Episode Summary
Executive Summary: Mish Tadani explains how Rhizome helps utilities quantify climate and operational resilience risks, prioritize investments, and justify spending to regulators. The conversation covers resilience definitions, asset vs. capacity risk, vegetation management, reconductoring, batteries, regulatory shifts, federal funding, and how AI can help utilities balance reliability, affordability, and clean-energy goals amid worsening extreme weather.
Main Topics: Defining resilience for utilities (Priority: 5/5): Tadani frames resilience as both the ability to recover after an incident and the ability to reduce impacts from non-blue-sky events like extreme weather, cyberattacks, and other threats. Rhizome focuses on the climate/weather side while using frameworks that can extend to other risks. Risk modeling: likelihood and consequence (Priority: 5/5): Rhizome models resilience by quantifying the probability of failures and the consequences if they occur, down to circuits, protected sections, and customer impacts. The goal is to give utilities high-resolution insight for planning and investment decisions. Investment tradeoffs across asset hardening and capacity (Priority: 5/5): The discussion distinguishes physical asset risk from capacity risk, showing how investments like covered conductors, undergrounding, reconductoring, batteries, and distribution automation can reduce outages, increase capacity, or both. Vegetation management and wildfire mitigation (Priority: 4/5): Vegetation is a major driver of outages and wildfire risk. Tadani explains that utilities must compare vegetation spending with capital investments such as conductor insulation or line hardening to determine the best long-term risk reduction. Regulatory change and resilience planning (Priority: 5/5): Utilities and regulators are increasingly adopting formal resilience plans, climate vulnerability studies, scenario analysis, equity considerations, and ongoing reporting to justify billions in resilience spending and demonstrate customer benefit. Federal policy and funding (Priority: 4/5): The Infrastructure Investment and Jobs Act is highlighted as a major source of grid resilience funding, with billions flowing to utilities for hardening, microgrids, storage, and advanced tools; Tadani argues modeling software should also qualify for support. AI, load growth, and affordability pressures (Priority: 4/5): AI is both a driver of new load and a tool for solving planning problems. Utilities must now balance reliability, clean energy procurement, electrification, and affordability in a climate-stressed system.
Key Arguments: Resilience is not a vague buzzword if it is tied to measurable recovery time, outage probability, and customer consequences. Utilities have historically lacked clean, high-resolution data on where failures happen and what external factors cause them, making better planning software valuable. Climate resilience investment decisions should compare alternatives on avoided outages, restoration costs, customer impacts, and long-term regulatory justification. Asset risk and capacity risk are distinct but interconnected; many investments can address both simultaneously. Reconductoring is not only about serving more load; it can also improve heat resilience by increasing line capacity under hotter conditions. Vegetation management is a critical, high-impact lever because tree-related failures drive a large share of outages and wildfire risk. Regulators increasingly require quantified resilience plans, but utilities need counterfactual analysis to prove investments would have prevented outages or reduced harm. Federal infrastructure funding is already enabling utility hardening, but advanced modeling and intelligence tools should be included in eligible resilience spend. AI-driven load growth intensifies the need to plan carefully because utilities must simultaneously support new demand, reliability, and clean-energy goals without making rates unaffordable.
Data Points: Utilities asking about cyber resilience: 10% to 20% of the time - Rhizome is asked whether its resilience frameworks can also apply to cyber threats. Customers knocked out in Houston wind event: 70% - A recent 100 mph wind event in Houston reportedly knocked out 70% of customer power. Tree branches as outage cause: over 50% - Tadani says tree branches account for more than half of power outages across U.S. systems. Winter Storm Uri restoration time: 3 to 5 days - Example used to show how long it can take to restore millions of customers after a major event. DC substation upgrade proposal: $250 million - Tadani references an early non-wires alternative proposal in Washington, DC to avoid a substation upgrade. Texas resilience plans: Encore: $3.0 billion; CenterPoint: $2 billion - Examples of large utility resilience plans filed under new Texas regulation. Infrastructure law utility resilience funding: $11 billion - Funding cited as going directly to utilities, states, and tribes for grid hardening, microgrids, and battery storage. Federal awards round mentioned: about $1 billion - Round-one investments already awarded to utilities for ADMS, undergrounding, and self-healing devices. Planning horizon for some utility assets: 50 years - Used to describe the long-lived benefits of devices like tripsavers and the need to justify investments over decades. Future climate event frequency example: 1-in-10-year event becoming a 1-in-2-year event by 2050 - Illustrates how climate change alters return periods used in risk modeling.
Pivotal Quotes: "The way that I would really categorize them and qualify them is in two distinct buckets." — Mish Tadani: Explaining his definition of resilience as both recovery capability and impact reduction from non-blue-sky events. "It’s all about quantifying the likelihood of a failure happening on the grid and what that consequence is." — Mish Tadani: Describing the mathematical basis of resilience modeling for utilities. "AI is part of the problem and part of the solution." — Jason Jacobs: Summarizing AI’s dual role as a driver of load growth and a tool for utility planning and investment decisions.
Implications: Utilities will need more granular modeling, better data, and stronger regulatory proof to justify resilience spending. The winners will be tools and strategies that reduce outage risk, support load growth, and keep electricity affordable while climate extremes intensify.