Few people doubt that the U.S. will continue to experience electric power outages of long durations affecting a large number of people and businesses. Some industry observers believe that the resilience of the U.S. electric-power network is deficient: If industry spends additional monies on improving its resilience, the benefits would outweigh the costs.

Customers, the media and the public have taken more interest scrutinizing utilities in recent years on their responses to weather-related disasters and threats of cyberattacks. We are also seeing a full-court press by the federal, state and local levels to bolster the resilience of electric power, even if it costs a substantial amount of money. 

The common perception is that the benefits are too large to ignore, which seems plausible on its surface. After all, the damage from a long power outage can be devastating to a locale affecting almost everyone.

One concise definition of resilience is that it measures the performance of a system under threat or stress, like power grid performance under severe weather conditions or a cyberattack. According to this definition, a resilient power system covers the ability of the power grid to withstand and recover from malicious and inadvertent cyber and physical attacks. 

Both the utility and electricity consumers can mitigate the damages from extended power outages. 

Resilience should be an integral goal of utility planning to determine long-term investments and other measures. A utility can through its pricing find out how much its customers are willing to pay for different levels of resilience. Customers can also self-insure and take other protective actions to mitigate the damage from long-term outages. 

Flawed decision-making by policymakers

Because policymakers and system operators rightly fear extended service interruptions and blackouts — they would face the brunt of criticism — they may not think twice about burdening electric consumers with the cost of avoiding them. They will tend to err on the side of excessive caution that translates into higher electricity prices for their customers. 

The problem is that they may view improved resilience to be beneficial from their perspective when it is not from society's.

Evidence in different contexts has shown that "probability neglect," namely, the sole focus on outcome and disregard for its probability, helps to explain excessive reactions to low-probability, catastrophic events; that is, the responses to tragedies and other highly damaging events often occur right after outrageous incidents with high public exposure. The result is a failure to apply rigorous, analytical approaches to managing risks. 

The mindset of many policymakers is: We can't let this happen again, no matter how slim the chances are and the cost. These events have a major effect on people's beliefs and behavior, with exaggerated risk perceptions often derived from high-profile publicity given to such events. 

The policy discourse over electric power resilience exemplifies this flawed thinking.

Prudent decision-making on resilience requires consideration of the probability of events, whether calculated objectively with historical data or subjectively. This means that assessing the economics of improved resilience should account for the likelihood of the future frequency and duration of extended outages covering a large area. 

How otherwise can decision-makers conduct valid cost-benefit review of costly investments and other actions?

Utility planning approach

What then is a sensible public policy toward low-probability, high impact events such as extended power outages? One strategy would be to expend resources today to mitigate the small chance of a future disaster. But this begs the questions of how much utilities should spend in total and for each resilience-improving measure. 

These are the basic challenges facing both utilities and their regulators.

From a public-interest perspective, the question comes down to whether a "resilience" problem exists; namely, either utilities are spending too much on the resilience that they presently have (however it is measured), spending too little for enhancing their resilience, or are overly resilient today.

Deficient resilience can exist because of its public-good nature — for example, the social benefits, which may include public health and safety, exceed the benefits to electricity customers and the utility itself. On the other hand, utilities may be overspending on resilience because of excessive caution and probability neglect.

Utilities can also spend too much on the resilience desired because of the absence of a sequence of actions based on cost-effectiveness. 

Some analysts have questioned the cost-effectiveness of underground lines: These lines can cost three to four times more than overhead lines of equal distances; although they can reduce the frequency of service interruption, outage duration is typically longer than with overhead lines because of the greater difficulty in repairing underground lines. 

Other measures (e.g., investment in an outage management system) taken by a utility can be cost-effective while the same measures may not be for another utility.

Under conventional ratemaking, utilities may have an incentive to inflate their rate base to improve resilience (assuming that the authorized rate of return exceeds a utility's cost of capital) — in regulatory jargon, gold-plating — by spending excessively to booster their profits. They may approach their regulators with key actions and investments to improve resilience without explicit consideration of their costs or effectiveness. 

The likely outcome is utility customers paying for resilience at an amount more than (1) the benefits they receive or (2) what they should because of utilities' cost inefficiencies.

If a problem exists, what might utilities do, and how do we know if improved resilience is net beneficial to society? These are tough questions to answer, especially when relying on conventional cost-benefit analysis and other analytical approaches.

