One of the great U.S. achievements during the first half of the 20th century was the near-universal electrification of America. The Tennessee Valley Authority Act and the Rural Electrification Act combined to set the stage for the remarkable growth that followed World War II.

Those postwar years saw millions of Americans connected to an electric network for the first time. This net-new distribution system had the added benefit of requiring little in the way of preventive maintenance. New components tend to last.

The downside to building out a net-new (or nearly new) system is that the entire system will get old at once. A “run to failure” maintenance strategy makes sense when the poles and lines are all new, but when assets age and failures become more likely, economics-based strategies must become part of the planning process. As the consequences become even greater from those failures — such as from increased loading and emerging smart grid technologies — utilities must look to invest in strategic replacement of assets. In those scenarios, we preemptively replace the most critical and least reliable assets before they can fail; usually the sooner, the better.

Cost-Effective Investment Strategies

It’s easy to zero in on the distribution assets themselves and neglect a utility’s broader context. Utilities have multiple — sometimes competing — commitments to their customers, members, shareholders and others. They also have obligations to be good stewards of their resources and the environment overall.

Ideally, it would be wonderful to capture all the reliability advantages that a modern, built-from-scratch, net-new distribution system might provide. However, such a system would be wildly expensive and wasteful. On a more practical level, a utility can pursue an affordable strategy that minimizes risk, meets reliability requirements, satisfies budget limits and reduces environmental impacts.

Such an affordable strategy consists of two parts. First, the utility must develop a capital expenditure (CapEx) plan that describes how the utility will invest in existing and new assets over time to sustain or grow its customer base and service offerings. With its CapEx plan in place, the utility can then turn to making resource-informed decisions about which assets to preemptively replace and when to replace them.

Value Driven by Optimization

Recently, we had the opportunity to help a utility with nearly 100,000 projects and a 10-year budget of nearly a billion dollars develop just such a resource-informed schedule. The four stages of solving the problem:

  • Need: Satisfy a desire to reduce overall system risk, using strategic asset replacement.
  • Task: Identify a schedule that reduces the most risk affordably.
  • Action: Design and develop a method that can consider trillions of schedule alternatives and find the optimal choice to reduce risk.
  • Result: A replacement schedule that offered the most bang for the utility’s buck.

We selected an optimization approach over several available heuristic methods. Any marginal increase in complexity was more than offset by optimization’s improved, and provably best possible, solution.

In reviewing the findings and summarizing our approach, we can examine this utility’s replacement plan. We found that the optimization approach for replacement scheduling could yield a 3%-4% increase the utility’s total risk reduction benefit when compared to a previous heuristic approach. While that percentage might sound small, it represents $2 million in annual added value to the utility.

The optimization approach can be extended to consider a variety of additional aspects:

  • Budget caps for utility regions and districts
  • Groups of projects that must be scheduled together
  • Multiyear projects
  • The need to enforce prerequisite projects

These extensions are key to helping each utility tailor an affordable replacement strategy to its unique distribution system, environment and stakeholders.


Utilities may have partnership or stand-alone business opportunities as broadband service is rolled out to underserved regions. Learn how a data-driven approach can give utilities needed insights.

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Tony Tarvin, Ph.D., is a senior data scientist at Burns & McDonnell. With more than a decade of experience in the data science field, his diverse background in data visualization, cost-benefit analysis and optimization help him provide insights that enable utility clients to make better decisions.