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Forecasting Meteorological Events Leading to Extreme Wind Gusts in Eletrobras' Power Transmission Assets
Co-development of a solution to forecast meteorological events that cause extreme wind gusts up to 72 hours in advance, based on meteorological data and information from the state of Paraná and surrounding regions, using an artificial intelligence framework from NVIDIA Corporation and with the active partnership of the SIMEPAR team - Paraná Environmental Monitoring and Technology System.
Using NVIDIA Corporation's AI framework, the EARTH 2 Studio, we seek proposals to develop a short-term weather forecasting solution (about 12 to 72 hours) that identifies the atmospheric patterns leading to extreme wind gusts, analyzing space-time scales beyond those typically addressed by nowcasting. The study area and data source for the development of the solution will be the state of Paraná and its surrounding regions. Consequently, to ensure the successful development of the final proposal, the participation of SIMEPAR – Paraná Environmental Monitoring and Technology System – will be essential.
The solution should be based on artificial intelligence and data analytics, applying NVIDIA Corporation's atmospheric forecasting, simulation and visualization modules, EARTH 2 Studio. This platform has an open-source framework for building, training and fine-tuning predictive models, combining causality, simulations based on atmospheric physics and observed data. To make the most of this platform, we will partner with NVIDIA Corporation.
Note: To submit the proposal, it is necessary to fill out the Registration Form and submit the Detailed Spreadsheets available at the following link.
The solution should be based on artificial intelligence and data analytics, applying NVIDIA Corporation's atmospheric forecasting, simulation and visualization modules, EARTH 2 Studio. This platform has an open-source framework for building, training and fine-tuning predictive models, combining causality, simulations based on atmospheric physics and observed data. To make the most of this platform, we will partner with NVIDIA Corporation.
Note: To submit the proposal, it is necessary to fill out the Registration Form and submit the Detailed Spreadsheets available at the following link.
Extreme Winds | Meteorological Events | Short/Mid-Term Forecasting | Data Analytics | Artificial Intelligence
Questions: For any questions or additional information, please send an email with the subject line identifying the title of this challenge to innovationgrid@eletrobras.com
Program stages
Evolution of Eletrobras Counterparty Risk Analysis Process
Evolution, automation, and integration of various stages of Eletrobras' counterparty risk analysis process focusing on energy commercialization in the Free Contracting Environment (Ambiente de Contratação Livre, ACL).
We are seeking project proposals for the evolution, automation, digitalization, and integration of various stages of Eletrobras' counterparty risk analysis process, with a focus on energy commercialization in the Free Contracting Environment (ACL). Eletrobras currently employs a robust and mature methodology for counterparty risk analysis; however, there is an opportunity to enhance this process using current advancements in artificial intelligence methodologies, enabling greater process efficiency, scalability, and exponential growth of the client portfolio. Click on the "Open Submissions" button for more details and to submit your proposal.
Reverse Pitch (online session for clarification of doubts): We thank all the more than 70 participants who were with us in the live that took place on the afternoon of 07/04/2024.
Reverse Pitch (online session for clarification of doubts): We thank all the more than 70 participants who were with us in the live that took place on the afternoon of 07/04/2024.
Data Analytics | Machine Learning | Natural Language Processing | Process Automation | RPA
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How can we optimize spare parts inventory management based on asset reliability and cost reduction?
We are looking for technological solutions that will help us reduce the total cost of storage, as well as the amounts tied up in stock. In addition, the technological solutions should help us lower the SLA for spare parts reservations for the Maintenance teams, reducing the unavailability of assets.
RPA | Data Analytics | Process Automation
