Hardware-in-the-Loop Evaluation Informs R&D of EGM’s Meta-Alert With a Goal To
Deliver Fault Location Precision Within a Single Span (~300ft /~100m)
Introduction
At any given second, during any given day, an electrical outage at a utility is going to
happen. For example, a feeder is down, customers are in the dark, and the only thing
the control room knows for certain is that the fault is somewhere out there —
somewhere along miles of wire strung between thousands of poles. Sometime later, a truck will roll. The crew will begin the slow, methodical process of driving the line,
looking for the damage.
Electrical Grid Monitoring (EGM) has set an ambitious goal for their Accurate Fault
Location and Detection (AFLD) solution: pinpoint distribution faults to within a single
pole span at a fraction of the cost of current solutions. For an industry where two-thirds of every outage is spent locating the fault rather than repairing it, achieving this goal has direct implications for grid reliability, affordability, and utility operations. EGM partnered with the Israel Electric Corporation (IEC) to evaluate the distribution fault location performance of their Meta-Alert system through hardware-in-the-loop (HIL) simulations at the National Laboratory of the Rockies (NLR).
Reliability and Affordability: The Central Challenge
Grid reliability is a national policy priority. The current administration has placed affordability and reliability at the center of its energy agenda as part of its ongoing support of Grid Enhancing Technologies. A recent 2025 Department of Energy forecast warned that the US could face a significant increase in power outages with customer outages rising to 800+ hours per year in certain regions. Meanwhile, customers are paying more and expecting more. Regulators are tightening performance benchmarks. And the single largest controllable variable in outage duration — the time it takes to locate the fault — has remained effectively unchanged for a generation.
These are not storm-driven challenges. This is “blue sky” reliability — the worsening of performance under normal operating conditions. Underinvestment in distribution infrastructure, aging equipment, and increasing system complexity from distributed energy resources are compounding the problem. And while catastrophic weather events dominate headlines, it is the everyday fault — for example – a tree branch on a lateral, the insulator failure at midnight — that drives the vast majority of customer-affecting outages.
Reliability is as much about metrics as it is about customer service and satisfaction. Two key industry reliability statistics are SAIDI (System Average Interruption Duration) and CAIDI (Customer Average Interruption Duration) calculations, but short duration faults are often omitted from these metrics. But a momentary fault is still a fault event that disrupts customers and any one of them may signal a developing permanent fault.
The Industry’s Blind Spot: Finding the Fault
The U.S. electric distribution network is deceptively complex: multi-source, heavily branched, and increasingly populated with customer-owned generation that introduces two-way power flow. Recloser and switch states change the topology in real time. Conventional impedance-based fault location — which calculates a single distance-to-fault value — often returns multiple possible locations on branching feeders.
The alternatives are familiar but limited. Faulted circuit indicators (FCIs) are inexpensive and widely deployed, but they are binary: they tell dispatchers which lateral experienced a fault, not where on that lateral the fault occurred. Intelligent reclosers can narrow the window but are cost prohibitive at approximately $20,000 per unit of hardware alone — in addition to the install cost. The economics do not scale for the distribution grid.
The operational consequence: over 50% of outage hours are typically spent locating the fault, with line crews patrolling lines looking for faults that may not even be visible to the naked eye. For customers, that search time isn’t just embedded in the SAIDI and CAIDI metrics that regulators use to benchmark utility performance – it manifests as frustration back at their utility providers and anger at rising bills for perceived worse service.
EGM Puts Their Technology to the Test
EGM’s collaboration with NLR began when EGM was selected as a participant in the Shell Game Changer Accelerator grid integration innovation program. Following the completion of the Accelerator project, EGM and the Israel Electric Corporation (IEC) were awarded a project through NLR’s Advanced Research on Integrated Energy Systems (ARIES) User Call for Advanced Distribution Management System (ADMS) Test Bed Use Cases. The ADMS Test Bed is a national, vendor-neutral effort to accelerate industry development and the adoption of ADMS capabilities.
EGM proposed that NLR perform independent testing of the Meta-Alert fault location technology, allowing EGM to gather data to show how their technology could be used to enhance Advanced Distribution Management System (ADMS functionality). IEC provided co-funding for NLR researchers to use NLR’s world-class testing facilities and EGM provided in-kind contributions. For the test configuration, IEC provided three real-world feeder topologies from its distribution network in Israel. One was selected and its characteristics were recreated in NLR’s ADMS Test Bed and then modified to match common grounding practices in the United States.
