How Do You Spend $400 Billion? Part V: A Business Opportunity – Identifying the “Top 20%” High-Value Nodes in the Power System

Final Avatar 80x80-Logo-SG-1-and-2-and-IX-LOGO-e1363114874895-150x150


Dominic Geraghty


In Part IV of this dialog series, we presented a Least Cost Strategy for deploying SG 2.0. The present dialog discusses how we identify and screen the most valuable projects within the Least Cost Strategy and how we address the risks and uncertainties inherent in the deployment of these projects.

In all situations, it is the business case that provides the basis for the go/no-go investment decision of an SG 2.0 application in a particular location. As we’ve said previously, a complete business case will include market, regulation, power system impact, other technical considerations, and an assessment of the risks/uncertainties. It will also include an assessment of qualitative factors.

The primary prioritization metric for projects is the benefit-to-cost ratio of the business case, subject to meeting hard constraints such as service reliability and environmental compliance.

Identifying High-Potential SG 2.0 Opportunities

Developing a business case is a very resource-intensive task. We don’t want to do it for every potential SG 2.0 application. Is there an efficient way to develop a first-cut list of the “Top 20%” (most valuable) applications? Yes, power system operators can speed-up the process.

10. DSC_1334-150x150These power system operators, i.e., vertically-integrated utilities, utilities, distribution companies, ISOs, and RTOs, will be the main users of SG 2.0 applications. They are the power system experts. They should be able to develop an initial list of high-potential opportunities for SG 2.0 applications based on their knowledge of stressed system nodes and likely optimal locations.

Project and power system simulation models can then be used to confirm (or not) the value of the applications for these locations. This is a business opportunity for software developers and SG 2.0 vendors.

As part of this identification process, the benefits that an SG 2.0 application may bring to the broader power system needs to be considered (see the discussion on power system simulation models below).

Developing Business Cases

Having screened for the most valuable SG 2.0 application opportunities first, detailed business cases are developed for these opportunities. Some re-ranking in the initial list based on the results of the business cases will result. Certain trade-offs will still be inherent in the process, based in part on the level of risk that decision-makers are willing to tolerate, e.g., their valuation of short-term versus long-term savings, their views on an acceptable level of risk.

It is entirely likely that the business cases will exhibit our desired characteristic discussed in Part IV, i.e., conforming to the 80%/20% rule that projects that 20% of the projects will provide 80% of the benefits of SG 2.0 applications. This is a critical element in achieving our “least cost” goal to create a significant reduction in cost relative to a less selective, less discriminating, deployment approach.

As part of a risk management approach (see below), some deployments may be in the form of “pilot demonstrations”, aimed at resolving uncertainties about their efficacy before committing to a commercial deployment.

The available budget can then be used to draw the cut-off line within the high-value project list and to program the sequence of projects in terms of a deployment time-line. The same thoroughly-developed, evaluated, and prioritized business cases can also be used in rate cases to justify investments as being “prudent”.

The “Top 20%” most valuable projects is a “living list” -- as additional information becomes available the ranking in the list of business cases may change, and other projects may be added to the list.

11. DSC_0118-150x150-150x150End-use customers, IPPs, vendors, consultants, and other participants in the power system will also benefit by using business cases to evaluate potential SG 2.0 applications, similar to the process above, but in many cases this may be for a single project, rather than a large list of possible projects. However, locating SG 2.0 applications at the “most valuable” nodes in the system will be just as important.

We Are Facing a Power System and Market Simulation Challenge

To be consistent, and to provide the opportunity to compare “apples to apples”, it would be great if PUCs, ISOs, RTOs, and balancing authorities, other regulators, and policy makers used a similar screening process to evaluate SG 2.0 applications at the state, regional, and national level. Of course, the criteria for ranking the desirability of various SG 2.0 applications will vary across different stakeholders.

These governing entities will be looking at the “big picture”, i.e., the SG as an interconnected system. We know that the behaviors of different elements in the SG are correlated. As a result, the benefits of a single SG 2.0 application can accrue in other parts of the power system quite removed from the location of the application. Crucially, these benefits have been omitted from almost all benefit-to-cost studies to date, thus short-changing the estimates of potential total value. Why?

Because simulating regional and correlated system benefits is a challenging modeling task that today is far from perfect. It can be very data- and computation-intensive and the optimization algorithms can be close to intractable. There are a number of efforts underway to create computational short-cuts for these types of simulations (see here and here).

