How to get data from the edge in a way that’s scalable (and actually do-able)
Posted: April 18, 2023
A recent global survey of operations and IT decision-makers shows that 94% of their organizations are at least planning to use industrial edge solutions in their operational activities. But even though industrial companies clearly understand just how valuable data from the edge can be, only about 1 in 10 organizations have actually entered advanced production of edge solutions. So, AVEVA is helping companies meet the challenges that have been keeping them from getting the edge data they want.
Typically, the industrial edge refers to local networks for remote assets. Those assets are often in widely distributed and unstaffed environments with unreliable connectivity. So, even if you don’t have remote assets, you can still think of your industrial edge as just including assets with data that’s difficult to access or manage.
Organizations often encounter multiple challenges when creating solutions at the edge:
- High costs for replacing or updating legacy IT infrastructure, along with even more costs for implementing new software and storing data.
- Mitigating risks concerning data loss, controls, lifecycle management and security.
- Lack of understanding about edge data and related technologies.
Enel, the world’s largest private player in renewables, is overcoming those challenges. The company described its edge journey in its AVEVA PI World Amsterdam 2022 presentation. No longer settling for data just from generating units, Enel’s analysts set their eyes on data from pipelines, aqueducts, wells, weather stations, individual photovoltaic panels, and more.
After Enel established AVEVA™ PI System™ as its cross-technology platform for data collection from all its plants, the global enterprise turned to some of AVEVA’s edge data collection solutions for solving three edge problems.
Enel wanted to expand its solar plant analysis to incorporate angle data for each individual solar panel. But that data would take as many as tens of thousands of streams at each plant—up from the mere hundreds of streams the existing network had been collecting from solar inverters. Sending that much data would burden Enel’s existing network. Improving network links would require excessive time and costs.
So, Enel installed AVEVA’s lightweight Edge Data Store software on its existing infrastructure, eliminating the need for additional hardware. Edge Data Store collects data from the individual panels, stores the granular data, and lets Enel apply custom aggregation scripts via REST API. It enables egress of just the aggregate data across Enel’s network and into the company’s existing AVEVA PI Server. Edge Data Store enabled the granular analysis Enel desired, while requiring fewer resources and deploying faster than alternatives.
Enel’s hydro- and geothermal power generation plants have many pipelines, aqueducts, wells and weather stations. Enel hadn’t collected data from these assets because the plants all had individual datalogger systems with no consistency from site to site. But then Enel saw how it could use AVEVA software to collect and aggregate data from those disparate assets.
It installed low cost IoT sensors on the assets and configured them to send data to an MQTT broker on an edge device. On the same edge device, Enel installed AVEVA Adapter for MQTT, which subscribes to the MQTT broker and sends all the sensor data to Enel’s existing AVEVA™ PI Server. Enel characterizes this simple and lightweight architecture as a proven, cost-effective, easily integrated, and scalable off-the-shelf solution for standardizing remote data collection across existing and new plants.
Enel has a global architecture with many different departments running many different network, hardware, and software components. The inevitable failures and maintenance activities required for this size of an organization can affect data flows. To mitigate interruptions, Enel’s Digital Hub team developed a data collection backup strategy.
Previous manual methods had proven too expensive. So, Enel installed AVEVA Adapter for OPC UA on existing servers alongside its existing data collection technology. When a user needs to recover data, they define an interval for recovery and Enel’s centralized queue management service, along with a custom script, communicates the interval to AVEVA Adapter for OPC UA. The adapter then provides the data from during that interval from Enel’s AVEVA PI Server. Enel can now flexibly recover data from a centralized environment without the need for different VPN connections or additional infrastructure.
Enel’s successes demonstrate that AVEVA provides proven, cost-effective, easily integrated, and scalable edge solutions that require fewer resources and deploy faster than alternatives. And that’s before AVEVA’s most recent release, which now combines the edge technologies above with other AVEVA solutions.
This new release will help you easily and securely deploy data collection, storage and local data access at scale—as well as manage the lifecycle of the software and its configuration all from a centralized location, managed by AVEVA. We at AVEVA understand that manually deploying software on your assets at scale can be expensive and time-consuming. We understand that you need reliable, manageable and affordable access to your company’s remote data.
Register for the webinar Hybrid industrial data management: remotely collecting operational information at scale to learn more.
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