Computational System for Sizing Wind Energy Generation Systems Using Artificial Neural Networks

Rafael Gil Ferques, C. E. C. Nogueira, A. M. Meneghetti and D. M. Rocha

Journal of Agricultural Science, 2024, vol. 10, issue 10, 423

Abstract: The objective of this work was to develop a computational application for the design of wind power generation systems in small-scale On-Grid and Off-Grid installations, using a user friendly and interactive process. Using artificial intelligence concepts in conjunction with genetic algorithms, to verify the technical and economic viability of the implementation of the wind power generation system. The application coding was done using the languages Java, C, C++ and the database in MySQL language, containing technical specifications and costs of components of a wind system (of this type of system). For the development of neural networks and genetic algorithms, the Encog library was used. The application has proven effective in designing and economic analysis of small wind systems, allowing fast and simple simulation of On-Grid systems and Off-Grid systems. In addition, it proved effective in storing and accessing the information regarding the simulations performed and in the comparison between them, in order to perform a new simulation. Also, it was reliable in the accomplishment of the economic analysis, returning in a clear form the feasibility or not of the implantation of the project.

Date: 2024
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