Utilities are facing an increasingly complex power delivery environment, with the need to incorporate renewables generation, electric vehicles, and complex demand response programs into their service area operations. In response, many are expanding their smart grid strategies to take advantage of new technology and software that can increase the understanding of grid dynamics and improve its efficiency and costs:
- There is a growing requirement to make use of the cross-application functionality that a truly integrated smart grid environment can deliver. Examples include the ability to incorporate smart meter end user voltage readings into DMS and OMS systems, or using the same data to trigger events and generate transaction requests for asset management and work order management systems.
- New analytics techniques and control applications are rapidly emerging, with the promise of developing actionable information from existing data streams without adding new banks of sensors or communications infrastructure.
It is true that lower-cost, smarter end-point devices, such as PMUs, are proliferating and are now capable of collecting orders of magnitude more useful operating data. Today’s challenge is that we have now also reached the point where it is becoming impossible to economically collect and process this vast amount of data in a central location for use by the many applications that need it.
This problem, identified as data gravity, applies across the entire Industrial IoT. As more and more data is collected at the edge devices, the data mass’ center of gravity swings away from the center toward the edge of the IIoT. Fortunately, Moore’s Law is also working for us, and the cost of appropriate, powerful industrial devices has been reduced to the point where multiple years’ worth of sensor data can be stored locally in a device costing less than a SCADA RTU. What is also needed, however, is a means of capturing that data and making it transparently available to the control and analytics applications that can use it. The capture-curate-package-deliver functionality that is required has to be provided on the edge devices, but also present the data requested to the central systems regardless of storage location or connectivity—making it look as though it is in the next server rack down.
This post is part one of a three-part series from Exara. Subsequent postings in this series will explore the detailed requirements of such an edge data services platform and how it can be incorporated into a utility’s smart grid strategy. In the meantime, please feel free to submit any questions through this blog.
About the author: Roy Hodges is an industry consultant for Exara, Inc., with 10 years’ experience working in communications and software solutions for smart grid and digital oil field deployments, both in the US and internationally.
Exara is an Intel Partner that has developed the world’s first edge data services platform for the Industrial IoT. The Exara platform is delivered on Intel®-based edge servers that can be deployed in substations, electrical plants, and many other industrial environments. For more information, please visit Exara's website.