A Digital Real-Time Simulator (DRTS) was used within the ADMS Test Bed to compute electromagnetic power system states in real time to match real-world transient dynamics and convert those simulated states to real analog voltage and current outputs that were provided as inputs to the EGM hardware under test. The EGM sensors connected in the test bed were modified to introduce the low-voltage analog outputs from the DRTS after the high-to-low voltage and current conversion that would be required for a sensor installed in the field, but other than that, there is no distinction between the RTDS outputs and outputs from a live distribution grid. The sensors measure, process, and respond exactly as they would in the field.
Fig. NLR laboratory CHIL evaluation setup
“Increase in grid visibility is a tool to enhance electric system optimization and reliability that can allow industry to mitigate system perturbations and reduce operational cost. The NLR ADMS Test Bed provides a resource for industry to fast-track the technology readiness with the ability to simulate a vast amount of scenarios that could take years to experience in the field.” – Ismael Mendoza, Principal Engineer, Power Systems Engineering Center at the National Laboratory of the Rockies
After EGM’s fault location algorithm in the system was calibrated with simulation data from faults at known locations on the feeder, the test program comprised 26 independently executed blind scenarios across three phases (A, B, and C) and four feeder segments. EGM had no advance knowledge of the fault locations or feeder segments selected by NLR. All scenarios were solid single-phase-to-ground faults – a controlled baseline that establishes the technology’s core accuracy under well-defined conditions.
The preliminary results of the testing show that the aggregated accuracy of the solution across 26 scenarios was within 156m / 512ft, of which ~70% were within 200m / 656 ft and ~40% within 100m / 328ft from the fault. The lower accuracy on phase A is thought to be a result of an error introduced on that phase in the changes made to connect the low voltage outputs from the DRTS directly to the sensors, but needs further investigation to confirm. On phases B and C, over 80% were within 200m / 656 ft and 50% were within 100m / 328ft from the fault.
“This marks an important milestone in evaluating EGM’s AFLD technology for accurate fault location. With these learnings and the upcoming release of our next-generation sensor we take an important step to becoming the leading player in distribution grid monitoring.” – Natti Hugi, VP of R&D, Electrical Grid Monitoring
| Phase | Runs | MAE*(m/ft) | Median (m/ft) | ≤ 100m (328 ft) | ≤ 200m (656ft) |
| Phase A | 8 | 252m / 827ft | 240m / 789ft | – | – |
| Phase B | 10 | 69m / 226ft | 48m / 156ft | 60% | 100% |
| Phase C | 8 | 163m / 535ft | 146m / 479ft | 38% | 63% |
| B + C | 18 | 113m / 371ft | 84m / 277ft | 50% | 83% |
| All | 26 | 156m / 512ft | 129m / 421ft | 39% | 69% |
*MAE: Mean Absolute Error
“This project exemplifies the value to industry of using hardware-in-the-loop laboratory testing infrastructure to evaluate new technologies that are aimed at improving grid operations” – Annabelle Pratt, Chief Engineer, Power Systems Engineering Center at the National Laboratory of the Rockies
The Deployment Economics
For utility executives across the United States evaluating capital investment in reliability, the question is not just accuracy — it is accuracy per dollar deployed. The distribution network of a major U.S. utility can include well over a million poles. Solutions that require a sensor on every pole are theoretically effective but practically unscalable to the whole network.
EGM’s system uses a cluster-based deployment model: a small number of strategically placed sensors covering an entire feeder. A typical deployment such as that run in this test, uses 12 sensors in 4 clusters. For comparison, a pole-mounted solution to the equivalent IEC feeder would require up to 80 sensors. EGM’s sensors install without heavy-lift equipment and without the need for external voltage transformers — so can be deployed at a fraction of the cost of alternative approaches. Sensor calibration is conducted in the factory and on the first cluster installation with any subsequent tuning conducted with remote Over The Air Programming (OTAP).
