A Novel Fuzzy-COVID Optimization Algorithm for Enhancing Energy Efficiency and Stability in Renewable Smart Grids
DOI:
https://doi.org/10.21070/jeeeu.v10i1.1745Keywords:
Fuzzy Logic Controller, COVID Optimization Algorithm, Renewable Smart Grid, Energy Efficiency, System StabilityAbstract
General Background The integration of multiple renewable energy sources into smart grids requires advanced control strategies to maintain efficient and stable operation under dynamic conditions. Specific Background Hybrid smart grids combining photovoltaic, wind turbine, fuel cell, and microhydro systems with battery storage present challenges in frequency and voltage regulation due to load variability and resource uncertainty. Knowledge Gap Conventional optimization approaches such as genetic algorithms and particle swarm optimization face limitations in achieving adaptive control and global parameter tuning simultaneously. Aims This study proposes a novel hybrid control approach using a Fuzzy Logic Controller integrated with the COVID Optimization Algorithm to address these challenges. Results Simulation results in MATLAB/Simulink indicate improvements of 15–20% in system stability and 12% in energy storage efficiency, alongside reduced frequency deviation (±0.18 Hz), minimized voltage fluctuation (±0.03 p.u.), and improved battery state-of-charge management compared to conventional methods. Novelty The integration of fuzzy logic control with the COVID Optimization Algorithm introduces a new optimization framework for adaptive parameter tuning in hybrid renewable energy systems. Implications The proposed method supports the development of reliable and flexible smart grid systems, contributing to sustainable energy management and improved operational performance in renewable-based power networks.
Highlight:
- Hybrid control method achieves notable gains in operational robustness under fluctuating conditions
- Optimization approach improves storage utilization and regulation accuracy
- Simulation confirms superior performance compared to genetic and swarm-based techniques
Keyword: Fuzzy Logic Controller, COVID Optimization Algorithm, Renewable Smart Grid, Energy Efficiency, System Stability
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