Extreme Weather and Utility Resilience: How Neara is Transforming Energy Management
In recent decades, extreme weather events have intensified in severity and frequency, posing significant challenges for utility companies and energy providers. Based in Redfern, New South Wales, Australia, Neara is dedicated to helping these organizations develop comprehensive models of their power networks, considering potential threats such as wildfires and flooding. The startup has recently introduced innovative AI and machine learning solutions that facilitate large-scale network modeling and risk assessment without the need for time-consuming manual surveys.
Since its commercial launch in 2019, Neara has secured approximately AUD 45 million (about USD 29.3 million) in funding from prominent investors such as Square Peg Capital, Skip Capital, and Prosus Ventures. Its diverse customer base includes Essential Energy, Endeavour Energy, and SA Power Networks, along with partnerships with Southern California Edison and EMPACT Engineering.
Neara's advanced AI and machine learning features are already integrated into its platform, benefiting utilities globally, including Southern California Edison, SA Power Networks in Australia, ESB in Ireland, and Scottish Power. Co-founder Jack Curtis emphasizes the enormity of expenditure on utility infrastructure, which encompasses maintenance, upgrades, and labor costs. He highlights how, when issues arise, consumers feel the immediate impact. Neara's integration of AI and machine learning aims to analyze existing infrastructure efficiently, eliminating the inaccuracies and costs associated with manual inspections.
The platform has evolved to create comprehensive models of utility networks and their environments, enabling simulations of extreme weather impacts on electricity supply before, during, and after events. This capability enhances power restoration efforts, safeguards utility teams, and mitigates the effects of severe weather. Curtis notes, "The increasing frequency and severity of extreme weather events drives our product development more than any single incident." Recent instances, such as Storm Isha affecting power in the UK and severe winter storms disrupting electricity across the United States, underscore this urgency.
Utilizing AI and machine learning, Neara's digital models help energy providers prepare for such events. They can anticipate scenarios where high winds may cause outages, as well as monitor flood levels that necessitate shutting off power lines. Additionally, the technology is adept at predicting ice and snow accumulation that could compromise network reliability.
In Curtis's view, AI and machine learning have been integral to Neara from the beginning, with lidar technology playing a crucial role in accurate weather simulations. The model is trained on over one million miles of diverse network territory, capturing minute but consequential details with exceptional precision. Such accuracy is vital; for instance, a slight change in elevation can lead to inaccuracies in water level predictions, which could result in premature or unnecessary energization of electrical lines.
Lidar imagery is captured by utility companies or third-party services, with some clients continuously scanning their networks to feed fresh data into Neara, while others delve into historical insights. Curtis emphasizes, "The real power lies in creating a digital twin model from this lidar data, rather than merely analyzing the raw data."
Two notable projects illustrate Neara's impact: with Southern California Edison, the aim is to automatically identify vegetation at risk of igniting, surpassing the accuracy of manual surveys. This approach not only enhances safety by informing inspectors of potential hazards but also standardizes data collection across different inspection teams, eliminating variations in subjective assessments. By utilizing lidar and satellite imagery, Neara simulates factors influencing wildfire spread, such as wind speed and temperature. Utilities often face complexities in evaluating the risk associated with each pole, assessing over 100 regulatory questions annually.
In its collaboration with SA Power Networks following the devastating River Murray flooding crisis of 2022-2023, Neara harnessed lidar data to model the digital impacts of flooding on its network. This innovative approach enabled them to assess damage and residual risks in just 15 minutes instead of months. As a result, SA Power Networks managed to restore power within five days, significantly faster than the original three-week forecast.
The 3D modeling system empowered SA Power Networks to evaluate the effects of varying flood levels on their electricity distribution, predicting potential breaches and disconnections. Once river levels stabilized, they continued utilizing Neara’s modeling capabilities to facilitate the reconnection of electrical supplies along the river.
Currently, Neara is investing in further R&D in machine learning, with a focus on maximizing utilities' use of real-time and historical data. Plans include expanding the variety of data sources for modeling purposes, especially in image recognition and photogrammetry. Additionally, Neara is collaborating with Essential Energy to create a detailed digital network model that will allow for enhanced asset assessment based on the likelihood of extreme weather events and their resilience. This transition from manual to automated risk/value analysis aims to minimize failures, particularly in critical situations like the California wildfires.
Curtis asserts, "We empower utilities to stay ahead of extreme weather, allowing them to understand its potential effects on their networks, ultimately keeping the lights on and communities safe."
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