/10.3390/ELECTRONICS9010031
Aguila-Leon, J., Chiñas-Palacios, C., Vargas-Salgado, C., Hurtado-Perez, E., & Garcia, E. X. M. (2021). Particle swarm optimization, genetic Algorithm and grey Wolf optimizer algorithms performance comparative for a DC-DC boost converter PID controller. Advances in Science, Technology and Engineering Systems, 6(1), 619–625. https://doi.org/10.25046/aj060167
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Miriam Lucero-Tenorio, Jesus Aguila-Leon
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)