Schematization and Updating of Electrical Protections in a Context of Power Electric System Expansion Planning

The project addresses the obsolescence of electrical protection schemes in the face of expanding power systems with high penetration of renewable energy and storage systems. Current infrastructure, designed under assumptions of topological stability and unidirectional flows, presents critical risks such as undetected faults and erroneous tripping due to the variability of modern grids. The proposed methodology is divided into four stages: diagnosis of existing protections, design of an adaptive scheme using machine learning algorithms, simulation of contingency scenarios in DIgSILENT PowerFactory, and physical validation through relay testing. This approach enables a transition toward smarter and more resilient grids. As a result, the project expects to optimize protection coordination, reduce response times, and improve system selectivity. The project directly impacts the technical training of undergraduate and graduate students, promotes a culture of technological innovation in the energy sector, and contributes to Sustainable Development Goals related to resilient infrastructure and responsible production.<br/><br/><b>Goal</b>: <br/>Optimize adaptive electrical protection schemes for expanding power systems by integrating renewable energy sources and storage to enhance stability and security. The project aims to develop and validate a machine learning-based model to overcome the limitations of traditional systems.<br/><br/><b>Research lines</b>: <br/>Optimization in electrical systems<br/>Transmission and distribution of electrical energy