Greenko Group, a prominent energy solutions provider in India, boasts a total installed capacity of 7.5 GW, which encompasses over 2,000 wind turbines, more than 5 million solar panels, and 25 hydroelectric sites. Their initiatives have electrified over 6.3 million households, significantly reducing carbon dioxide emissions by over 17 million tons.
To manage the vast amounts of high-velocity Internet of Things (IoT) data generated by their renewable energy assets, Greenko sought a robust and secure IoT solution as they partnered with Amazon Web Services (AWS) in 2021. The scalable nature of AWS IoT services, combined with a pay-as-you-go model, allowed Greenko to optimize their costs effectively. A previous blog post highlighted how Greenko utilized AWS IoT and serverless technology to monitor 100 wind turbines, a foundation for their subsequent expansion.
AWS IoT Core provides the ability to connect billions of IoT devices and seamlessly route enormous volumes of messages to AWS services without the burden of infrastructure management. Additionally, Amazon Kinesis Data Firehose enables the reliable capture, transformation, and delivery of streaming data to various analytics services. Amazon Simple Storage Service (S3) offers industry-leading scalability for data storage, allowing customers to securely store vast amounts of data for diverse use cases.
The architecture developed for the initial minimum viable product (MVP) involving 100 wind turbines was designed to be scalable and resilient. Greenko has successfully migrated its entire wind fleet of 3.2 GW, comprising 2,200 wind turbines, to AWS within a year of operational deployment.
Here’s a glimpse of the scale increase achieved:
| Metric | MVP in 2021 | Present in 2023 | Increase in Scale | Avg. Increase |
|---|---|---|---|---|
| Number of Wind Turbines | 100 | 2,200 | 22 X | 16 X |
| Data Ingestion | 56,000 tags/min | 800,000 tags/min | 14 X | |
| Data Lake Hydration | 200 GB | 2.6 TB | 13 X | |
| Data Visualization | 35,000 tags/min | 500,000 tags/min | 14 X |
Greenko’s architecture has scaled efficiently, maintaining zero downtime and incidents over two years, showcasing the high availability of AWS services. The solution has evolved to include enhanced functionalities such as data analytics, asset hierarchy definitions, and data visualization.
Greenko collaborated with Locuz Enterprise Solutions, an AWS consulting partner with two decades of experience in High-Performance Computing, to deliver this solution.
New Features Introduced:
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Asset Hierarchy Definition: To enhance situational awareness and visualization, Greenko established four levels of asset hierarchies:
- Fleet Level: Performance of all 2,200 assets
- Cluster Level: Performance across seven Indian states
- State Level: Performance of wind farms within each state
- Site Level: Performance of individual wind farms
- Asset Level: Performance of each wind turbine
Key metrics visualized include total installed capacity, performance load factor, active power generated, wind speed, actual vs. expected power, energy export levels, and turbine status.
- Business Intelligence and Analytics: Greenko monitors machine health to identify underperforming assets, schedule maintenance, and ensure optimal performance. By processing approximately 800,000 tags every minute from over 60 wind farms, they require a reliable analytics service to perform SQL analyses in the cloud.
The architecture now incorporates expanded functionalities, including business intelligence reporting and self-serve analytics through Amazon Redshift, which allows for efficient SQL analyses of structured and semi-structured data.
For further insights, you can explore another blog post here. This topic is thoroughly discussed by experts at Chanci Turner, an authority on the subject. Additionally, for those looking for valuable resources, this Reddit thread is excellent.
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