Furthermore, the operation of the physical smart grid system is affected by the operation of power markets, and vice versa – simulating these interacting feedback loops is still in the early stages of development and can provide highly relevant insights on the impact of SG 2.0 applications on regional power systems and markets-- insights that cannot be derived from traditional linear models.

Traditional algorithms will evolve within these system simulators as market structure and protocols continue to be refined.

Through the above advances, we will continue to improve our ability to identify the most valuable nodes in the system.

Business opportunities: The market value of the results of these advanced types of power system simulations should spawn some interesting business opportunities for integrated power system and market software platforms.

But Isn’t the Above Business Case Approach No Different Than What Was Used Before for AMI Investment Evaluations?

Up to a point, yes -- the mechanics are quite similar, but the difference is that now we are dealing with SG 2.0 applications that do not need to be universally deployed.

DSC_0150 150x150We can pick and choose SG 2.0 applications and where we want to deploy them (the “most valuable nodes”) – the business case is our selection tool. And we are sure to face budget constraints that will require a sharp differentiation between short-term and long-term savings, and between quantitative and qualitative benefits for each of the applications, all of which can be handled within the business case framework.

Caveat Emptor Still Applies for All SG 2.0 Investments

We’ve learned some hard lessons, given the disappointing performance (or the over-promises) of our first “smart grid” investments, i.e., AMI systems. We need to be brutally realistic about our assumptions (see Part III). This is especially important in estimating the expected size of SG 2.0 benefits because (1) in the past, “smart grid” benefits have been over-estimated or asserted without credible justification, and (2) a substantial portion of the benefits of SG 2.0 applications are qualitative and therefore subject to legitimate differing views regarding their value.

We also need to pay attention to our assumptions about the time required for deployment (underestimated in the past), and about technology costs and readiness (also previously under-estimated and overestimated, respectively).

On the positive side, there are system and regional benefits that do not appear to have been included in most studies to date due to the computational difficulties of representing them with acceptable fidelity.

Bottom line: like any professional investor, we need to be skeptical. But we can’t eliminate all of our uncertainties.

So, let’s move on to risk management.

Risk Management -- Testing the Sensitivity of Results to Uncertainties

Our base-case assumptions will not all turn out to be correct. Some of them have very broad uncertainty bands. And, given the long time-frames that we are contemplating here, the unexpected is sure to occur.

So, we need to build some flexibility into our deployment plan. We suggested above that simulations of the sensitivity of outcomes can help us determine the risks for which we need to have contingency plans. We especially need to understand the sensitivity of the outcomes to the most uncertain input variables.

DSC_0139_2_2 150x150Uncertainties that affect the benefit-to-cost ratio of SG 2.0 applications comprise a long list. Some examples include the timing of SG-supportive regulatory actions, including incentives (regulatory lag is one of the biggest risks), lagging market structural changes, the impact of new energy policies, technology readiness and costs (some of the business opportunities being promoted today appear to be well ahead of technology readiness), the timeline for the transition to interoperability across the smart grid value-chain, the potential impacts of SG 2.0 applications on reliability and stability (especially in distribution systems), the possibility of coordinated cyber-security attacks, and the unanticipated disruptive technology (an unknown, by definition). The list goes on……

Obviously, risk management is not cost-less.

Analyzing the impact of these uncertainties will identify which ones have the highest impact. It will also provide us with a “cap” on how much we are willing to pay for additional flexibility, “off-ramps”, remediation actions, and/or power system resiliency investments to mitigate the potentially negative impacts of these risks.

Our “Managed Deployment Strategy”

Bottom Line: Our managed deployment strategy for SG 2.0 applications consists of:

(1) A least cost investment methodology based on individual business case evaluations of high-value applications, in combination with

(2) A scenario analysis that evaluates the key risks and uncertainties.

What’s Next?

In our SGiX dialogs to date, we’ve developed a comprehensive picture of the context within which SG 2.0 investments will be made, and presented a methodology for evaluating these investments.

Now it is time to move on to the evaluation of specific SG 2.0 business opportunities and business cases within the value chain of the SG. We are planning to do that in following dialogs.

As always, comments are welcome and appreciated.

Leave a Reply

Your email address will not be published. Required fields are marked *