Smart Energy
Smart Energy.
Intelligence for the Grid.
From energy data to intelligent decisions.
Energy networks are becoming increasingly complex: distributed generation, renewable energy, electric vehicles, smart meters, IoT devices, new consumption patterns and massive amounts of data.
Traditional monitoring tells us what happened. The next generation of systems must help us understand what is happening now, why, what is likely to happen next and what should be done.
From Smart Grid to Intelligent Grid.
What we build
Energy data becomes intelligence.
The energy transformation
The Energy Transformation.
Modern electricity infrastructure is no longer defined only by transformers, substations, cables and meters. Every connected component can become a source of information.
G3T Smart Energy
Four layers.
One foundation.
Together, these layers create the technological foundation for Intelligent Energy Systems.
Energy data intelligence
Every source,
one understanding.
AI for loss analysis
AI for Loss Analysis.
Energy losses represent a major operational and economic challenge. Advanced analytics and AI can help identify patterns that may indicate areas requiring additional investigation.
Find faster. Understand better. Act earlier.
Featured production
AntiLost — AI for
Energy Efficiency.
AntiLost represents an important Smart Energy development direction for G3T. G3T participates in the development of AI tools and further development of a software solution aimed at reducing losses in energy systems.
Energy Expertise + Data + Software Engineering + AI
Anomaly detection
Show us where to look.
AI-based anomaly detection can help identify unusual consumption behavior, unexpected measurement patterns, abnormal changes over time, inconsistencies between related datasets and operational deviations.
Predictive analytics
Reactive → Proactive
→ Predictive.
The objective is to move from explaining the past toward asking: what is likely to happen next?
Predictive Maintenance
As a development direction, combining historical information, operational measurements, sensor data and AI models can potentially help identify changes in equipment behavior earlier and support better maintenance prioritization.
- Earlier detection
- Better maintenance prioritization
- Reduced unnecessary interventions
- Improved asset utilization
- Better operational planning
Grid Forecasting
From past data to future insight — forecasting as a standing capability of the grid.
Optimization & decisions
Better grid performance.
Better decisions.
Grid Optimization
AI-based models can potentially help identify more efficient ways of using existing infrastructure, identify inefficiencies and priorities, and reveal opportunities for loss reduction.
The goal is better grid performance.
Decision Intelligence
AI should not be seen only as a replacement for human decision-making. In critical infrastructure, one of its greatest roles can be to provide operators with better information: what changed, where, why it matters, what may happen next and where to look first.
The intelligent grid loop
The G3T Intelligent
Grid Loop.
Towards the digital twin
See the grid. Understand
the grid. Simulate the grid.
As a long-term development direction, different data sources can be connected into a unified digital model of infrastructure: topology, assets, metering, sensor data, historical events, operational information and AI analytics.
Smart Energy Architecture
From Monitoring to Autonomy
Vision
The grid should not only be smart. It should be intelligent.
A smart grid connects infrastructure. An intelligent grid understands it, recognizes patterns, detects deviations, learns from historical information, anticipates future behavior and helps operators make better decisions.
G3T Smart Energy — Engineering Intelligence for Energy
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Smart Energy
G3T — A Belgrade Production