OpenPDC

OpenPDC includes an integrated historian that archives streaming synchrophasor data to disk with extremely low latency. It uses a custom binary file format optimized for sequential write performance, enabling sustained ingestion of millions of measurements per second without data loss. The historian supports lossless compression and automatic file rotation based on configurable size or time thresholds. Archived data can be queried by time range and exported for offline analysis using tools like MATLAB or Python.

The platform's action framework allows users to define custom processing logic that executes on each received synchrophasor frame. Actions are implemented as .NET assemblies and can perform:

• Real-time event detection (e.g., frequency deviation alarms)
• Data quality flagging based on user-defined thresholds
• Custom calculations such as derived phasor quantities
• External system integration via SQL, REST, or message queues Multiple actions can be chained into a processing pipeline, and actions can be enabled or disabled at runtime without restarting the service.

OpenPDC can simultaneously publish aligned synchrophasor streams to multiple downstream consumers. Output options include:

• IEEE C37.118.2 server mode for feeding other PDCs or applications
• GEP for efficient inter-PDC data exchange
• Kafka and RabbitMQ adapters for integration with modern data lakes
• WebSocket streaming for browser-based visualization dashboards This multi-cast capability ensures that a single OpenPDC instance can serve operations, engineering, and planning teams concurrently without duplicating data flows.

OpenPDC implements robust data quality management to ensure downstream applications receive reliable measurements. Key features include:

• Timestamp validation to detect GPS clock errors or spoofing attempts
• Data gap detection with configurable fill policies (hold last value, insert NaN, or flag)
• Frame rate monitoring to identify PMUs that are under-sampling or stalled
• Total Vector Error (TVE) threshold alarming based on IEEE C37.118 compliance limits Quality flags are propagated through the data pipeline so that consuming applications can make informed decisions about measurement trustworthiness.

OpenPDC supports hierarchical PDC topologies where local PDCs at substations concentrate data from PMUs and forward time-aligned streams to regional or central PDCs. This architecture reduces WAN bandwidth requirements and provides fault tolerance through redundant data paths. The system can be configured for active-active or active-standby failover using external load balancers or the built-in GEP subscription model. A central management console provides visibility into the health and throughput of all distributed PDC nodes.

The source device that generates the streaming data OpenPDC concentrates. A PMU samples AC waveforms at 30-120 samples per second and time-stamps the calculated synchrophasors using a GPS-disciplined oscillator. OpenPDC is designed to receive and parse these high-speed streams natively, supporting multiple PMU vendors simultaneously without protocol translation middleware.

The primary communication standard that OpenPDC uses to ingest data. It defines four frame types:

• Data frames: Streaming synchrophasor measurements
• Configuration frames: PMU reporting capabilities and scaling factors
• Header frames: Human-readable station metadata
• Command frames: Remote control requests OpenPDC's input adapter parses these binary frames in real-time, extracting phasor magnitude, angle, frequency, and ROCOF.

The core function of a Phasor Data Concentrator. OpenPDC uses a concentrator algorithm that sorts incoming frames by their GPS timestamp, waits for late-arriving data within a configurable lag window, and publishes a complete, time-aligned dataset. This process handles network jitter and ensures all downstream analytics operate on a consistent, simultaneous snapshot of the grid.

OpenPDC includes a built-in historian that archives aligned measurements to a local database. It supports multiple backends:

• SQL Server / MySQL: For operational metadata and event logs
• Custom binary files: For high-performance, lossless data capture
• OpenHistorian: A companion time-series database optimized for terabyte-scale synchrophasor storage This enables post-event analysis, oscillation replay, and model validation.

The application layer that consumes OpenPDC's output. WAMPAC systems subscribe to the real-time data stream to perform:

• Modal analysis for small-signal stability assessment
• Angle difference monitoring across critical transmission corridors
• Oscillation detection for early warning of grid instability OpenPDC acts as the data backbone, providing a single, reliable point of access for all these mission-critical functions.

The absolute prerequisite for synchrophasor data validity. OpenPDC relies on every PMU being synchronized to a common time source, typically a GPS Disciplined Oscillator (GPSDO). The concentrator's alignment algorithm uses the GPS-derived timestamps to correlate measurements across hundreds of miles. A GPS spoofing attack or clock drift on a single PMU will corrupt the entire aligned dataset, making time-source integrity a critical cybersecurity concern.