When 97% isn’t good enough

By Lakshman Sutrave, February 8, 2018

Any asset owner knows that a 100% guaranteed uptime is well-nigh impossible, especially when the usage conditions vary.

In case of wind IPPs, many of the contracts with Wind Turbine OEMs was inked at a 97% time based machine availability as the OEMs took care of O&M.

However, many IPPs realized the slotted 3% tolerance often didn’t play out as expected. As an IPP, they would expect that a lot of the maintenance activity be carried out in the low wind season so that they could have the highest uptime in the high wind season. But this often doesn’t work as planned – O&M teams often don’t have enough advance warning on asset health to prevent sudden breakdowns in the high-wind season.  Due to this, there are often delays in ensuring trained professionals had all the information leading to the breakdown, isolating underlying breakdown issues, or even getting replacement parts to the site.

On the other hand, while availability targets are met, the efficiency at which the assets need to perform is not included in the SLAs.

End result: Loss of revenue, which would be borne by IPPs if this was within the 3% availability tolerance window.

Until recently, the only way to overcome this was for the IPP to have their own trained personnel inspect every turbine in detail, and manually draw inferences on asset health. This has to be done in the low wind season to ensure minimum revenue loss due to scheduled downtime.

However, data-science based solutions can ease out a lot of the problems using predictive analytics.

IPPs have started deploying real-time performance monitoring and analytics softwares, accessing  SCADA data from the OEMs. They are also building their own remote monitoring & analyst teams, not only to reduce the risk of unplanned breakdowns and take a proactive approach to issues, but also to ensure they eke out the optimum efficiency from their assets that are operating.

Some advantages for IPPs deploying these solutions are:

1. Asset behavior analyses and continuous improvement of generation over and above the guaranteed machine availability given by the OEMs
2. Proactive measures on issues such as unplanned downtimes
3. Control over the park to identify efficiency related problems and inform the O&M teams for prompt actions
4. Data backed conversations with OEMs and O&M teams

BCT has developed powerful monitoring and predictive analytics solution for the renewable energy industry. BCT’s renewable energy solutions for wind power and solar power are built using RETINA – our patent-pending predictive analytics platform that helps clients increase energy generation, improve machine availability and identify asset performance degradations, proactively. The solutions are OEM-agnostic and provide insights critical for driving renewable business operations. For more information on our offerings in this space, please visit renewables.bahwancybertek.com

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Lakshman Sutrave

Lakshman is a seasoned Marketing Specialist with a focus on Product Marketing, Pre-Sales, Presentations and Demos. He has over 10 years of experience working in Marketing with large brands like Frost & Sullivan, GE Prolec and Triveni Turbines. He currently works with Bahwan Cybertek helping market the company’s marquee Energy & Renewables products. His extensive experience working in Energy adds great value to the company and its offerings.

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