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Managing data overload in the smart grid

Collecting data from the smart grid generates a wealth of data. Or an abundance of data. Or a cascade of data. Perhaps even a virtual explosion of data, or a data avalanche. Or simply information overload, depending on how the data is collected and structured.

The answer to data overload is a distributed approach. More on that later.

Treated correctly, raw and unstructured data from the grid can be converted to invaluable information. Continuous and reliable access to the data is an essential feature of the smart grid. But with embedded intelligence, end points in the field provide massive amounts of data on localization, sensing, control, identification, etc. – data that needs to be gathered, verified, stored and analyzed for intelligent decision-making.

The abundance of data is truly what makes the smart grid smart:

  • Data can enable more accurate predictions and reduce outages
  • Data can provide better insight and prevent failures
  • Data can enable informed decision-making
  • Data can help align demand with supply
  • Data can improve operational efficiency
  • Data enables utilities to integrate renewable energy assets into the grid

But how do we ensure that we only collect data that is actually needed, instead of choking on massive amounts of irrelevant information? We are creating data bottlenecks and diluting the value of data abundance, rather than focusing on retrieving the data that we need, and leaving the rest behind to be retrieved later – if we need to.

What utility companies need are intelligent solutions that efficiently retrieve and store data in an automized process, without creating data overload.

Amplex uses a distributed approach in all our smart grid solutions – in fact, we have been using distributed intelligence for more than a decade. We store data locally, on CPUs that can handle frequent collections from end points, and make that data available upon request from the control room.

We don’t clog up communication lines by sending data that might never be needed. Instead, we instruct the CPU to send only the information that the utility company has deemed relevant and necessary, and thereby keep data volumes and complexity levels down, without compromising the quality of the data collected.

This is truly a distributed approach, and it will change the way we handle the massive amounts of data created by the smart grid.

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