One analytical approach is the break-even method. It asks the following question: If we know the costs of increasing resilience and the costs of electric outages to customers and society, how large does the probability of an event combined with the effect of resilience investment on that event have to be to balance the benefits and costs? 

Break-even analysis becomes more valid when there exists a high degree of uncertainty over the probability distributions of relevant outcomes, which accurately describes investments in resilience. With high uncertainty, even when doing sensitivity analysis, policymakers have little clue of the probability for each future.

Customer-driven approach

One customer-driven approach is for utilities to offer service-differentiated pricing. This has the potential to optimize the response to service interruptions by allowing utilities to charge a premium to customers who value uninterruptible service at the highest level. These customers, to the extent technically feasible, will have their service cut off only after the utility interrupted service to other customers. 

The central planning or top-down alternative, previously mentioned, whereby a utility makes network-wide investments to increase resilience for all customers can be extremely expensive. It would also likely result in those customers who impute a relatively low value on increased resilience to subsidize other customers. 

Service-differentiated pricing considers explicitly customers' willingness to pay (WTP). WTP is an economic concept used to value non-market goods, such as cleaner air, more wildlife, fewer power outages. Evidence shows that customers suffer widely varying costs from power interruptions.

For example, some retail customers are very tolerant of variations in power quality and power interruptions, while other customers are less accepting of these problems. Customers would therefore be willing to pay different amounts for protection against interruptions.

One prime example is interruptible rates for customers who are willing to accept less reliable service in return for a lower rate. Critical peak pricing and peak-time rebates also illustrate where customers are willing to tolerate lower reliability for savings on their electricity bills.

One apparent cost-beneficial practice is to minimize service interruptions of critical services. This may require the use of distributed generation and microgrids for essential load, like police, gas stations, hospitals and cell towers, and take nonessential loads offline.

Another action may be to ensure that essential services have backup systems. There are different ways to maintain essential services when power is out, and the most economical ones ought to be part of a "resilience" plan.

Non-critical customers can also take actions to mitigate the damage from extended outages, other than purchasing insurance from a third party. Many industrial customers who find service interruptions extremely costly have a direct connection to the bulk power system and backup generation. 

Other customers can purchase a backup generator, solar PV systems with smart islanding inverters, or install Powerwall batteries. Residential customers can prepare for an outage by buying extra batteries, flashlights and blankets, and mitigate losses by purchasing surge protectors. 

Any regulatory policy should recognize that both a utility and its customers could mitigate the harm from service interruptions. Enhancing resilience is therefore a split responsibility between utilities and their customers. 

What it comes down to

The overall goal of resilience should be to minimize the lost value to electric customers and society from service interruptions caused by external natural and human threats, net of costs. In other words, actions to improve resilience should minimize the social costs from a disruptive event, which requires accounting for both the benefits and costs.

To quantify the social costs with reasonable accuracy, utilities will need to develop new data and models. These additional analytical capabilities can identify areas of greatest risks and system vulnerabilities, allocate resources more efficiently, and help prioritize investments. 

We should emphasize the fact that research and development for promising technologies and mechanisms, like improvements to control systems and distribution automation, holds the key to improving resilience in the long term.

It all comes down to how much is society willing to pay for increased resilience. The answer depends on the avoidance of lost welfare that would otherwise occur. The lost welfare measures what analysts refer to as the "value of lost load" or VOLL. VOLL measures can help to set "resilience" targets and to allocate monies toward different measures to enhance resilience. 

A risk-averse society would be willing to spend more than the expected loss in welfare. The tough chore for analysts is to calculate the risk tolerance of different customers. 

For the top-down approach, their analysis would have to aggregate the disparate risk preferences across utility customers into a single standard for society.

Knowing with reasonable accuracy how much customers and society would be willing to pay for avoiding long service interruptions is critical for prudent decision-making. But presently that information is too imprecise to render much value. 

For example, VOLL measures are highly uncertain and specific to local conditions, outage duration and scope. Besides, almost all studies focus on outages of 24 hours or less. The benefits of investments in resilience to counter interruptions of long durations (e.g., multi-day service outages) are consequently dubious and much more uncertain than the benefits for investments in electric power reliability.

A customer-driven approach with service-differentiated pricing seems like the most promising path to pursue if one wants to know how much customers are willing to pay for resilience. But because of the external benefits (e.g., macroeconomic effects, public health and safety) from higher resilience, and the technical and political difficulty for a utility to differentiate services across customers, it will be wrong to expect a socially optimal outcome from market forces alone.