TL;DR:
- Neara utilizes AI to assist utilities and energy providers in modeling their power networks and potential risks from extreme weather events.
- The startup, based in Redfern, New South Wales, Australia, has secured significant investments totaling $45 million AUD from various investors.
- Neara’s AI and machine learning products have been embraced by utility companies globally, including major players like Southern California Edison and SA Power Networks.
- Co-founder Jack Curtis highlights the critical role of AI in analyzing infrastructure and simulating weather-related impacts for faster power restoration and enhanced safety.
- Neara’s predictive capabilities encompass identifying potential outage areas due to high winds, wildfires, flooding, and ice/snow buildups.
Main AI News:
In recent decades, extreme weather occurrences have not only intensified but also grown in frequency. Neara focuses on empowering utility companies and energy providers to construct models of their power networks and potential disruptors, such as wildfires or flooding. The Redfern, New South Wales, Australia-based startup has recently unveiled AI and machine learning solutions, facilitating the creation of extensive network models and risk assessments without resorting to manual surveys.
Since its commercial launch in 2019, Neara has secured a total investment of $45 million AUD (approximately $29.3 million USD) from backers like Square Peg Capital, Skip Capital, and Prosus Ventures. Among its clientele are Essential Energy, Endeavour Energy, and SA Power Networks, while collaborations extend to Southern California Edison and EMPACT Engineering.
Neara’s AI and machine learning-based functionalities are already integrated into its technology stack, having been adopted by utilities globally, including Southern California Edison, SA Power Networks, and Endeavor Energy in Australia, ESB in Ireland, and Scottish Power.
Co-founder Jack Curtis informs that substantial investments are directed towards utilities infrastructure, covering maintenance, upgrades, and labor costs. Immediate consumer repercussions follow any breakdown in the system. Initially, Neara incorporated AI and machine learning to analyze existing infrastructure sans manual inspections, which Curtis deems often inefficient, inaccurate, and costly.
Subsequently, Neara expanded its AI and machine learning capabilities to develop large-scale models encompassing a utility’s network and its surroundings. These models serve various purposes, including simulating the impact of extreme weather on electricity provision pre, during, and post-event. This approach accelerates power restoration, ensures the safety of utility teams, and minimizes weather-related disruptions.
Curtis emphasizes, “The escalating frequency and severity of extreme weather propel our product development more than any single event.” Recent occurrences like Storm Isha in the UK, winter storms triggering extensive blackouts in the US, and tropical cyclones affecting Australia’s electricity grid underscore the significance of this endeavor.
Through AI and machine learning, Neara’s digital utility network models enable energy providers and utilities to preemptively brace for adverse weather conditions. Predictive capabilities encompass identifying areas where strong winds could lead to outages and wildfires, determining floodwater levels necessitating energy shutdowns, and forecasting ice and snow buildup affecting network reliability and resilience.
Conclusion:
Neara’s innovative approach to utility protection, leveraging AI and machine learning, signals a significant shift in the market. By offering predictive capabilities and efficient risk assessment, Neara enables utilities to mitigate the impact of extreme weather events, ensuring operational resilience and customer satisfaction. This underscores the growing importance of AI-driven solutions in safeguarding critical infrastructure in an increasingly volatile climate landscape.
