Volume 8 • Issue 1 • PP: 01–05 • 2024
An AI-Based System for Predicting Renewable Energy Power Output Using Advanced Optimization Algorithms
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© 2024 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Accurate forecasting of renewable energy source (RES) generation is increasingly important for effective grid operation and energy management as RES are integrated into electrical grids. Machine learning (ML) and deep learning (DL) algorithms can learn complex relationships from data and provide forecasts, addressing limitations of traditional approaches. This review examines the state of the art and future directions in ML- and DL-based renewable energy forecasting. It surveys the approaches and models used to predict renewable generation and highlights challenges including output uncertainty and variability, data accessibility, and model interpretability. Developing accurate and dependable forecasting models is essential to support the transition to sustainable energy and the integration of RES into electrical grids.
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