Making a Business Case for More Intelligence at the Grid Edge

The future of our modern grid is dependent on leveraging more distributed intelligence (DI) at the grid edge to help manage growth, stability, and safety. The move toward a smart grid also has a strong business case. Utilities that have implemented advanced metering infrastructure (AMI) investments are now nearing a breaking even point. But the good news is adding DI can create a positive business case without any consumer behavioral change, leading to nearly US$50 million net business case benefit from DI for just a US$22 million investment, and this number continues to grow.

Adding more intelligence means moving processes from the central office and distributing them throughout the grid. The added visibility from this DI ensures utilities and critical infrastructure operators will be able to meet the shifting requirements of their customers while improving safety and efficiency.

One utility currently at the forefront of testing and implementing DI applications is Tampa Electric Co. (TECO). TECO completed the first-ever field trial deployment of DI-enabled meters with Itron and is currently testing DI applications to improve overall operational efficiencies and improve customer relationships.

Digital transformation and DI

More intelligence at the edge provides additional visibility and control of assets to gain greater efficiencies. It also drives an entirely new customer experience by providing proactive ways to engage with customers, optimizing the effectiveness of load control, demand response, and dynamic pricing programs. DI minimizes the amount of data you must transmit to the back office to analyze and make decisions, which is time-intensive, ineffective, and costly. Pushing the analysis to the edge helps resolve issues faster, saving both time and resources spent chasing symptoms, more proactively.

According to David Lukcic, TECO's director of AMI strategic solutions, TECO's shift toward embracing DI began as an extension of broader digital transformation initiatives around the automation of data and services. The journey to DI was natural and supported a transformational investment in new customer experience and operational programs. The energy company had already maximized the benefits of AMI investments and was looking toward the future in ways to improve overall service delivery and provide additional revenue opportunities to offset the continued costs of upgrading grid infrastructure.

The proposed benefits of DI offer significant value to utilities, including the ability to:

• Manage rapidly changing conditions in real time.

• Enable an increasingly diverse ecosystem of smart meters, grid devices, and distributed energy resources (DERs) that communicate and collaborate.

• Establish measured improvements in grid efficiency, including location awareness, safety and reliability, and outage detection and restoration.

• Transform customer service by optimizing the effectiveness of load control, demand response, and dynamic pricing programs.

• Maintain distribution network stability and operation by monitoring and managing operations in real time.

DI helps improve safety, address energy use, and build stronger relationships with customers — adding more value to all parties. DI empowers an open and vibrant ecosystem of solution providers and applications for both utilities and customers. For example, DI allows energy companies like TECO to manage transactions and power flows in real time, all setting the stage for a future dynamic grid.

Putting edge analytics to the test

The promise of DI is shifting intelligence and analytical processing to the edge, replacing costly and inefficient traditional back-office data operations. TECO developed a multi-phase test that first pitted DI applications against traditional back-office analytics programs to validate DI's real value for itself and the industry as well, to be followed by field tests later this year.

The goal of the trial was to see if DI would result in a higher yield with less inference and wasted resources, like having to send crews to the field to chase things that may not be there. With faster decisions based on more valuable information, TECO was hoping to see a significant drop in the total cost of ownership with less data backhauled, stored, or analyzed in the back office.

The first phase of testing was against three DI use cases — meter-bypass theft, neutral-fault detection, and high-impedance detection. These tests ran over a month in a controlled lab, and the results were promising.

The DI apps and cloud analytics detected all meter-bypass theft use cases, but the big difference was DI triggered no false positives where the cloud analytics triggered seven. These false positives should be lower in field trials as algorithms are tuned by training machine learning algorithms with more data. DI proved itself in neutral-fault detection and high-impedance detection, being able to capture all use cases in each category accurately.

Only DI has the capability to observe broken neutral issues in a 2S meter configuration, the most common meter form in North America. The 2S meter only measures line-to-line voltage, and the required data frequency to discriminate and compute broken neutral conditions from available meter measurements is just not viable in a centralized cloud approach.

Capturing the signatures of high-impedance faults is not possible when the frequency of meter data is sent every 5 to 15 mins in a centralized, back-office cloud model. Having the ability to track, in advance, DI meters at 1 sec or sub-second increments allows for a wider variety of use cases that can be detected.

Looking ahead

TECO's lab results validate the benefits of DI applications by gaining actionable information and a new perspective on problem-solving from more granular real-time data. Shifting critical safety and customer impact issues a utility would treat on failure are now identified and proactively remediated to provide greater efficiencies and cost-savings while delivering a more exceptional customer experience. The utility is developing a white paper to share later this year and is currently preparing for field trials with plans to deploy apps to the meter farm and then production meters beginning this summer.

The bottom line is grid edge intelligence empowers business transformation, evolves distribution grid operations, and enhances customers' experience with proven, innovative applications that are managing the active grid of today and tomorrow.