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Hybrid Renewable Energy System Using Cuckoo Firefly Optimization

M. E. Shajini Sheeba1,*, P. Jagatheeswari2

1 Department of EEE, Stella Mary's College of Engineering, Nagercoil, 629202, India
2 Department of EEE, Ponjesly College of Engineering, Nagercoil, 629003, India

* Corresponding Author: M. E. Shajini Sheeba. Email: email

Intelligent Automation & Soft Computing 2022, 34(2), 1141-1156. https://doi.org/10.32604/iasc.2022.024549

Abstract

With abundant and non-polluting benefits in nature, sources of renewable energy have reached vast concentrations. This paper first discusses the number of MPPT (Maximum Power Point Tracking) techniques utilized by wind and photovoltaic (PV) to create hybrid systems for generating wind-PV energy. This hybrid system complements each other day and night to enable continuous power output. Then, a new MPPT technique was proposed to extract maximum power using a newly developed hybrid optimization algorithm, namely the Cukoo Fire Fly method (CFF). The CFF algorithm is derived from the integration of the cuckoo search (CS) algorithm and the Firefly (FF) optimization algorithm. In addition, the proposed system comprises a LUO converter controlled by an integrated proportional controller (PI) which includes control of the power delivered to the load. The LUO converter can increase or decrease power depending on load requirements. The results are compared with Harmony Search Algorithm (HAS), Cuckoo Search (CS) and Firefly (FF). Investigation of the proposed system was carried out on the MATLAB/Simulink platform.

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Cite This Article

M. E. Shajini Sheeba and P. Jagatheeswari, "Hybrid renewable energy system using cuckoo firefly optimization," Intelligent Automation & Soft Computing, vol. 34, no.2, pp. 1141–1156, 2022. https://doi.org/10.32604/iasc.2022.024549



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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