Program Overview
This immersive, expert-led program explores the deep-domain application of advanced SCADA (Supervisory Control and Data Acquisition) systems in wind energy. Participants will gain hands-on understanding of real-time monitoring, fault diagnostics, power optimization, and data-driven maintenance strategies. With rich insights from real-world use cases and guided simulations, the course empowers professionals to identify inefficiencies, reduce downtime, and optimize turbine output. It also addresses critical topics such as wake loss analysis, SCADA cybersecurity, and the integration of digital twins and AI, making this a must-attend for teams driving wind energy performance and reliability.
Features
- Gain deep functional knowledge of advanced SCADA architecture and turbine-specific data acquisition.
- Learn to analyze real-time SCADA data for predictive maintenance and early fault detection.
- Apply SCADA insights to optimize turbine output and reduce wake-related performance losses.
- Build situational awareness in SCADA security, data integrity, and future-ready control systems.
Target audiences
- Wind Farm O&M Professionals
- SCADA & Power Systems Engineers
- Renewable Energy Data Analysts
- Wind Asset & Plant Managers
Curriculum
- 7 Sections
- 34 Lessons
- 2 Days
Expand all sectionsCollapse all sections
- SCADA Evolution in Wind Energy5
- 1.1SCADA: architecture, history, and utility
- 1.2Transition from traditional to advanced SCADA systems
- 1.3Key terminologies: RTU, PLC, HMI, OPC, IEC 61400-25
- 1.4Deep-dive: Wind-specific protocols and communication standards
- 1.5Exercise: Map your current SCADA setup vs. advanced architectures (gap analysis)
- Real-Time Monitoring and Data Acquisition5
- 2.1What data SCADA collects in wind farms: pitch, yaw, nacelle, meteorological, gearbox, rotor, etc.
- 2.2Understanding turbine behavior through live signals
- 2.3Alarm logic & severity mapping
- 2.4Role of latency, polling rates, and signal resolution
- 2.5Use Case Discussion: Diagnosing blade pitch faults through SCADA data streams
- Situational Awareness Through SCADA Dashboards5
- 3.1Designing custom dashboards: KPI visualization, control room alerts
- 3.2Identifying operational anomalies, downtime causes
- 3.3Integrating SCADA data with CMMS, ERP, and asset analytics tools
- 3.4Human-machine interface (HMI) usability best practices
- 3.5Simulation: Analyze simulated turbine data from SCADA to pinpoint performance degradation
- Predictive Maintenance & Fault Diagnostics5
- 4.1Leveraging SCADA + ML/AI for failure prediction
- 4.2Common fault patterns and root cause analysis using SCADA logs
- 4.3Integration with vibration monitoring, thermography, acoustic sensors
- 4.4Deep-domain concepts: LIDAR-enabled SCADA, drift detection, SCADA shadowing
- 4.5Case Study: Early-stage gearbox failure prediction using SCADA trends
- Wake Effect & Power Curve Deviation Analysis5
- Cybersecurity and Data Integrity in SCADA Systems5
- Future Trends in Wind SCADA4
Instructor
