Client: National Power Distribution Utility

Challenge:
The client had difficulty analyzing massive IoT data from millions of smart meters and grid devices. Outages were frequent, and energy consumption forecasting was inaccurate, leading to inefficiencies and higher customer complaints.

Solution (Detailed):
Chrysalis built a cloud-based big data ecosystem to handle structured and unstructured data from IoT-enabled assets. Key components included:

• AI Forecasting Models – Predicting energy demand and load fluctuations at regional and household levels.
• Predictive Maintenance Analytics – Using sensor data to detect early signs of transformer or grid equipment failure.
• Customer Analytics – Offering households personalized insights and recommendations to optimize usage and save costs.

Results:
✔ 20% reduction in power outages with predictive grid maintenance.
✔ 15% energy savings achieved through AI-driven load balancing.
✔ 30% higher customer satisfaction with personalized energy reports.