Renewables Data Lake & Analytics
Providing the data foundation to monitor and optimize renewable energy assets.
At AWS we are helping renewable asset owners and operators expedite time-to-value by putting their data to work immediately and providing the data foundation for wind, solar, and battery energy storage systems (BESS). The Renewables Data Lake & Analytics is a cloud native solution that offers customers IoT data ingestion pipeline, data lake and advanced analytics for their renewable energy assets. This solution allows customers to monitor and optimize their renewable generation fleets at a relatively low cost, and at scale, for many millions of "tags", and both in near real-time as well as through bulk extraction. Built on an open architecture, this solution also help customer more easily integrate IT/OT data and apply modern AI/ML and BI tools, and extract the most value from their data. Our vision is that this solution can serve as a foundation for renewable project lifecycle optimization, by breaking down the data silos and integrating 3rd party tools and customer-built applications.
Specifically, the Renewables Data Lake & Analytics solution delivers the following capabilities for the customer:
Renewables Data Lake
Automated data pipeline modules, including edge connectivity (IoT), data streaming and analysis and storage.
Asset Analytics Infrastructure
Packaged architecture for generation asset analytics, including big data, BI/reporting and AI/ML/analytics tools plus unified data, asset, and governance models.
The Renewables Data Lake & Analytics solution provides a unified data backbone and drives insights for improved performance and planning of renewable assets
Renewables Data Lake & Analytics solutions help overcome the following challenges:
- Remote Operations/Operations Control Centers: Proper data ingestion and storage can be challenging and expensive with on-premises solutions.
- Lack of integration between IT/OT data and across make and model of assets.
- Performance analytics and predictive maintenance - 3rd party tools lack extensibility and open architecture.
- Data standardization.
Customer References
Greenko is one of the largest operators of renewable assets in India with an installed capacity of 7.5 GW. Originally completely on premises, Greenko was struggling to derive value from data trapped in historians, rising IT infrastructure costs and delays in onboarding of new renewable sites.
Using AWS IoT and serverless technologies, Greenko developed a scalable, cost efficient and secure IoT data ingestion and analytics platform, which eliminated data silos. The solution was implemented by Locuz and allows Greenko to get real time insights into the health of their wind turbines, spread across 15 states of India.
- Fully scalable and secure IoT industrial data lake.
- Ingests 700,00 tags per minute, with capability to expand to over 1 Million tags a minute.
- Real time dashboard and analytics, with field to cloud latency of ≤1 minute.
- Work in progress to extend architecture to solar and hydro sites.
As part of the goal to reach net-zero carbon emissions by 2040, Amazon is on a path to powering its operations with 100 percent renewable energy by 2025—five years ahead of the original target of 2030. In June 2021, Amazon became the world’s largest corporate purchaser of renewable energy, reaching 65 percent renewable energy across the business. As our renewable energy fleet grows exponentially, so does our need to monitor renewable asset operational performance in near-real time to ensure we are achieving production goals. The challenge of monitoring the performance of hundreds of renewable assets in more than 30 countries increases each day.
The Renewable Energy Optimization team at Amazon developed a complete solution built entirely on AWS to perform near-real-time monitoring of asset performance.
How to get started
Deployment Readiness Assessment:
Activities
- Business case definition
- Data strategy & requirements
- Analytics strategy & requirements
- Connectivity & security
Outcomes
- Readiness and maturity assessment
- Infrastructure inputs into planning
- Engagement scope
Deployment Planning:
Activities
- Evaluate data and analytics strategy
- Data lake infrastructure review
- Enrich data lake with additional sources
- Architecture review
Outcomes
- Reference architecture
- Solution features
- End-to-end engagement plan
Deployment Execution:
Activities
- Security (implement firewalls & data security)
- Establish connectivity
- Implement solution (onboard sites in waves)
- Test and optimize
Outcomes
- Implemented solution
- Deployed use cases
- Compliance & governance
Visit the AWS Solutions Library so you can learn how to get started with Renewables Data Lake & Analytics and other solutions for the energy industry.
Solution Partners
Get started
