Use Risk to Your Advantage in Asset Investment Planning

By Ajay Madwesh, Space-Time Insight

Utilities run, in part, on money. Infrastructure for generation, transmission and distribution is expensive to plan, purchase, install, operate and maintain. This reality drives financial professionals in utilities to deploy an end-to-end methodology for asset investment planning.

In developing and applying such a methodology, key questions arise, such as:

Where are my high-risk assets?

“- How do I prioritize my maintenance tasks?

“- How do I justify my next capital request?

“- Where are the best asset capital investments I can make?

“- Can I defer capital spending without significantly increasing risk?

“- In the face of changing technology and business models, how can I best use my existing assets and capital investments to generate revenue?

“- Can I get more out of the IT and operational systems that I already have in place?

These questions are difficult to answer based on time-based maintenance approaches to understanding and managing assets.

This article presents four steps that utilities can take to generate greater efficiencies from existing assets investment planning efforts, and apply the resulting savings effectively in support of further improvements to the utility grid.

Step 1: Know Your Asset Risks

Before you can make risk-based decisions for new asset investments, you first need to understand the risks inherent in your current asset fleet. In asset investment planning, risk is defined as the likelihood of asset failure combined with the consequence should failure occur.

Each asset has its own unique risk profile. Factors such as age, location, usage, maintenance and relationship to other assets all contribute to an asset’s risk profile. For example, consider two identical power transformers installed on the same day. Based just on age, make and model, these two should have the same risk level. But if one transformer spends its life in a shady and protected spot serving the relatively light load of a residential neighborhood, it will likely have a much lower probability of failure than its twin toiling way in an exposed, hot area serving a fast growing commercial district. In addition, if the residential power transformer should fail, the consequences of the resulting power outage are likely less than the loss of community service and economic activity should the commercial district lose power.

Once you know the true risk level of your assets, you can begin to be more discriminating in how you invest your money, time and resources. In that differentiation lies the possibility for capital efficiency that frees funds for new investments.

Step 2: Manage Your Existing Asset Fleet

In managing assets, you have a range of actions from which to choose to improve reliability and lower risk. Each choice has an accompanying level of cost and risk reduction. You can choose to do nothing, which costs nothing but yields no risk reduction. On the other extreme, you can choose to completely redesign an asset to greatly reduce your risk, but that of course can be costly. Redesign carries the costs, risks and time requirements of solution research and development, in addition to implementation work of replacing an asset that no longer meets your needs.

Knowing the risk inherent in an asset allows you to make better choices among these options. For example, knowing that an asset could benefit from repair, but has only minor consequences should it fail, allows you to decide whether to postpone or cancel repair altogether, in favor of spending your money, time and resources on some other, more critical activity. You can also target energy efficiency or demand response, to reduce stress on the asset.

On the flip side, knowing that an asset in failing health also represents major consequences should it fail, you can decide to invest money, time and resources now to improve the reliability of the asset, and potentially reduce or avoid the future costs of an asset failure.

More-informed asset management gives you the ability to lower the overall risk in your existing system while also lowering your overall investment in maintaining the existing system. Now you have both the confidence and the funds to invest in new projects in alignment with your organizational goals.

Decisions Based on Analytics of Cost vs. Risk Reduction.

Step 3: Plan and Justify Your New Investments

When you optimize your current asset spending based on your knowledge of risk, your initial savings may be in the millions of dollars. At the same time, your future investments in system improvements could be in the billions.

Saving “only” millions may seem meaningless at first. However, those millions can go towards studies, proofs-of-concept, pilot programs and enabling systems that are the first steps towards finding the next right investments that work for you and your customers, investors, regulators and other stakeholders. Providing utility service is growing increasingly complex and diverse; some new investments will be more applicable than others depending on the geography and customer base you serve, your current generation portfolio, the regulatory climate of your state, and other factors.

For example, supporting residential solar power and electrified transportation makes good sense for sunny, urban areas such as Los Angeles. For wintry rural areas such as Minnesota, it might make more sense to invest in wind power, energy storage, and microgrids to make the system more resilient to outages caused by storms.

Because your new understanding of risk is data-driven, it can be forecasted. This becomes useful as you’re building the rate cases, bond offerings and other capital requests that you’ll need to take your grid investments from trial stages to full scale. When you can present data-driven analysis of the future benefits of your plans, you’re more likely to win the funds you need.

Step 4: Deploy New Assets

Once you have identified new grid investments that justify full-scale expansion, the order and location in which you deploy the related assets can have a major impact on ROI and customer satisfaction. Consider these use cases:

If you are focusing on supporting electrified transportation, then enhancing the grid in areas with greater demand because of higher EV penetration and usage might take priority

If you are focusing on supporting more residential solar power, then improving feeders that are at risk of failure from supporting two-way energy flow makes sense

If you are increasing the amount of storage on your grid, you could reduce risk and impact of power outages by targeting your deployed energy storage to support critical loads such as water pumping stations, medical centers and emergency shelters

In these cases and more, specific knowledge of existing and forecasted risk can be the determining factor in how and where you adapt, expand and enhance your system. Analytics drives asset investment planning.

How can utilities support system improvements with insight to the probability and consequences of asset failure?

Traditional methods of business intelligence and forecasting are increasingly proving incapable of handling the volume and real-time nature of data streaming from smart devices. The volume, variety and sub-second speed of IT, operational and external data generated every day is now too much for humans to manage, comprehend and apply without help from computers.

Fortunately, the growing volume and speed of system-related data coincides with the rise of situational intelligence applications. These applications gather and correlate data from disparate systems, analyze it and visualize it in decision-making-friendly formats.


As vice president of the Utilities Business Unit at Space-Time Insight, Ajay Madwesh draws on more than 20 years of experience in software development and technology management in utility and process automation environment, and has spent several years evangelizing the integration of real-time operational technologies with IT.

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