Enexis Transforms Smart metering with real-time data streaming

Quick facts

• Company: Enexis Netbeheer
• Date: 2023-Present
• Our Involvement: Enterprise Kafka platform deployment for smart grid data infrastructure, including governance framework implementation and integration with existing DSO systems

About Enexis

Enexis Netbeheer operates one of the largest electricity and gas distribution networks in the Netherlands, serving over 2.7 million connections across five provinces. As a Distribution System Operator (DSO) managing critical energy infrastructure, Enexis faces the technical challenge of processing massive volumes of smart meter data while maintaining grid stability and regulatory compliance.

Goals & context

Enexis needed a data streaming platform capable of handling smart meter lifecycle management across their service territory. The challenge extended beyond simple data collection. Smart meters generate continuous streams of consumption data essential for billing accuracy, grid balancing, power quality monitoring, and fraud detection. Their existing approach failed on multiple fronts: manual data retrieval from low-level AMR (Automatic Meter Reading) systems created bottlenecks, inconsistent request-response patterns prevented standardization, and the architecture couldn't enforce the governance rules required for a regulated utility operating critical infrastructure.

The constraint was clear: any solution needed to integrate with legacy utility systems (Tibco, Menix, OSGI) while providing modern streaming capabilities. Standard DIY Kafka implementations would require specialized expertise Enexis couldn't dedicate to platform management when their focus needed to remain on grid operations and energy distribution.

Strategic approach

Hypothesis: Smart meter data management requires more than raw streaming infrastructure. It demands governance-first architecture that enforces data quality, access control, and audit capabilities from day one.

Principles:

• Governance as a fundamental requirement, not an afterthought
• Self-service capabilities for development teams without sacrificing control
• Integration with existing DSO systems rather than replacement
• Real-time processing enabling operational decisions at grid speed

Operating Model: Deploy Axual as the central data streaming platform connecting smart meter infrastructure with internal applications, business intelligence systems, and analytics platforms. Enable domain teams to create and consume data streams through governed self-service while maintaining centralized oversight of the entire data topology.

Implementation: From manual processes to governed streaming architecture

The manual data collection workflow represented a fundamental architectural limitation. Employees logging into individual AMR systems couldn't scale to millions of smart meters generating readings every 15 minutes, with no way to enforce consistent data formats, access policies, or audit trails. Each integration with billing systems, grid management platforms, and analytics tools required custom development, creating a maintenance burden that would only grow with expanded smart meter deployments.

Rather than building custom integration layers, Enexis implemented Axual's Apache Kafka platform with integrated governance. This created a centralized streaming backbone where smart meter data flows once and becomes available to any authorized application in real-time. The Strimzi-based open-source foundation combined with enterprise governance features addressed both immediate data collection challenges and long-term integration complexity.

The implementation centered on four architectural capabilities. Role-based access control ensured only authorized applications could access specific meter data streams. Schema management standardized data formats across all smart meter events. Visual data flow management provided operations teams clear visibility into how data propagates through systems. The connector framework integrated with Tibco, Menix, and legacy OSGI components without custom code, treating external system integration as configuration rather than development.

The platform's self-service interface enabled development teams to create new data streams without waiting for central IT, while governance policies automatically enforced regulatory requirements. Enexis deployed connectors for Debezium (change data capture), S3 and Snowflake (data lake and analytics), Java-based applications, and legacy systems. Multi-cluster architecture with built-in replication ensures high availability for mission-critical meter data.

The architecture now handles 70+ distinct data streams serving 60+ integrated applications, with 150+ developers collaborating on the platform. Seven distinct technology stacks integrate without custom code, each benefiting from the same governance policies and access controls.

Enexis eliminated manual data collection entirely. Fraud detection improved through real-time processing rather than batch analysis. Development cycles shortened as teams provisioned new streams through self-service. Most significantly, the governance framework ensures every data access, schema change, and application integration leaves an audit trail meeting regulatory requirements for critical infrastructure operators. The standardized architecture means Enexis can add new capabilities like power quality monitoring or distributed energy resource management without architectural redesigns.

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Results

• 70+ Data Streams processing smart meter events, grid operations data, and system integrations
• 60+ Applications consuming real-time meter data for billing, analytics, fraud detection, and grid management
• 150+ Developers collaborating on the platform across multiple business units and technical domains
• Zero Manual Data Collection from AMR systems, eliminating bottlenecks and inconsistent data retrieval

Closing Thoughts

The Enexis implementation demonstrates a crucial principle for critical infrastructure operators: streaming platforms require governance by design, not as an afterthought. While DIY Kafka implementations might succeed initially, they often falter when regulatory requirements evolve, team sizes grow, and the number of integrated systems multiplies. Enexis built an enduring capability that processes smart meter data today while providing the governance foundation to adapt as energy distribution becomes increasingly complex with distributed generation, electric vehicle charging, and grid flexibility requirements.

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