ARTIFICIAL INTELLIGENCE APPLIED TO INTELLIGENT LOAD DISPATCH IN PHOTOVOLTAIC SYSTEMS: A SYSTEMATIC REVIEW WITH APPLIED ANALYSIS

• DOI: https://doi.org/10.22533/at.ed.8208162614013

• Palavras-chave: -

• Keywords: Artificial Intelligence. Intelligent Load Dispatch. Photovoltaic Systems. Energy Management. Systematic Review.

• Abstract: The increasing penetration of photovoltaic systems into the energy matrix has intensified challenges related to efficient energy management, particularly due to generation intermittency and variability in electrical demand. In this context, intelligent load dispatch plays a fundamental role in decision-making regarding local consumption of generated energy, storage in battery systems, or injection of surplus energy into the electrical grid. This article investigates the application of Artificial Intelligence techniques to load dispatch in photovoltaic systems, focusing on adaptive and data-driven decision strategies. The study is conducted through a systematic literature review, covering recent publications that employ machine learning algorithms, reinforcement learning, artificial neural networks, and fuzzy logic for energy management. The adopted methodology involves rigorous selection of studies, classification of the identified approaches, and comparative analysis of methods considering system architectures and energy performance metrics. As an additional contribution, a conceptual framework for intelligent load dispatch is proposed, integrating photovoltaic generation, loads, energy storage systems, and artificial intelligence algorithms, aiming to optimize energy efficiency and enhance operational reliability. The results indicate that artificial intelligence-based approaches outperform traditional load dispatch methods.