“Every hour spent searching for a fault is an hour customers are without power and an hour the utility is burning operational dollars. When you can put a crew on the fault in the field within a span, you are not only improving SAIDI – you’re delivering the kind of reliability that customers expect and that regulators are increasingly demanding.”- Mike Spoor, former Florida Power & Light T&D Executive and EGM Board Member
Once installed, the operational savings compound. With well over ~10 million annual US truck rolls at an estimated $1,000 cost for each, the accruing cost to consumers through rates comfortably runs into double digit billions. Eliminating even one hour of search time per outage delivers direct, measurable value for both Utility and Customer.
Why Existing Approaches Fall Short
Pole-mounted sensor solutions face fundamental scaling challenges. Instrumenting every pole on a large distribution network is logistically impractical and economically prohibitive. But the limitations go deeper: because pole-mounted sensors sit outside the conductor and therefore they cannot measure electrical parameters. This limits their ability to detect transient and momentary faults — the very events that are not factored into reliability statistics but signal developing permanent failures. Faulted Current Indicators do measure current and sit on the wire, however, they only provide a binary “yes/no” signal of whether current is flowing. This can be helpful to narrow down the patrol area for line crews but is a crude tool and is only as precise as the density of lateral lines on which FCIs are installed. Intelligent reclosers provide better granularity than FCIs but cannot distinguish between taps unless installed at every branch point. The hardware cost alone is approximately $20,000 per unit, with installation potentially doubling or tripling that figure.
EGM’s sensors are on the conductor — not mounted externally on the pole. They capture the full electrical signature of fault events, measuring over 40 parameters including voltage, current waveforms. With high sampling rates and GPS-timestamped data logging – this makes the same sensor platform suitable for phasor measurement, power quality monitoring, and disturbance analysis.
“Collaborating with a lab to independently measure your fault location accuracy in a blind test — 26 scenarios, no advance disclosure — that’s the kind of technical due diligence that gives utility executives confidence to deploy.” – David Costello, former Chief Sales & Customer Service Officer of Schweitzer Engineering Labs (SEL) and EGM Chairman
Investing in a Long-Term Reliability Platform
The distinction matters for a utility’s investment strategy. A pole-mounted sensor solves the narrow, low-cost problem today — but it does little to build a reliability and resilience platform for the future. EGM’s technology is not a single-application sensor. It is a measurement platform with a roadmap that extends from fault location to power quality management, distributed energy resource integration, and predictive maintenance.
NLR and EGM plan to participate in the follow-on Solar-HERO project that focuses specifically on autonomous optimized outage recovery with data orchestration. The same sensor hardware, already evaluated for fault location, would be applied to an application of increasing urgency to speed up recovery time and reduce operational cost.
“Our focus has always been on the utilities and the grid operators keeping the lights on. If we can give operators clearer visibility of the distribution grid and help them find faults faster, then we are delivering them value. Everything we build starts with what our customers need to run their grids more affordably and more reliably.” — Alex Levran, CEO, Electrical Grid Monitoring
EGM is working with the Israel Electric Corporation and several U.S. investor-owned utilities and cooperatives to deploy the technology on live distribution networks. The testing of EGM’s Accurate Fault Location and Detection technology at the National Laboratory of the Rockies is an important step in EGM’s goal of developing precise, scalable fault location and moving it from theory to practice. By reducing the time utilities spend searching for faults with actionable operational intelligence, technologies like EGM’s offer a practical path toward improved reliability, lower operational costs, and stronger grid resilience. This translates into meaningful benefits for customers, regulators, and utilities alike.
NLR will be presenting more detailed results from the laboratory evaluation later this year at a workshop on ADMS Test Bed projects for industry professionals.
About the Authors
Natti Hugi, VP of R&D; Electrical Grid Monitoring
Alex Levran, CEO, Electrical Grid Monitoring
Dr. Alex Levran is CEO of Electrical Grid Monitoring. He brings nearly 40 years of executive leadership in renewable energy, utility systems, and power technologies. He holds six U.S. patents and has held senior leadership roles at ABB and SUMEC Group.
Natti Hugi is Vice President of R&D at Electrical Grid Monitoring, where he leads the development of advanced grid monitoring, analytics, and fault location solutions. He brings more than 20 years of engineering and leadership experience in complex infrastructure and multidisciplinary product development teams.