AI-Based Optimization of Renewable Energy Systems for Grid Stability
DOI:
https://doi.org/10.65405/.v10i37.608Keywords:
Renewable energy, Grid stability, Artificial intelligence, Optimization, LibyaAbstract
The increasing penetration of renewable energy sources such as solar and wind into power
systems has created new challenges for grid stability and reliability, especially in countries facing
frequent power outages like Libya. This study proposes the use of Artificial Intelligence (AI)
techniques to optimize the operation and management of renewable energy systems. Machine
learning algorithms are applied for short-term forecasting of solar irradiance and wind speed,
while optimization models are developed for intelligent scheduling of hybrid renewable sources
and storage systems. The proposed approach aims to minimize fluctuations, reduce reliance on
fossil fuels, and improve overall grid stability. Simulation results demonstrate that AI-based
optimization can enhance the efficiency and reliability of renewable energy integration, making it a
promising solution for sustainable energy development in Libya.
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