How the Renewable Energy Industry Can Leverage Real-time Analytics to Improve Asset Performance and Outcomes.

Position:DATABASE AND NETWORK INTELLIGENCE
 
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While renewable energy companies have developed advanced applications to improve diagnosing anomalies on wind turbines, for example, most are still taking a "trip first, analyze later" approach.

This operating method was acceptable when near real-time analytics or software applications were not available. Today, however, analytics can be applied seamlessly within the operational workflow of existing monitoring operations, resulting in several immediate benefits.

Automated real-time analytics for all renewables.

First, for wind power, real-time analytics enable operators to avoid tripping turbines needlessly and reset tripped turbines faster, resulting in more power output due to higher availability. This application of automated analytics results in safer asset operations with consistent, automatic review of event data to drive decisions.

Second, complex analytics that are currently being processed in batch mode by diagnostic engineers can now happen automatically in near real time. This closes the gap between insights showing what is happening on the turbine and the ability to respond quickly, resulting in better wind farm performance.

Lastly, the use of real-time analytics makes monitoring operations of all renewable energy vastly more efficient, as diagnostic personnel and engineers are freed from routine tasks and can focus on increasing asset performance and uptime.

While some companies have shied away from near real-time analytics in the past, it is now easier than ever to deploy this type of monitoring operation that has low risk and high impact on energy assets.

In order to create successful digital transformation using real-time analytics, companies must implement a solution that:

Incorporates their Subject Matter Experts' (SMEs') knowledge, enabling engineers to collaborate and build analytics;

Provides automation of key business processes (e.g. fault diagnostics) and builds a foundation for more complex analytics (e.g. machine learning).

Having software built on your Subject Matter Experts' knowledge is the best starting point.

Your SMEs and engineers have been monitoring and maintaining critical assets for years. Their knowledge is the best available expertise on how your equipment should be operated, maintained, and evaluated. Incorporating their knowledge on how to best analyze data from critical equipment is the ideal starting point for the application of real time analytics.

Analytic platforms providing purely...

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