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Cloud-Based IoT Solution for Wind Farms

Client

A leading developer and operator of renewable energy projects, focused on providing sustainable energy solutions generated from wind farms and solar power across Asia.

Industry

Renewable Energy

Offering

A cloud-based IoT solution with an advanced analytical engine for condition monitoring and performance tracking of equipment at wind farms. The solution offers the client a bird’s-eye view into power generated as well as operational aspects of turbines, wind masts, and substations.

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Business Requirement

The client required a centralized dashboard to monitor operations at remotely located wind farms. The solution would provide the management with a bird’s-eye view into power generated as well as operational and conditional aspects of turbines, wind masts, and key components at substations and farms.

  • Consolidated view into performance and condition of wind turbines at farms with remote monitoring of relevant statistics
  • Real-time monitoring capability to track key KPIs
  • Real-time analytics to quickly identify and mitigate technical problems that can disrupt operations
  • Capture and store data for future analysis

QBurst Solution

We developed a cloud-based Industrial IoT solution to monitor wind turbines (including blades, gearbox, bearings, and generator), wind masts, and other critical components at the client’s wind farms spread across multiple locations. The collected data is consolidated by the analytical engine and insights are presented via a centralized dashboard.

Solution Components

  • Web and mobile-based interfaces to monitor wind farm infrastructure
  • Backend analytics engine to consolidate, process, and derive insights
  • Cloud-based service for data storage and retrieval

Business Benefits

  • Improved ROI through effective turbine monitoring by tracking changes in input and output parameters as well as performance indicators
  • Bird’s-eye view into operational status of equipment at wind farms helped improve equipment utilization and power generation
  • Alarm and notification features help technicians take quick action on critical issues
  • Advanced analytical capabilities facilitate predictive maintenance, extending asset life
  • Significant reduction of time, effort, and cost involved in manual and periodic monitoring practices

Key Features

  • Monitor turbine parameters such as generator and rotor speed, nacelle and gearbox oil temperature, yaw deviation, pitch angle, nacelle position, and power.
  • Detect underperformance by comparing the power curve provided by the turbine manufacturer with actual power output.
  • Track average power production time relative to wind speeds on a visually intuitive time-series graph.
  • View farm and turbine data by navigating the tree view with drill-down facility to view status of each turbine/substation.
  • Intuitive warning alerts to help detect asset performance issues with easily recognizable color codes for timely maintenance and corrective action.
  • CMMS plug-in module supports alerts and calendar-based maintenance management system with push notifications. View and manage maintenance/service records.

Technologies

  • Apache Kafka
  • Apache Spark
  • HDFS
  • MongoDB
  • Scala
  • Python
  • OPC

Business Requirement

The client required a centralized dashboard to monitor operations at remotely located wind farms. The solution would provide the management with a bird’s-eye view into power generated as well as operational and conditional aspects of turbines, wind masts, and key components at substations and farms.

  • Consolidated view into performance and condition of wind turbines at farms with remote monitoring of relevant statistics
  • Real-time monitoring capability to track key KPIs
  • Real-time analytics to quickly identify and mitigate technical problems that can disrupt operations
  • Capture and store data for future analysis

QBurst Solution

We developed a cloud-based Industrial IoT solution to monitor wind turbines (including blades, gearbox, bearings, and generator), wind masts, and other critical components at the client’s wind farms spread across multiple locations. The collected data is consolidated by the analytical engine and insights are presented via a centralized dashboard.

Solution Components

  • Web and mobile-based interfaces to monitor wind farm infrastructure
  • Backend analytics engine to consolidate, process, and derive insights
  • Cloud-based service for data storage and retrieval

Business Benefits

  • Improved ROI through effective turbine monitoring by tracking changes in input and output parameters as well as performance indicators
  • Bird’s-eye view into operational status of equipment at wind farms helped improve equipment utilization and power generation
  • Alarm and notification features help technicians take quick action on critical issues
  • Advanced analytical capabilities facilitate predictive maintenance, extending asset life
  • Significant reduction of time, effort, and cost involved in manual and periodic monitoring practices

Key Features

  • Monitor turbine parameters such as generator and rotor speed, nacelle and gearbox oil temperature, yaw deviation, pitch angle, nacelle position, and power.
  • Detect underperformance by comparing the power curve provided by the turbine manufacturer with actual power output.
  • Track average power production time relative to wind speeds on a visually intuitive time-series graph.
  • View farm and turbine data by navigating the tree view with drill-down facility to view status of each turbine/substation.
  • Intuitive warning alerts to help detect asset performance issues with easily recognizable color codes for timely maintenance and corrective action.
  • CMMS plug-in module supports alerts and calendar-based maintenance management system with push notifications. View and manage maintenance/service records.

Technologies

  • Apache Kafka
  • Apache Spark
  • HDFS
  • MongoDB
  • Scala
  • Python
  • OPC
AWS Cloud Migration

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