Optimization of renewable energy integration in electrical systems using a genetic algorithm.

Authors

  • Franco Zanek Universidad Nacional de Salta, Argentina

DOI:

https://doi.org/10.56124/encriptar.v7i13.001%20

Keywords:

Energy optimization, Genetic Algorithm, Renewable Energy Systems

Abstract

This study presents a theoretical model that introduces a hybrid method for the effective integration of renewable energies into electrical systems, combining initial value simulation with the Genetic Algorithm metaheuristic. Current optimization strategies are examined, highlighting the challenges and opportunities associated with optimizing sustainable energy systems. The primary objective of this proposal is to define a model that maximizes the incorporation of renewable energies and minimizes dependence on fossil fuels in electricity generation, thus promoting the transition to a cleaner, more diversified, and efficient energy matrix. The implications of this approach for such a transition are addressed, emphasizing the need to develop mathematical models capable of simulating and optimizing large-scale energy systems, progressively replacing fossil fuel-based technologies with renewable sources. This strategy offers promising prospects for the planning and operation of sustainable energy systems, as evidenced by the results obtained from validating the model with data focused on the City of Salta, Argentina.

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Published

2024-06-28

How to Cite

Zanek, F. (2024). Optimization of renewable energy integration in electrical systems using a genetic algorithm. Scientific Journal of Informatics ENCRYPT - ISSN: 2737-6389., 7(13), 1–20. https://doi.org/10.56124/encriptar.v7i13.001