Project Description

Data ingestion: Kylo 0.8.4 (with Nifi, Spark, HDFS and Hive)

Controlling Operational Efficiency at Wind Farms


Assembling large number of technicians and investment in time & money manages numerous remotely located turbines. The monitoring of performance of turbines at wind farms are expensive affair that most companies wish to do away with. Such problems are being addressed by IoT with advanced sensors capturing key performance indicators such as vibration, speed, and temperature, available from a concentrated dashboard. The dashboard represents intuitive graphs and charts that present operational and conditional parameters on a single screen for simple supervision and analytics.

Client profile:

A foremost developer and operator of renewable energy projects across Africa focused on providing sustainable energy solutions produced from wind farm and solar power.

Business Requirement:

The client wanted a centralized dashboard which would help in monitoring operations remotely at wind farms. The solution would provide the organization with the bird’s eye view into power produced as well as operational and provisional facets of turbines, wind masts, and key components at farms and substations.

  • Combined track of routine and condition of wind turbines with remote monitoring
  • Real time supervising ability to track key KPIs
  • The real-time investigation to spot technical problems which causes disruption
  • Confine and accumulate data for future analysis

Solution Provided:

We build a cloud based Industrial IoT solution which monitors wind turbines (including blades, gearbox, bearings and generator), wind masts, and various critical components at multiple locations where the wind farms are set up. The insights are offered by centralized dashboard and the data is united by analytical engine.

Real-time Performance and Production Monitoring

The solution includes the collection of data from wind farm equipment by interfacing with the systems at backend. The data is being transmitted to cloud based backend which examines data using statistical and data mining techniques which detects changes in systems behavior. This makes the data easy for analysis and to plan corrective action accordingly. This practice is cost and time effective unlike seen in manual and periodic practices.

Proficient tracking of Composite Operating Environment

This platform gives client the access to equipped data securely from anywhere with the help of web-based interface. Data from turbines, wind masts and substations will be available through Open Platform Communication (OPC) servers. The data will be fetched and transmitted with the help of OPC to cloud for computation and supervision. The data is presented through web based dashboard using graphs and other elements.


  • Changes in input and output as well as performance indicators are done through effective turbine monitoring which directly improves ROI
  • Equipment utilization and power generation are improved with the help of Bird’s eye view into operational status of equipment.
  • The technicians are being alerted to take quick action on critical issues through alarms and notifications.
  • Predictive maintenance and extending asset life are facilitated by advanced analytical capabilities.
  • This practice is cost and time effective unlike seen in manual and periodic practices.

Technologies Used:

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


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Project details
  • January 10, 2018