The EDF Group is one of the world’s largest utilities companies. Active in 22 countries with operational assets in 15, EDF has more than 150,000 employees and 37 million clients worldwide. EDF’s goal is to supply safe, clean, and affordable electricity. Their offers aim to help individuals better control their electricity consumption, support companies’ energy performance, and put sustainable solutions in place for local communities. EDF Renewables (EDFR) is the EDF Group’s dedicated affiliate focusing on renewable energies, including wind, solar photovoltaic, and storage with activities in over 20 countries worldwide.
EDFR’s solar panels and wind turbine generators are equipped with sensors that collect data on power output, temperature, wind direction and speed, irradiance, and other relevant conditions.
This streaming data totals more than 3 million tags coming from operational assets in 15 countries across 5 continents and is stored in an array of forms including the OSIsoft PI system. Prior to migrating to Amazon Web Services (AWS), these systems were supported using on-premises hardware. EDFR needs to be able to bring their data into a repository, efficiently and cost-effectively.
“The energy industry is in transition. The way that we generate renewables is changing. Our customers want energy when they want it, in the shape they want it, and with more transparency,” says Damien Buie, chief digital officer at EDF Renewables.
“We need to provide the value of data to our customers, and to do so, we need to be able to adapt and to understand with more precision how our assets operate. We need to understand how customers want their energy delivered and what risks our customers bear so that we can provide a better service at a lower cost point.”
To achieve an increase in stability and visibility, EDFR determined to push the data contained in their OSIsoft PI System data lakes to a centralized storage framework. With these aspirations in mind, they decided that a cloud-based architecture was the optimal solution.
After assessing several cloud providers, EDFR chose AWS due to its maturity in the cloud space, its breadth and depth of services, and its intense customer-focus, a trait they share with AWS. They were also already running some workloads on AWS, including business intelligence systems using Tableau and TRUalytics and were impressed with the level of service AWS was providing for them, making it an easy choice.
When EDFR told AWS that they were looking to drive richer insights from their OSIsoft PI System data, AWS engaged APN Premier Consulting Partner 47Lining, a Hitachi Vantara Company. 47Lining had previously executed a proof of concept with EDFR, which demonstrated the value of an AWS-based data lake for EDFR’s industrial process data from other supervisory control and data acquisition (SCADA) systems. Based on this engagement, and others with organizations in the oil & gas, mining, and manufacturing industries, 47Lining was able to understand the common requirements that these organizations shared. Most were using on-premises historians, such as the OSIsoft PI System, but were searching for a way to easily connect this data to the cloud. This insight enabled 47Lining to build the AWS Industrial Time Series Connector Quick Start, a “data bridge” that connects OSIsoft PI System industrial time series data to AWS.
Since this Quick Start was already built, the next step was to understand EDFR’s more specific requirements and get their AWS solution production-ready. EDFR was very comfortable using standard SQL to run queries on their PI System data lake and maintaining this capability on AWS was key. The connection was established, and the system was functional in 12 weeks—an aggressive timeline, but one that was achievable due to close alignment between 47Lining, EDFR, and AWS. Through this process, 47Lining also helped EDFR get familiar with running this system on the cloud, giving them confidence to operate it post-implementation. EDFR’s industrial process data lake on AWS leverages Amazon Simple Storage Service (Amazon S3) as a central repository for all the sensor data coming from their wind turbines and solar panels.
This gives them scalable, reliable storage infrastructure that can handle heterogenous data with ease. To move the data from their highly geographically distributed assets into this environment, they leverage Amazon Kinesis Data Streams in a steady state. Amazon Redshift is also used as an enterprise data warehouse to complement their Amazon S3-based data lake.
Now that EDFR has their PI System data bridge in place, they can leverage the AWS global infrastructure to easily transfer data from their solar panels and wind turbines into the cloud in a centralized framework, with much greater transparency and stability than on-premises. None of the institutional knowledge they have developed over several decades in operation has been compromised—they’re still able to use the BI tools they’re familiar with and standard SQL. Their AWS data lake empowers them to drive insights that help reduce costs, drive new revenue, and provide greater transparency into their valuable assets.
“The numbers we’re talking about are challenging. One of our data lakes is over 2 million PI tags. We want to stream a lot of data into these environments,” says Buie.
“With 47Lining and AWS, we’ve been able to demonstrate that under a steady state. We will continue to mature our Data Lake environment to take advantage of more of the features embedded in the OSIsoft tool, and the rich feature set provided by AWS. We’ve had a very successful engagement with 47Lining—they’ve helped us a lot. They’ve been reactive, supportive, and competent.”
EDFR is continuing to investigate new ways to tap into the broad portfolio of AWS big data and analytics services to better meet their customers’ changing expectations and remain a leader in the renewables space.
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47Lining delivers big data solutions and managed services to support businesses. Focused on enterprise-managed data lakes, data warehousing, predictive and real-time analytics, machine learning, and IoT, the company's experience accelerates time to value in industrial, oil & gas, mining, energy, life sciences, gaming, ad tech, retail analytics, financial services, and media & entertainment industries.