Optimized integration of renewable energy sources using seven-level converter controlled by ANFIS-CS-GWO
•The proposed FLRES-SLC system effectively integrates SPV, wind, fuel cell, and tidal power sources, leveraging their complementary nature to enhance overall energy reliability and sustainability.•The use of an ANFIS fine-tuned by CS-GWO provides an advanced control mechanism that significantly impr...
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Veröffentlicht in: | e-Prime 2024-09, Vol.9, p.100689, Article 100689 |
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Sprache: | eng |
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Zusammenfassung: | •The proposed FLRES-SLC system effectively integrates SPV, wind, fuel cell, and tidal power sources, leveraging their complementary nature to enhance overall energy reliability and sustainability.•The use of an ANFIS fine-tuned by CS-GWO provides an advanced control mechanism that significantly improves system stability, response time, and efficiency.•The seven-level converter system ensures a robust voltage profile and markedly reduces THD, resulting in higher quality and cleaner power delivery suitable for sensitive electrical equipment.•The novel control strategy reduces FST, thereby enhancing the system's ability to quickly recover from disturbances and maintain reliable power supply under varying operational conditions.
The global energy landscape is undergoing a significant transformation, driven by the need to reduce greenhouse gas emissions, enhance energy security, and provide sustainable and clean power solutions. Renewable energy sources (RES) such as Solar Photovoltaic (SPV), wind, fuel cells, and tidal power play a crucial role in this transition due to their abundant availability and low environmental impact. However, integrating these diverse energy sources into power systems requires advanced control strategies to ensure stability, efficiency, and reliability. Existing systems, however, face significant challenges such as unstable voltage profiles, prolonged fault settling time (FST), and high total harmonic distortion (THD), which compromise their efficiency and reliability. To overcome these limitations, a novel methodology is proposed, integrating Solar PV (SPV), wind, fuel cell, and tidal energy sources into a seven-level converter (SLC) system, which is named as Four Level RES based SLC (FLRES-SLC) system. This system is managed by an Adaptive Neuro-Fuzzy Inference System (ANFIS), fine-tuned by Cuckoo Search adopted Grey Wolf Optimizer (CS-GWO). This hybrid control strategy ensures a robust voltage profile, significantly reduces FST, and lowers THD, thereby markedly improving the overall performance of the converter system. The innovative approach offers a reliable and efficient solution for modern power systems, enhancing their integration with diverse RES and ensuring high-quality power delivery. |
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ISSN: | 2772-6711 2772-6711 |
DOI: | 10.1016/j.prime.2024.100689 |