Navigant Research Blog

Clearing the Data Hurdle for Effective Asset Performance Management

— June 9, 2017

Few in the utility industry today disagree with the notion that technical advances in terms of sensing and analytics are yielding powerful new solutions for asset performance management (APM) and predictive maintenance. Many would also agree, however, that there are challenges for utilities ready to digitize their asset management program. Indeed, finding, consolidating, mapping, cleansing, and storing the data from a multitude of sources can seem like a daunting challenge.

Best practices are emerging as major utilities take the APM plunge, and meaningful benefits to holistic APM strategies are now clear. One transmission operator, for example, has avoided five major transformer failures since the implementation of its APM program—and said that “just one or two saves paid for the system.”

With growing emphasis on reliability from regulators, aging infrastructure, and accelerating workforce retirement at utilities, the need for a utilitywide APM program has never been greater. Understanding the data challenges utilities are likely to face is an important first step to putting a plan in place.

Who, What, Where, When, and Why?

When preparing to deploy an APM solution, the five Ws should be asked in the context of company assets and data:

  • Who: Which operating divisions house data needed for the desired analytics? What institutional knowledge is held by which actors? How can it be incorporated into the APM system for preservation? How do IT and operational personnel coordinate efforts?
  • What: What datasets exist today? In what format? Electronic or paper-based? Is the data accuracy good? Is it verifiable? Are there new datasets that need to be developed?
  • Where: Where has asset data historically been housed? Where should it be stored going forward? Do I need a data lake? Can I store my data in the cloud? How should the transition be orchestrated? Is there data available in the field that is not communicated to the operations center? Should asset analytics be performed centrally or in the field?
  • When: How often should asset data be updated? Is there connectivity to the asset, allowing for real-time or on-demand reads?
  • Why: For what applications do I need this data? For what applications might I want the data in the future? What are my primary goals for the APM system—reducing maintenance expenses with proactive repairs and replacements? Reducing outage frequency/duration? Shoring up grid stability where solar penetration is high and growing? All of the above?

As the APM planning team drills down into each of these questions, new questions will become apparent. Testing and validation of analytics algorithms must be thorough and must be completed on an ongoing basis—rather than one and done. As new data becomes available, adjustments may be needed due to previously unforeseen situations.

Is It Worth It?

It’s still early days in the APM world, but clear benefits have been reported by utilities that have done pilots or full-scale deployments. As more utilities invest in APM solutions, it seems likely that the benefits—in terms of avoiding unnecessary repairs, preventing outages, averting capital investment, and efficiently managing field crews—will become apparent. New applications that can be created with a robust, agile APM platform and complete, quality datasets will also emerge.

Join the Webinar

If you’d like to learn more about the nitty gritty details of the APM world, attend the Navigant Research webinar, The Digital Future of Asset Performance Management. Join me, ABB’s Matthew Zafuto, and FirstEnergy’s Dana Parshall for an interactive discussion of the data challenges and lessons learned in FirstEnergy’s implementation of ABB’s Asset Health Center solution.

 

How Will Self-Driving Vehicles Find Their Way?

— January 8, 2015

Google continues to push the technology for its autonomous vehicle, but some recent articles in the media have been more about the detailed mapping required than any of the other technologies that may be necessary for bringing such vehicles into production.  Google is not the only company interested in this angle.  Nokia’s HERE subsidiary is also putting a lot of effort into making high-definition maps that combine detail about roadways with information about traffic flow.

Google has decided that its vehicle must have a detailed map of the roads it will travel on, accurate to a few centimeters, with detailed knowledge of the exact location and height of the curbs, not just the lane markings.  Recognizing that these vehicles must also cope with construction and temporary obstacles, HERE is exploring the idea of using the cloud to store the digital map data and having it updated on a continual basis.

A Perfect Map

The concept relies on huge amounts of data being constantly uploaded and downloaded to the cloud so that all vehicles always have a highly accurate digital map of their surroundings to rely on.  While this is clearly one potential solution for the future of autonomous vehicles, it’s a concept thought up by two large companies that have already invested heavily in scanning and mapping technology.  It’s natural to find solutions that match the tools already available, and all the better if the solution requires a tool upgrade.

In a previous blog, I wrote about self-driving vehicle developments in China.  It seems to me that putting more intelligence into each vehicle, to deal with real-time traffic issues, is a more practical option than requiring a highly accurate database of all the world’s roads that is updated minute by minute.  Existing digital maps can be used to provide direction just as they do for human drivers today, and powerful, intelligent sensors can monitor the local traffic and obstacles in real time.  I suspect this is how the major automakers are moving forward with autonomous vehicle technology – and why nobody has yet jumped on Google’s offer of a partnership.

 

Utilities Poised to Join Enterprise Cloud Migration

— January 8, 2015

According to a study released by Infosys in November, more than 80% of large organizations are either using or planning to use cloud-based, mission-critical applications over the next 2 years.  Here at Navigant Research, we believe that trend is now extending to electric power utilities, as described in our white paper, Smart Grid: Ten Trends to Watch for 2015 and Beyond, also released in November.

