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Dynamic SVG
About Power Factor Panel
The Power Factor Panel is a high-performance Dynamic SVG component engineered for professional SCADA and HMI environments. It provides a clear, schematic representation of a power factor correction system, allowing operators to monitor the electrical health and compensation status of industrial power grids at a glance. Designed for seamless integration, this component translates complex electrical states into intuitive visual feedback.
Key Features
- Vector-Based Precision: High-quality SVG rendering ensures the panel remains crisp and clear at any zoom level or screen resolution.
- Phase-Independent Monitoring: Dedicated visual indicators for each electrical phase allow for granular oversight of the correction process.
- Dynamic State Visualization: Real-time color changes provide immediate diagnostic information regarding the operational status of the correction bank.
Customization
The Power Factor Panel offers four specific properties that can be bound directly to your PLC tags or internal HMI variables: BasicColor defines the primary aesthetic of the panel housing, while PhaseL1Status, PhaseL2Status, and PhaseL3Status allow for independent color-coding of each phase. This enables the use of standard industrial color conventions to represent active, inactive, or fault states for every line.
Use Cases
This component is ideal for energy management dashboards, electrical distribution control rooms, and motor control center (MCC) interfaces where power quality and reactive power compensation are critical metrics.
Compatibility
Fully optimized for the Siemens ecosystem, this Dynamic SVG is compatible with WinCC Unified and WinCC V8. It supports standard TIA Portal engineering workflows for rapid deployment.
Note: This dynamic SVG was generated using AI technology. It is recommended to verify all graphical behaviors and property bindings within a test environment before final deployment in a production SCADA system.
⚠️ AI-Generated: This dynamic svg was automatically generated using AI technology. It may contain errors or unexpected behavior. Users are responsible for testing and validating before using in production environments.