Rhizome offers a software platform which aims to introduce climate resilience and wildfire ignition analytics into grid modeling and investment planning efforts. The platform enables electric utilities to:

• Identify vulnerabilities in the grid stemming from long-term extreme weather threats and wildfire risk
• Prioritize investments in grid resilience based on projected risks and potential benefits
• Quantify the benefits of those investments to secure regulatory approval

The platform analyzes distribution networks, focusing on:

• Identifying asset threats: Pinpoint potential risks from climate change (down to a sub-feeder level)
• Quantifying climate risk: Assess the impact of various climate factors
• Modeling interventions: Develop and test strategies to mitigate risks
• Designing resilience plans: Create comprehensive plans tailored to specific needs

The platform delivers measurable outcomes, such as:

• Reduced outages: track progress with metrics like SAIDI and SAIFI
• Increased efficiency: designed to integrate with existing utility systems
• Improved social impact: analyses include data, such as income and demographic information, to provide an equitable and inclusive approach to resilience

Annual subscription to the software-as-a-service platform.

Rhizome’s solution provides the unique capability to bring grid and environmental datasets together within a common modeling and simulation platform. Along with proprietary ML-based analytics and an intuitive user interface, engineers and other utility personnel can prepare a range of climate scenarios, as well as evaluate a range of upgrades to mitigate the risks identified by those scenarios.

The platform works by:

• Creating a comprehensive “digital twin” of the distribution system (ingests the utility network model)
• Combining outage, climate, weather, vegetation, customer, and social equity data to generate a dynamic and comprehensive picture of climate risk and its impact on every feeder and lateral
• Leveraging machine learning and causal inference statistical techniques

These functionalities then give utilities the ability to:

• Quantify the probability of asset failure across various climate threats and failure modes
• Estimate the outage and restoration costs associated with such failures
• Predict the total risk reduction achievable through investments in vegetation management, asset replacements, undergrounding, and grid hardening The resulting "value of resilience" metric empowers asset planners and engineers to optimize capital investment plans for maximum protection of their grid assets and their customers.

As extreme weather events become more frequent and severe, electric utilities are finding it increasingly important to not only increase funding for resilience, but to strategically prioritize investments that yields that highest benefit to the system and customers. Without fully understanding the vulnerabilities and corresponding risk at high resolutions (e.g., sub-feeder level), grid value and benefits are being left on the table. Furthermore, as the risk profile is anticipated to change in the future, there is a need to incorporate various scenarios of climate projections to ensure that future risks are being fully taken into account.

Example business process enhancements:

• Regulatory engagement: quantify benefits and minimize risk for smoother approvals (address the challenge of justifying resilience investments)
• Enhanced asset management and operations: gain insights into climate-related asset risks and proactively address vulnerabilities (e.g., pole replacement/upgrades, strategic undergrounding, vegetation management, non-wires alternatives)
• Integrated grid planning/integrated resource plans (IRPs): model and simulate a range of scenarios to capture climate uncertainties and develop adaptable resilience strategies