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How GIS is helping power companies enhance their financial performance & optimize their systems

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It’s an exciting -- and challenging -- time in the power industry, particularly the regulated power sector. Since 2007, operating margins have declined by more than 30% across utilities, automotive, energy and industrials. Increasing momentum toward the decentralization and decarbonization of power industry assets has contributed to declining margins, as have rising operations and maintenance (O&M) costs driven by slow adoption of digital technologies.

In the last 5-7 years there has been an uptick in developing advanced technologies such as GIS, artificial intelligence (AI), machine learning, computer vision, and the Internet of Things (IoT) that enable power companies to enhance their financial performance by reducing their costs and optimize their systems. A steady increase in investments for these technologies demonstrates that these themes are transforming the power sector for a diverse mix of utilities, industrial companies, and independent power producers (IPPs).

One technology in particular that is reimagining the power and energy industry is geographical information systems (GIS). With the advent of technologies like GIS, the power sector can harness data to prevent outages in equipment, or run operations more cost-effectively or efficiently. In a highly competitive power market with razor-thin margins, even two percent improved efficiency can help companies win contracts or provide better service to their customers.

GIS for Automation

The aging utility workforce and automation replacing human workers are hot button issues for many utilities and their regulators. What is the right balance between preserving institutional knowledge and replacing workers with faster, more cost-effective automation? One perspective is that “enabling” workers by automating low-value tasks can help strike a balance between automation and knowledge management in the immediate term. Repetitive and time-consuming activities in particular —manual data collection, processing and analysis — are ripe for disruption, and the solar industry offers several great examples of how GIS can automate low-value tasks to remove friction and lower costs.

Residential solar sales & permitting

As utilities increasingly offer DER to customers, a question often arises — which customers are best suited for DER, while minimizing grid impact? Aurora Solar uses GIS and LiDAR to remotely evaluate a building or home for solar, identifying obstacles on rooftops and suitability for solar. In minutes, Aurora’s solution creates an accurate 3-D report detailing the size, cost, savings and production. Their software creates a system design, evaluates project economics based on customer load profiles and local financial incentives, and prepares permit-ready engineering diagrams to simplify the preinstallation process. Aurora is further enhancing the platform to evaluate battery storage with solar. Utilities can partner with Aurora to identify the optimal solar customers on distribution circuits with the most DER hosting capacity, without ever having to roll a truck. Design, site inspection and permitting represent a significant (and stubbornly high) portion of the overall cost of solar; removing friction around the sales and design process can help utilities avoid backlogs and speed up deployment of distributed solar assets.

Utility-scale solar site assessment, construction and maintenance

DroneDeploy offers a GIS-enabled drone software platform to automate asset and land inspection, surveying, and mapping. DroneDeploy’s software can even automate drone flight plans and post-collection image processing, generating actionable business insights. Currently, DroneDeploy is working with an IPP to evaluate potential solar photovoltaic (PV) development locations without requiring a manual walkthrough, saving both time and money. DroneDeploy is also beginning to support T&D applications for vegetation management or asset inspection, where they can measure underperforming panels in a solar field, for instance, and direct maintenance crews to individual panels in a matter of minutes, instead of days.

Another area that’s ripe for disruption is risk mitigation. Climate change poses a significant threat to utilities, IPPs and asset owners in general. The recent ConEd blackout in New York City is a good example: although the company is still working to investigate the root cause, according to CBS News, ConEd is warning of potentially more blackouts for New York City as temperatures continue to rise. In addition to heat, storms, hurricanes, fires and floods also threaten new and aging energy assets. Technologies like GIS and AI can help asset owners predict risks to their infrastructure to avoid damage, downtime, or catastrophic failure.

Jupiter Intelligence uses AI to build models that help asset owners predict climate-related risk: GIS functionality enables the company to predict risk down to the individual meter level. With predictions spanning a year, five years, or ten years into the future, Jupiter helps utilities and IPPs determine the potential cost to their investments as hurricanes become more severe, or wildfires more frequent and intense. This is useful not only for owners of existing assets, but for entities considering new investments or construction: they might consider steps they can take to mitigate damage, such as updating equipment or buying more insurance, or even change a planned asset deployment site.

As older industries transition to a more digital and connected world, the utility industry is ripe for disruption. There is a significant amount of change going on right now. New companies that have harnessed the power of technologies like GIS and AI will play an important role in helping older industries and incumbents become more efficient and adjust to their changing environment.

Amy Francetic's picture

Thank Amy for the Post!

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Matt Chester's picture
Matt Chester on Jul 29, 2019 11:14 am GMT

Great overview on the potential for GIS in the industry, Amy-- thanks for sharing!

The aging utility workforce and automation replacing human workers are hot button issues for many utilities and their regulators. What is the right balance between preserving institutional knowledge and replacing workers with faster, more cost-effective automation?

In addition to the points you make here, I wonder if another reason to embrace the digital with GIS is for improved accuracy through reduced human error-- do you have any insight on if that comes into play?

Amy Francetic's picture
Amy Francetic on Aug 7, 2019 5:38 pm GMT

Hi Matt,

Thanks for your insightful comments. Glad that you enjoyed the article, there is a wealth of potential in utilizing GIS. We've likely only just begun to scratch the surface. I think that automation is complementary and not a full replacement for human workers.

Yes, you're correct. Improving accuracy in reducing human error is another reason to embrace the digital with GIS. And, it's important to remember that the parameters of GIS are still established by humans, which can still result in error. Penn State University took a closer look at error, accuracy and precision within GIS. We invite you to read up on their findings here: https://www.e-education.psu.edu/geog469/node/262

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