Infosys and Forrester Consulting surveyed more than 300 technology managers and business decision-makers from the United States, Australia, and Europe.  Key findings included:

  • 77% of respondents are either using or planning to use Internet as a service (IaaS), platform as a service (PaaS), or software as a service (SaaS) for a wide range of business applications.
  • 66% of enterprises agree that they should prioritize developing a comprehensive cloud strategy for their IT infrastructure.
  • 70% of businesses want to work with a cloud implementation provider that offers a single point of accountability.
  • 66% of companies are either concerned or very concerned about the complexity involved in managing and governing a hybrid cloud environment.
  • 83% of the cloud adopters surveyed are struggling to consolidate their cloud services – from IaaS, PaaS, and SaaS and from public and private clouds.

The survey also found that agility – rather than cost savings – is now the dominant driver for cloud adoption.  The full report can be found here.

Smart Grid in the Cloud

In Navigant Research’s white paper, we observed that smart grid as a service (SGaaS) is now moving from hype cycle to real world product, driven by the growing complexity of smart grid applications, a dearth of qualified IT professionals at all but the largest utilities, and increasing understanding on the part of utility execs that they may benefit by sticking to their knitting (i.e., keeping the lights on).  Itron, General Electric, ABB, and AT&T have all moved decisively into the SGaaS space over the last 18 months.

From a vendor perspective, the SGaaS model is appealing because it generates recurring revenue, which can help smooth out the ups and downs of direct sales.  Navigant Research expects that the market for managed utility services will grow from $1.7 billion in 2014 to $11.7 billion in 2023.  (For additional analysis and detailed forecasts for the SGaaS market, see Navigant Research’s report, Smart Grid as a Service.)

Annual SGaaS Revenue by Category, World Markets: 2014-2023

(Source: Navigant Research)

 

Using Applications to Empower Smart Cities

— December 9, 2014

In late November, the crowdsourced smartphone app Waze released a stunning visualization that showed the traffic flowing through New York City on a recent September day.  Resembling blood flow though a body, cars move through the arteries and veins of city streets and highways, slowed by both collisions and general congestion.  Waze collects data via smartphone owners that allow their location (and speed and direction) to be captured and aggregated, providing real-time information on traffic in a city.  When using Waze, drivers can be alerted to new incidents like accidents and police on the road, and the app can even suggest new routes for a faster ride.

Crowdsourcing apps like Waze, ridesharing apps like Ridejoy, and home control apps like Nest may also be a boon to some of the smart city initiatives being developed and planned worldwide.  Numerous cities in the world are adapting IT for their infrastructure and streamlining operations for their departments.  Navigant Research’s report Navigant Research Leaderboard Report: Smart City Suppliers identifies the promising companies that have demonstrated advanced approaches and penetration in this sector.  Most smart city initiatives begin with public transportation and traffic monitoring, as they are critical services for citizens, and promote commerce as well.

Short on Cash

There’s a basic challenge for cities that want to pursue programs like these, though: limited municipal funding.  In the first world, or in a few examples in the developing world, cities have signed multimillion-dollar contracts, paying large IT and equipment companies for equipment and consulting services for smart city initiatives.  These large price tags limit the adoption of (large) smart city programs in the developing world and in smaller cities and towns.  Crowdsource apps could provide a solution.

If the data from crowdsourced apps like Waze could be shared with municipal agencies, data limitations would virtually disappear.  Instead of paying millions for a full service solution, a city could hire a cadre of data analysts to examine the trends in traffic, identify collision hot spots, and use the aggregated data for long-term traffic planning, supplanting expensive traffic studies.  One example of an interesting use of this kind of data is New York University’s (NYU’s) visualization of taxi rides in New York City.

Taxi Confidential

Using data from the Taxi and Limousine Commission, NYU researchers created a rich queryable database where taxi demand is revealed visually, and the impact of major disruptive events like Hurricanes Sandy and Irene on taxi rides can be understood (namely, that few taxis ventured into the power-less regions of lower Manhattan).  MIT has, in turn, developed an interactive website using the taxi data to demonstrate the value of ridesharing.   The academic insight has yet to be used for city policy, but as the analysis improves, such applications will surely follow.

Certainly, there are obstacles with this approach.  The first is privacy.  Aggregated urban mobility data can be anonymized.  Yet, the idea of governments gaining access to individual citizens’ whereabouts, regardless of the source of the data, may make a fair number of people uncomfortable.  Open questions prevail: Could mobility data be used for forensic purposes?  Since Waze is owned by Google, what other information could be associated and shared?  These questions and many others will have to be addressed through real deployment.  As has been seen through companies like Uber, which is now causing taxi medallion prices to fall, disruptive technologies can shake up the status quo.  City governments have not traditionally been the locus of innovation, but the smartphone in your pocket may change that in the near future.

 

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