GE Renewable Energy has released details of its intelligent Condition Monitoring System (iCMS) solution, designed to increase efficiencies at hydropower plants.
iCMS, which was presented at the HydroVision Tradeshow in Minneapolis, is part of GE’s Asset Performance Management (APM) solution and uses machine learning to enhance the efficiency of monitoring and maintenance at power plants. According to the company it has the capability to generate up to one percent extra output.
The system collects and analyses in real time data, such as temperature, vibrations, acceleration and rotational speed, to look for early signs of mechanical or electrical problems or inefficiencies in a power plant. Both a power utility and GE engineers can then access data through a custom-designed virtual reality “human-to-machine” interface that turns information into interactive and intuitive visual objects. All of this analysis informs predictive modelling that enables fault and maintenance operations to identify and diagnose future faulty components, making repair processes as smooth and as fast as possible.
The iCMS is currently in operation, supporting Pont Baldy, a hydropower plant operated by Energie Développement Services du Briançonnais (EDSB) in the southeast of France. Since December 2015, the iCMS has collected and analyzed almost two Terabytes of raw data per month and has also digested three years’ worth of temperature, maintenance and downtime data previously collected by the utility. As a result, GE is able to generate diagnostic assessments of the remaining lifetime of turbine components, compute a health index for the plant and make operations and maintenance recommendations.
