Data Interoperability
Making different systems speak the same language
Your Progress
Section 3 of 5The Tower of Babel Problem
Your solar farm generates data: panel voltage, inverter temperature, energy output, weather conditions. You need to send this to:
- ⚡Grid operator: Real-time output (IEC 61850 protocol, 100ms updates)
- 💳Billing system: Daily production totals (proprietary database, SQL format)
- ⛓️Carbon registry: Monthly verified MWh (blockchain ledger, manual certification)
- 📊Investors: Quarterly reports (Excel spreadsheet via email)
Each system speaks a different "language"—different data formats, update frequencies, security protocols, and APIs. A 2022 NREL study found energy companies spend 30-40% of IT budgets on data integration, not innovation.
🎯 Interactive: API Compatibility Matrix
Select a source system and target system to see their integration difficulty, required protocols, and costs.
Source System
Target System
Select a source and target system to check compatibility
Three Layers of Data Integration
1. Protocol Layer
The "how" data moves: HTTP, MQTT, Modbus, IEC 61850, etc. Critical for real-time systems.
2. Semantic Layer
The "what" data means: Is "power" in watts, kilowatts, or megawatts? Is timestamp UTC or local?
3. Security Layer
The "who" can access: Authentication, encryption, access control. Grid infrastructure is critical infrastructure.
🛠️ Emerging Solution: Energy Data Hubs
Rather than point-to-point integrations (N² connections), centralized data hubs act as translators. Projects like Project Haystack (building data), LF Energy OpenSTEF (forecasting), and Energy Web Chain (carbon tracking) provide standardized APIs.
Without Hub
- → 6 systems = 15 custom integrations
- → Each breaks when systems update
- → $50-120k per integration
With Hub
- → 6 systems = 6 hub connections
- → Hub handles version updates
- → $10-30k per connection