Artificial intelligence transforms the daily routine of energy consultancies, speeding up complex simulations and data cross-referencing for the power sector.
PSR, a renowned consulting firm and developer of analytical tools, is integrating advanced artificial intelligence solutions to optimize its operations.
The technology has been fundamental in reducing manual effort in in-depth analyses, allowing specialists to examine a much broader range of hypotheses and scenarios in the clean energy market.
The innovations were detailed during the AI Day event, where the company demonstrated how natural language commands can already interact directly with complex computational models.
While the technology takes over repetitive and high-volume operational tasks, technical validation and analytical rigor remain under human supervision.
Intelligent Agents Connected to Models
The key differentiator of PSR‘s new approach is the use of autonomous agents capable of interpreting textual requests and executing operational sequences without the need for prior coding.
Using the Model Context Protocol (MCP) and programming interfaces known as APIs, these agents can manipulate databases and trigger simulation software with extreme speed.
During demonstrations, the tool interacted with SDDP—one of the country’s main energy operation optimization systems—to automatically alter demands, perform consecutive runs, and generate analytical graphs.
What previously required almost an entire day of operational work can now be completed in a few minutes, increasing technical efficiency.
Raphael Sampaio stated:
If it has to do 100 runs, it will do 100 runs. But, at the end of the day, the responsibility is ours.
The statement was made by Raphael Sampaio, head of Research and Development at the organization.
Data Unification and New Horizons
Another technological pillar presented is the corporate lake house, developed to centralize dispersed information from regulatory bodies and operators such as Aneel, CCEE, and ONS.
By cross-referencing heterogeneous records in a single interface accessible via natural language, the structure simplifies performance diagnostics, outflow restriction studies, and detailed analyses of self-generation for renewable energy projects.
The initiative marks a significant evolution in how the power sector handles the massive volume of operational information.
With the significant reduction in processing time for scenarios of energy transition and expansion of clean sources, analysts and regulators are expected to gain even more agility in planning the future of the national electricity matrix.
