The Biggest Obstacle to Your Renewable Strategy? Your Data

Jaime Crawford's picture
Partner PwC

Jaime Crawford is a Partner at PwC focused on delivering geospatial solutions to the power and utilities sectors.   In this role, Crawford focuses on the delivery of innovative solutions to...

  • Member since 2022
  • 4 items added with 4,115 views
  • Apr 11, 2022

I had the pleasure of being a guest on a recent episode of Energy Central’s Power Perspectives Podcast where I discussed the impact that location intelligence is starting to have across nearly every aspect of utilities’ operations. In that episode, “Are You Overlooking a Critical Tool for Solving the Most Pressing Challenges Your Utility Faces?” host Jason Price, producer Matt Chester and I discussed how so many of the most urgent challenges facing utilities can only be solved if they are tapping into the power of geospatial technology and location intelligence. That includes decarbonization initiatives that utilities are implementing in order to respond to climate change, to comply with regulatory mandates at the state and federal levels, and to serve increasingly-sustainability-minded consumers.

That discussion with Jason and Matt was a wide-ranging one that covered everything from predictive maintenance to employee safety to wildfire prevention. But Energy Central has asked me to do a deeper dive into one of the topics that came up and that a number of readers have asked about: the role of location intelligence in the deployment of renewables. Every reader of Energy Central knows that deploying, tracking, managing and maintaining distributed energy resources is a complex undertaking, particularly at scale. That task is challenging enough for centralized energy infrastructure. It is far more complex when those assets are distributed across a utility’s geography and operating as part of smart grid deployments.

Location intelligence has an indispensable role to play in these renewables programs. That is because these programs do not just run on sun, wind and hydrogen. They run on data – specifically location data. The simplest definition of location-based data is any piece of information that includes a physical address or GPS coordinate. Eighty percent of the data that utilities have in their systems pertains to a physical location on the surface of the earth (or even under it or towering high above it). That becomes clear as soon as you start rattling off the kind of infrastructure and work that utilities do. The location and status of electrical transformers. Service requests from consumers. Field reports from workers doing maintenance. The vast majority of the information that utilities work with is location data. That rises to 100 percent of the data for renewables programs because of the distributed nature of those assets, the networks that connect them, and everything required to manage, monitor, inspect and operate them.

Everything in renewables programs runs on location data, but there’s a problem: many utilities have massive data problems that are guaranteed to undermine their renewables programs if they don’t take action. These data problems typically include most or all of the following challenges:

  • That data is often siloed in areas of the organization that are walled off from each other with little to no communication and coordination

  • The data is often trapped in not just siloed departments, as noted above, but also in systems that are not interoperable or connected to one another

  • Existing data needs to be more granular and more spatially accurate 

  • This internal data often lacks information that is readily available from external sources

  • The GIS system is too complex for all but a few geospatial experts to use

  • The data, once aggregated, is too overwhelming to effectively analyze using the patchwork of existing software

  • The actionable insights that are generated often fail to be distributed to the teams that can benefit most from them

  • And these systems are unable to provide visibility into, and measurement of, whether location data is having the impact that it should

If your organization puts a checkmark next to any or all of those data issues, you’re not alone. The vast majority of utilities have these challenges. These are common, which is exactly why this is such an urgent issue for renewables programs that rely on this data for every aspect of their operations, from the very first steps of site selection to day-to-day operations to load planning to outage responses to strategic roadmapping of future DER deployments. These data problems stand in the way of all of those aspects of renewables programs.

To remove those obstacles, utilities need a location intelligence strategy that systematically addresses each of those problems with a strategic approach to collecting, analyzing and generating actionable insights from location data that they generate internally and have access to externally. The first step is to do a full accounting of the location data that currently exists in silos across your organization as well as the competing GIS and computing systems that currently manage that data. Aggregating, cleaning and integrating those data sets paves the way for a unified software strategy that can combine that internal data with a wealth of open-source external data that augments the information your renewables program can derive insights from.

That ocean of accurate, reliable data can then be translated into actionable information using location intelligence software that utilizes AI to guide decision-making. That software is light years ahead of past GIS in terms of how usable it is by non-experts, allowing every team involved in renewables programs to work with the insights to do the job of deploying, managing and maintaining renewables resources. This puts the power of location intelligence into the hands of anyone with a smartphone or a laptop, paving the way for dramatically broader use of these insights in the office or in the field. This also provides all of the real-time data that consumers expect to have access to be informed and empowered about their energy usage.

Putting this kind of location intelligence strategy into action will solve each of the data challenges that pose such serious challenges to renewables programs. It also provides exactly the kind of foundation that utilities need to expand their renewables programs and make measurable progress toward their Net Zero goals for decarbonization.

About the Author

Jaime Crawford is the Senior Vice President of Strategic Industries at Locana (formerly Critigen), a location and mapping technology company whose software products and services solve the world’s most pressing infrastructure, sustainability, business, and social challenges. In this role, Crawford focuses on the delivery of innovative solutions to industries such as utilities where location intelligence is poised to have a dramatic impact across every aspect of the market. She has more than 20 years of experience in location intelligence, including her time in this leadership role at Locana/Critigen and at PwC where she led its GIS practice for power and utility clients. She has also worked closely with strategic clients in prior roles at CH2M Hill and at Esri. She also taught GIS at the University of Washington for nearly a decade, training the next generation of geospatial professionals. Crawford is based in Seattle and holds a Bachelor of Science from Western Washington University and a Masters in Environmental Science (GIS emphasis) from the University of Charleston.

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Matt Chester's picture
Matt Chester on Apr 12, 2022

Everything in renewables programs runs on location data, but there’s a problem: many utilities have massive data problems that are guaranteed to undermine their renewables programs if they don’t take action. 

Does this at least present the silver lining that perhaps it's easier to integrate new data practices as more renewable assets are deployed (compared with fixing the data issue for already installed projects)?

Jaime Crawford's picture
Jaime Crawford on Apr 14, 2022

Yes there is a silver lining!  If you adopt new data practices you can start collecting information on renewable assets now.  You don't have to wait, small steps now can result in a big pay off later.

Paul Gwaltney's picture
Paul Gwaltney on Apr 12, 2022

Great article.  An additional challenge I've seen with geospatial data is that utilities operate on large time-scales, our infrastructure is installed and operational over decades of service life.  Systems and data availability can change dramatically over that time period and it's not always easy to migrate or maintain compatibility.  This is also complicated by digital roadmaps that may project 5 years out, when systems and infrastructure can last another 15-20 years.  Digital strategies should encompass this long view.  I'm also interested in the use of AI and automation to help overcome the data challenges.  Of course, digital technologies also change at a rapid pace and the right strategy should include shoring up your data across the organization, but remaining agile on top of that. 

Jaime Crawford's picture
Jaime Crawford on Apr 14, 2022

Thanks for the thoughtful comment Paul.  Since utility assets are in service for decades we also need methods for monitoring the heatlh of the asset and updating changes to the asset over time.  We need to make sure the asset is captured when it's put into services, but also updated during routine inspection and maintenance work.  There are great solutions out there that combine field work management sytems with mobile GIS to keep asset data up to date.  I also like the idea of AI for both data cleansing and predicting asset health and risk.  The exciting part is that the technology exists today to accomplish these outcomes.

Jaime Crawford's picture
Thank Jaime for the Post!
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