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Advanced Analytics System for Smart Metering Infrastructure

future-processing.com

Energy & natural resources

Utilities

Business Challenges

Need for digital transformation to enhance distribution system operator (DSO) processes through advanced analytics of smart meter data, including detection of illegal energy consumption, reduction of trading losses, prevention of technical failures, and scalable architecture for 14 million planned smart meters.

About the Client

Largest distribution system operator in Poland, serving 5.6 million customers and distributing 50 TWh of energy annually across 57,940 km².

Key Goals

Implement scalable cloud-based analytics system for 61.7 million daily smart meter readings
Enable real-time detection of illegal energy consumption using machine learning
Optimize grid efficiency through reactive energy flow analysis and load modeling
Automate calculation of grid performance metrics (SAIDI, SAIFI, simultaneity factor)
Support digital transformation of DSO business processes

Core System Capabilities

Multi-source data ingestion from AMI and balancing meters
Machine learning models for anomaly detection
Interactive visualization dashboards with GIS mapping
Automated grid performance metrics calculation
Load modeling and simulation tools for grid expansion planning
Reactive energy impact analysis module
Scalable data storage architecture

Technology Stack

Cloud computing platforms (AWS/Azure)

Machine learning frameworks (TensorFlow/PyTorch)

Time-series databases

Big data processing engines (Spark)

API gateways for system integration

System Integrations

Advanced Metering Infrastructure (AMI)
Balancing electricity meters
Existing DSO operational systems
Grid management systems

Operational Requirements

Horizontal scalability for 14 million meters
Real-time processing capabilities
Data integrity across multiple sources
Enterprise-grade security and compliance
High-availability cloud architecture
Cost-optimized resource utilization

Expected Business Outcomes

Enables 80% smart meter coverage by 2028 with scalable infrastructure, reduces commercial losses through faster illegal consumption detection, optimizes grid maintenance through predictive analytics, improves energy supply stability, and supports data-driven investment decisions for grid modernization.