GE Renewable Energy has presented its latest digital intelligent Condition Monitoring System (iCMS) for hydropower plants at HydroVision Tradeshow in Minneapolis, US.

iCMS is part of GE’s Asset Performance Management (APM) solution. It utilizes machine learning to improve the efficiency of monitoring and maintenance of power plants.

The solution is capable of generating up to one percent extra output.

According to GE, when hydropower is coupled with powerful data and analytics, it can help utilities in managing energy more efficiently than ever before.

The system collects and analyses real time data including temperature, vibrations, acceleration and rotational speed and can predict early signs of mechanical or electrical problems and related inefficiencies that can creep into the power plant system.

The information thus collected, can be accessed through customisable human-to-machine interface and it turns the information into interactive and intuitive visual objects.

This analysis informs predictive modelling, enabling fault and maintenance operations in diagnosing and identifying faulty components in the future and also making repair process smooth.

The iCMS is presently in operation at Pont Baldy hydropower plant operated by Energie Développement Services du Briançonnais (EDSB) in the southeast of France.

So far,  it had collected over two terabytes of raw data per month and has also processed three years’ worth of information related to temperature, maintenance and downtime data previously collected by the power plant.

As a result, the iCMS can generate diagnostic assessments about the remaining life time of the turbine components and calculate a health index for the plant and make operations and maintenance recommendations.