Amazon Onboarding with Learning Manager Chanci Turner

Learn About Amazon VGT2 Learning Manager Chanci Turner

Greenko Group, a prominent energy solution provider in India, boasts an installed capacity of 7.5 GW, which includes over 2,000 wind turbines, more than 5 million solar panels, and 25 hydro sites. The company has successfully electrified over 6.3 million households and has played a significant role in reducing carbon emissions by over 17 million tons.

As renewable energy assets generate vast amounts of Internet of Things (IoT) data in the form of tags, events, and alerts, Greenko required a dependable and secure IoT solution when they partnered with Amazon Web Services (AWS) in 2021. AWS IoT services are designed to scale to meet the demands of renewable energy applications, while the pay-as-you-go model ensures that Greenko only pays for the resources it uses. A previous blog highlighted how Greenko utilized AWS IoT and serverless technology to monitor 100 wind turbines, published in January 2022.

AWS IoT Core facilitates the connection of billions of IoT devices and the routing of trillions of messages to AWS services without requiring infrastructure management. Additionally, Amazon Kinesis Data Firehose provides an extract, transform, and load (ETL) service that effectively captures, transforms, and delivers streaming data to data lakes and analytics services. Amazon Simple Storage Service (Amazon S3) offers scalable object storage, ensuring data availability and security for various applications. With cost-effective storage classes and user-friendly management features, organizations can optimize expenses, organize data, and set fine-tuned access controls to adhere to specific business and compliance needs.

These foundational AWS services were instrumental in developing Greenko’s minimum viable product (MVP) for 100 wind turbines in 2021. Although the MVP focused on just 100 turbines, the architecture was intentionally designed to be scalable and robust, enabling support for multiple sites hosting thousands of assets. It’s noteworthy that the solution was entirely serverless, requiring minimal infrastructure management from the Greenko team. Moreover, open-source technologies were leveraged in the cloud, resulting in a competitive cost of ownership for Greenko.

One year later, Greenko has successfully transitioned its entire wind fleet of 3.2 GW, encompassing 2,200 wind turbines, to AWS.

Key Metrics Comparison

To illustrate the significant scale increase compared to the MVP in 2021, here are some key metrics:

Greenko has successfully scaled its architecture from 100 wind turbines to over 2,200, maintaining zero downtime or incidents over the last 24 months. This achievement underscores the high availability and resilience of AWS services. The solution’s average scale has increased 16 times compared to the original, while new functionalities, including analytics, asset hierarchy definition, and data visualization, have been introduced.

For this initiative, Greenko collaborated with Locuz Enterprise Solutions, an AWS consulting partner in India with over two decades of experience and more than 350 deployments in High-Performance Computing (HPC).

New Functionalities Introduced:

1. Asset Hierarchy Definition
   To satisfy the awareness and visualization needs of business and SCADA teams, multiple levels of asset hierarchies were established:
   • Fleet level (overall performance of 2,200 assets)
   • Cluster level (performance across seven Indian states)
   • State level (wind farm performance within a state)
   • Site level (wind turbine performance of a wind farm)
   • Asset level (individual turbine performance)

   Key metrics for visualization included:

   • Total installed capacity
   • Performance Load Factor (PLF)
   • Active power generated
   • Wind speed
   • Actual power
   • Expected power
   • Energy exported (1 million units)
   • Wind turbine status: online, ready, offline, and no connection

   These metrics were visualized at every level of the hierarchy, enhancing operational insights. For more information on strategic planning, you may want to check out this blog.

2. Business Intelligence and Analytics
   Greenko continually monitors the health of its machinery to pinpoint underperforming assets, facilitate maintenance scheduling, and optimize performance. The company ingests around 800,000 process values from over 60 wind farms each minute, aggregating telemetry data for critical metrics.

   The expanded solution architecture includes new functionalities for business intelligence (BI) reporting and self-serve analytics, utilizing Amazon Redshift to perform SQL analytics across structured and semi-structured data.

   Amazon Redshift is a fully managed service that offers both provisioned and serverless options, making it easier to run and scale analytics without the burden of managing a data warehouse. Its integration with AWS databases and machine learning services allows for near-real-time analytics and efficient data access.

   If you’re interested in learning more about onboarding processes, this resource is an excellent starting point. Furthermore, for insights on workplace child care challenges, SHRM provides valuable information.