Data-Driven Edge Critical to the Modern Energy Environment

Utilities modernizing their operations need 5G and edge processing to help make sense of and reduce the large volumes of data generated by IoT and other smart devices.

The modern energy company environment today often must incorporate renewables and distributed generation into existing generation, transmission, and distribution environments. Increasingly, energy companies are looking to edge technologies and 5G to better measure, monitor, and manage these complex environments.

Why the need for better data-driven insights? Energy companies must manage complicated, constantly changing supply patterns. They must predict the maintenance needs of millions of geographically distributed generation points. They must also understand energy usage at a granular level through intelligent connected meters.

Data captured, delivered, and analyzed from edge initiatives can also help change the business model of modern energy companies. For instance, they might use the data and insights to incentivize changes in consumer demand. For example, they might offer and support ‘time of use’ tariffs and smart appliances, which automatically operate at times of lowest demand. Or they might augment generation infrastructure by returning excess energy from consumers’ wind turbines, solar panels, and electric vehicle batteries to the grid.

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Energy edge applications abound

Two elements are essential to modernize the operations of utilities. They need high capacity, low latency data communications on a vast scale. And they need ubiquitous edge processing to help make sense of and reduce the large volumes of data generated by IoT and other smart devices.

When these two elements are present, there are multiple innovative applications. Some edge use cases we’ve highlighted in the past in our energy industry coverage: include:

See: Real-time AMI Data Helps Utilities Anticipate Power Needs

Advanced Metering Infrastructure (AMI), featuring technologies like smart meters and distributed intelligence (DI), helps utility providers more accurately measure how much and when energy is consumed. Analysis of such data enables more accurate short-run forecasts as well as the long-run energy usage by day and time of day. This helps to ensure there is sufficient generation and transmission and distribution infrastructure to meet demand.

In addition, DI can provide deeper insights into grid edge transactions such as solar power generation and distributed generation. This enables utilities to track power generated by consumers who have installed solar panels on their homes or businesses to offset electricity costs. These consumers can sell excess solar power to other consumers to reduce the strain on power plants and the electricity grid.

See: 5G Connectivity Enables Smart Power Substations

A UK smart power substation design aided by 5G connectivity could help save over 63,000 tons of CO2 by offering more efficiency than traditional substations. The substations will fit into the puzzle between smart control rooms and smart chargers, allowing UK Power to control and optimize each component of energy delivery. 5G enables on-device processing and reduces latency in communication, allowing devices to connect in power and processing in efficient ways not previously possible.

See: Energy and Utilities Fighting Disruptions with Data

Predictive analytics is largely untapped in the utilities and energy sector, but not for long. Energy is no longer linear. It now employs a complex spiderweb of systems, everything from intelligent distribution grids to smart meters in homes. Some organizations are using sensor data embedded in transformers, allowing them to monitor and employ predictive maintenance. Others are analyzing data from customer behavior and smart meter usage to predict which ones are likely to fall behind on paying.