Data Analytics for Utility Communications Networks
President Harry S. Truman said, "There is nothing new in the world except the history you do not know." Knowing how complex data management challenges have been resolved in telecom by means of advanced analytics will help bring smart grid benefits to utilities and consumers.
The smart grid adds complexity to grid operations. Nowhere is this more apparent than in the outfitting of the power distribution system with communications capabilities. But complexity, from a management perspective, does not have to be complicated. Data analytics solutions have proven to assist telecom network operators in managing hybrid communications networks as well as the multiple suppliers providing equipment and bandwidth for their networks.
Every distribution grid, regardless of size, is complex, dynamic and mission-critical. Many such grids are undergoing profound changes as they are transformed by information and operations technologies. The grid must deliver power reliably, safely, and cost-effectively, It also requires reliable and cost-effective performance from the communications networks that monitor, collect, process and control remote equipment and devices. Managing and making sense of all the data from all the new devices in a smart grid, combining electrical distribution and communications is a significant challenge for utilities. This can only be reached through solutions that can correlate, integrate and analyze data to manage network and grid performance.
From a data analytics perspective, the distribution grid has some common characteristics with wireless service provision. Wireless companies have networks that are arguably even more complex than power grids with large numbers of devices that combine voice, data, and video in different and sometimes very elaborate subscription plans. At the present time, in contrast, we all typically get the same electricity service and consume kilowatthours with little variability in rates.
What can we learn from communications service providers about managing hybrid communications networks and multiple vendors? For answers I turned to Bob Becklund of PreClarity Utilities, a company located in Reston, Va. that is well-versed in advanced data analytics for communications service providers and retail business sectors.
Utilities typically have a variety of communications needs that cannot be addressed with one communications solution. Permutations and combinations of wired and wireless communications channels serve different applications or operational needs in existing utility communications networks; from that point of view, the smart grid will just be more of the same hybrid networks.
Probes and self-monitoring network elements can provide quality-of-service and bandwidth data to more effectively manage smart grid communication networks. By collecting, trending, summarizing and analyzing detailed network routing, network reliability and network performance statistics, issues involving multiple networks and capacities for growth can be centrally monitored and managed.
Carriers and other communications service providers already use comprehensive advanced analytics coupled with network topology details and a solid strategy for performance data generation, collection and processing. These analytics are used to determine how network traffic can be prioritized, route-optimized and dynamically managed to ensure timely delivery of critical data and improved, low-cost bandwidth management for latency-tolerant critical data.
Data analytics drives down costs and improves service delivery quality for telecommunications providers, and can do the same for utilities managing similarly complex networks.
Utilities not only have diverse communications networks, but they also have a range of vendors supplying equipment for their power and communications networks. While many utilities negotiate comprehensive and detailed service level agreements with their suppliers, they lack the tools to track these agreements against actual performance. The costs and reliability of public networks have been common concerns for utilities when considering use of public networks for their communications.
The use of fact-based vendor service statistics enable utility companies to verify vendor compliance claims as to performance and procure future power or communications assets based on actual historical fault and service trends. Mirroring best practices from the enterprise network and telecommunications industries, the analysis of failure statistics and performance can effectively reduce costs, enable prudent future equipment procurement choices and help achieve lower costs and less down time. Given the millions of assets that utilities will continue to deploy in smart grid buildouts, the cost-saving possibilities of minimizing failures through predictive asset management and statistically managed component quality achieve real eloquence on balance sheets.
Utilities are well-served to learn from experiences gained in similar business sectors and start at the top of the learning curve instead of the bottom when it comes to understanding and deploying data analytics solutions to optimize operations. The results will lead to much higher confidence in both the private and public networks while providing more cost effective and reliable grid operations and asset management.