Renewable Assets — Solar & Wind Farms

The Challenge

Renewable energy operators struggle with unpredictable generation, equipment failures, and suboptimal asset utilization across geographically distributed sites.

Root Cause Analysis

• Data fragmentation: SCADA, weather, market, and maintenance data in separate silos
• Reactive maintenance: Equipment failures cause unplanned downtime and revenue loss
• Inaccurate forecasting: Poor generation predictions lead to market imbalances and penalties
• Manual monitoring: Operators can't effectively monitor hundreds of distributed assets

How We Solve This with Cloud Technologies

IoT-to-Insight Platform

We build cloud-native platforms on AWS IoT / Azure IoT Hub that unify all asset data:

• Real-time ingestion: SCADA data streamed via MQTT/OPC-UA to cloud event hubs
• Predictive maintenance: ML models (SageMaker/Azure ML) detect anomalies before failures
• Generation forecasting: Weather-aware AI models predict output 24-72 hours ahead
• Digital twins: Simulate asset behavior for optimization without physical risk

Reference Architecture

1. Edge layer: IoT gateways at each site for local aggregation and edge inference
2. Ingestion: Kafka/Event Hubs for real-time streaming
3. Data lake: Delta Lake with bronze/silver/gold medallion architecture
4. ML platform: MLflow for model lifecycle, Feature Store for feature engineering
5. Dashboards: Real-time operations dashboards with geospatial visualization

Business Impact

• 15% increase in energy yield through optimized operations
• 30% reduction in unplanned downtime via predictive maintenance
• Accurate forecasting reduces market imbalance penalties by 50%