How edge computing is driving smart grid responsiveness and resilience

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Today’s electrical utilities are rapidly transforming into smart utilities. Utility companies are digitizing the control of the electricity distribution network to improve responsiveness, efficiency, and resiliency. Smart utilities leverage data and analytics to make better decisions on delivering electricity and tapping into sustainable energy sources. Yet, these utilities need quick access to quality data to make good decisions. This is where edge computing comes into play.

How edge computing makes smart grids smarter

As electrical utilities evolve and digitize their operations, the new smart infrastructure requires a boost in data processing. Edge computing solves this issue as it provides physical computing and storage infrastructure near where data is generated. In addition, by combining edge computing with smart grids, utilities gain several advantages that help increase their power networks’ reliability.

smart grid and edge computing

Lower data latency

Within the last few miles of their transmission networks, utilities convert very high-power voltages into medium and lower voltages that are safer for customers. Elements such as frequency control play a significant role in ensuring the power supply is stable enough for end-use. Other variables, such as power factor, must also be controlled to avoid safety issues and regulatory penalties. Under such scenarios, the responses of smart grid technology must be immediate. By placing edge computing power along the utilities’ distributed substation networks, latency is mitigated, and data flows back and forth much faster than if the network were dependent solely upon physically distant cloud servers.

Minimize risk of data privacy breaches

With digital technologies integrated into smart grids comes the risk of data breaches. For example, with smart metering, private customer information is shared over networks. This data is particularly vulnerable when using the cloud for storage and transmission. In addition, cloud data can reside anywhere, and, in some cases, for privacy reasons, countries, regions, or states may have laws requiring data to remain local without crossing any borders. Edge computing can reduce data privacy risks by providing data storage and processing at the source, keeping the data local to comply with regional data privacy regulations.

Better management of big data

Digitized smart grid devices are generating unprecedented quantities of new data. As a result, network bandwidth has become a constraint to a utility’s ability to respond quickly to customer issues (like rapid recovery from power outages of electrical systems after extreme weather events). In addition, high expense and inefficient use of resources present obstacles if all of this data is hosted in the cloud. Edge computing addresses this challenge by improving data processing and transport times and increasing the availability of data when and where it’s needed.

Edge computing’s role in renewable energy

Utility companies have made a lot of progress utilizing more renewable energy sources such as wind and solar. However, these utilities must mitigate the unpredictable nature of these resources due to weather fluctuations.

Edge computing can quickly process local data to manage fluctuating demands as well as mitigate the impact of renewables-driven variable generation. The integration of microgrids and energy storage also requires AI and analytics-based smart grid intelligence to better manage the complexity of what is now a two-way grid (power flowing from the utility to the users and power flowing back from users to the utility).

The application of edge computing solutions for smart grid operations is in its early chapters but poised to enable utility companies to better adapt to market demand shifts as well as tapping into renewable energy sources. To learn more about how edge computing can increase the IQ of smart utilities, access the grid data management resource site.

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