Why Risk-Based Replacement Is the Future of Grid Asset Management

Summary

Utilities are moving beyond age-based asset replacement by using condition-based maintenance with continuous thermal and visual monitoring to make smarter, data-driven planning decisions. By leveraging real-time health scores and long-term trend analysis, they can safely defer replacements, prioritize high-risk assets, and optimize capital spending. This shift enables utilities to extend asset life, reduce failures, and justify investment decisions with objective, actionable data.

Aging infrastructure, shrinking budgets, and escalating reliability demands are pressuring utility asset managers to do more with less. But the traditional approach to asset planning no longer meets the needs of today’s grid. As utilities face critical decisions on when to repair, replace, or defer investment, real-time data is emerging as a powerful tool for optimizing capital allocation and extending asset life.

Continuous monitoring using advanced thermal and visual sensors is transforming how utility planners prioritize replacements and justify budgets. The result? Smarter investment decisions, reduced risk of failure, and significantly more value extracted from existing assets.

The Problem with Age-Based Planning

For decades, utilities have depended on fixed timelines and generalized age-based models to determine equipment end-of-life. Transformers, for example, were often scheduled for replacement at the 30-year mark regardless of condition. While simple to administer, this strategy fails to account for how load profiles, weather exposure, and operational stress can accelerate or decelerate equipment degradation.

The result is inefficient capital spending as healthy assets are replaced too early, while aging equipment in decline may be left in service until failure. In a grid environment where transformer lead times now exceed three years and costs top $3 million, these planning blind spots are no longer sustainable.

A New Model: Condition-Based, Risk-Informed Planning

Modern utilities are shifting from calendar-based to condition-based asset planning, using continuous monitoring systems that provide real-time insight into the health and performance of critical assets. Systems With Intelligence's Touchless™ Monitoring solutions integrate thermal imaging, visual analytics, and long-term trend data to create a full picture of asset condition across the fleet.

Planning departments can now make replacement and maintenance decisions based on actual risk profiles, not guesswork. Here’s how:

  • Thermal trend analysis identifies gradual degradation, such as increasing load tap changer temperatures or phase imbalances, that may indicate impending failure.
  • Visual sensors verify physical condition, detect leaks, or confirm cooling system operation.
  • Health scores incorporate multiple data sources to dynamically assess conditions and prioritize replacements based on real risk and operational impact.

This shift empowers utilities to allocate capital where it's needed most, which is deferring replacement of healthy assets while focusing investment on those most likely to fail.

Want to see how leading utilities are doing this today? Download our white paper: Building the Resilient Grid

Better Data Enables Better Budgeting

With continuous monitoring, planners can present stronger business cases supported by objective, time-stamped data. Historical thermal performance, visual anomalies, and trend lines provide quantifiable evidence for:

  • Regulatory filings and rate case justifications
  • Capital budget planning and deferral strategies
  • Insurance claims and policy discounts
  • Replacement prioritization across mixed-vintage fleets

The value is in decision confidence. Utilities can defend every dollar of investment with data-backed insights, reducing the risk of both under- and over-spending on infrastructure.

Health Scoring: The Cornerstone of Portfolio Optimization

One of the most impactful developments enabled by continuous monitoring is dynamic asset health scoring. Rather than relying solely on static data like nameplate age or maintenance records, utilities can calculate live health indices using:

  • Temperature deviations (40% of score)
  • Visual conditions like oil leakage or discoloration (20%)
  • Operational stress and load history (20%)
  • Maintenance history and asset age (20%)

These real-time health scores enable portfolio-wide risk ranking, helping planners identify which assets present the greatest risk of failure and the highest cost of inaction. They also support long-term trending, allowing utilities to spot systemic issues across asset classes, regions, or manufacturers.

Building a Data-Driven Planning Culture

Data alone isn’t enough. To truly capitalize on the benefits of continuous monitoring, utilities must build a culture of evidence-based decision-making. This includes:

  • Training staff on how to interpret monitoring data
  • Integrating condition data with asset management platforms
  • Aligning planning, operations, and maintenance teams around shared metrics
  • Transitioning performance measurement from inspection counts to outcomes like failures prevented and life extended

Those that make this shift are already seeing the results: deferred capital expenditures, avoided failures, improved safety, and stronger regulatory alignment.

The Future of Asset Planning Is Intelligent

As the grid grows more complex and the consequences of asset failure more severe, utilities cannot afford to rely on outdated planning models. By leveraging continuous monitoring, utilities gain unparalleled visibility into asset condition, enabling smarter, faster, and more financially sound decisions.

With real-time insights, risk-informed health scoring, and automated trend detection, Systems With Intelligence helps utility planners move beyond reactive infrastructure management and build the resilient, data-driven grid of tomorrow.

For the full story: download our white paper: Building the Resilient Grid 

Fabricio Silva is a Field Application Engineer with Systems With Intelligence.