A version of this article was originally published on May 4, 2016 on Greentech Media.
By Michael O’Boyle
Utility regulation is getting harder. Before information technology’s rise combined with plummeting costs of energy efficiency and customer-sited generation, utilities had relatively few options for minimizing costs while achieving a balance of reliable, safe, and environmentally clean service. But distributed energy resources (DER) and better system awareness made possible by information technology have created massive new opportunities to optimize the system around these outcomes.
This proliferation of solutions has reduced regulators’ ability to review investment plans and ensure they produce optimal results reflecting the public interest. If utilities are to serve as system optimizers, regulators must address the information asymmetry that strains cost-of-service prudency review to maximize the public interest.
The regulatory review times, they are a changin’
Historically, regulatory review and utility investment were straightforward. Economies of scale were universal—pooling one set of resources and spreading costs over a broad base of customers was the most economically efficient way to build out the power system. Because greater investment tended to yield greater value, the revenue model for utilities rewarded shareholders for ever-increasing investment, which in turn ensured the benefits of increasing scale.
As a result, regulators tasked with reviewing utility investment plans line by line had enough information to determine, with some margin for error, whether investments were producing outcomes that reflected the public interest. Regulators maintained prudency review as a hedge against poor or excessive utility investment choices and as a proxy for competitive pressure; only what was “used and useful” could be recovered from captive customers.
But today, the sheer magnitude of options for electricity system optimization has rendered cost-of-service prudency review insufficient for simulating competition. Economy of scale, while still applicable in most cases, is no longer the universal truth it was when the rate of return regulatory model became standard. Without this certainty, regulators can no longer have confidence all “used and useful” investments are actually the optimal solution.
The role of information
Today’s technologies and big data fundamentally change the suite of options for delivering an affordable, reliable, and clean electric system. As power system optimization options proliferate, regulators find themselves in an era of rising information asymmetry vis-à-vis the utility. It’s no longer as simple as looking at electricity demand and determining whether or not it’s prudent to build one more centralized generator to serve it, or one more transmission line to bring power to a new area. Instead of focusing on construction and expansion, utilities’ new role should be to optimize the system using a portfolio of distributed and centralized resources.
There may even be unknown unknowns—most utilities may not even know where latent value lies in their system to be captured by, for example, customer-sited generation. Without vast swaths of data and the resources to digest it, regulators cannot know what options utilities have for optimizing the system, and thus what constitutes prudent investment.
If the utility’s role is still providing universal service that maximizes the public interest, a new role for regulators and utilities needs to be defined to deal with rising information asymmetry. As California Public Utility Commissioner Mike Florio put it in a recent ruling, “given the complexity of the distribution system, this Commission is ill-equipped, at least at present, to determine with the necessary specificity exactly when and where . . . DER deployment opportunities may exist. . . . Practically speaking, command-and-control regulation faces major challenges in this context.”
In this era full of many more options, regulators’ roles in determining utility investment prudency now lies on a new spectrum. On the “information-intensive” side of the spectrum, regulators double down on prudency review by increasing regulatory resources and staff to analyze more transparent data. On the “outcome-focused” side, regulators reform utility revenue models to reward outcomes reflecting system optimization and the public interest.
Each approach has benefits and drawbacks, but both deal with the information asymmetry that makes standard rate of return prudency review an ineffective tool to simulate competition.
An “information-intensive” approach
Distributed energy resources provide a stack of benefits including transmission, generation, and distribution capacity deferral, as well as societal benefits and operational efficiencies including greater reliability. A data-driven approach recognizing and appropriately valuing these attributes goes a long way towards maximizing the net benefits to consumers by ensuring regulators, stakeholders, and system planners have adequate information to determine the combination of centralized investment and DER deployment is in the public interest.
For example, to understand how DERs can avoid distribution system costs, utilities and their regulators require precise information about the locational value of DER. This means utilities must accumulate and process customer usage data in conjunction with location-based assessments of infrastructure needs – no small task for businesses built under the safe assumption traditional distribution infrastructure investment was always the most economical solution to reliability concerns.
The California Public Utilities Commission’s (CPUC) Distributed Resource Planning (DRP) proceeding demonstrates the heavy lifting required to acquire this information through an information-intensive approach to utility planning and regulatory review. In their proposed DRP work roadmaps, the state’s investor-owned utilities indicated they needed upwards of five years to accumulate data and complete demonstration projects to accurately compare DER investments against distribution infrastructure investments, although some stakeholders dispute this timeline.
If the CPUC approves the utility proposals, demonstration projects would occur in conjunction with $5-6 billion in proposed grid modernization investment, half of which is driven by investments to collect and process locational data. While significant evidence suggests some data could be acquired more cheaply from non-utility sources, the scale of investment requested by utilities and the regulatory back-and-forth suggests significant financial and regulatory costs to enabling, among other things, comparison of DERs and centralized investment.
But on the positive side, this kind of upfront investment in data would allow a more nuanced assessment of the prudency of subsequent utility investment and yield other operational benefits. Of course, even with the data available, regulators still face the tall task of synthesizing it and comparing alternatives to utility proposals. However, the transparency created by locational value would allow stakeholders (including DER providers) to identify solutions, supplementing regulatory capacity.
The “outcome-focused” approach
On the outcome-focused side of the spectrum, regulators can prioritize creating utility incentives to pursue the most efficient system optimization solutions without relying so heavily on a line-by-line review. Performance-based regulation ties utility shareholders’ returns on equity investments to achieving outcomes. If calibrated correctly, utilities’ primary avenue for increasing the value of their company no longer lies in capital investment, it lies in system optimization.
In this scenario, the regulatory role shifts to defining system goals and calibrating incentives to elicit desired utility behavior. Defining reasonable targets (e.g., peak demand reduction) requires regulatory resources, but these pale in comparison to the cost of making locational value transparent. The question then becomes, how much should we pay for these outcomes?
The answer may depend in part on the amount of information asymmetry to overcome. The harder it is for the regulator to identify latent value, the more they might to be willing to pay the utility to find it – certainly in line with the “information intensive” approach where cost scales with data requirement. But evidence suggests utilities may be motivated to consider DER alternatives even with a relatively small amount of revenue at stake, meaning regulators must balance the cost of obtaining enough information to set the utility incentive with the risk of arbitrary compensation.
For example, ConEd’s Brooklyn Queens Demand Management project allows the utility to obtain an elevated rate of return on a $200 million DER investment that, in conjunction with incremental utility infrastructure investments, would defer a $1 billion substation for 10 years. The utility receives a rate of return on DER payments that is higher than the regulated rate of return on capital investments, but low enough to preserve significant value for customers.
In a recent ruling, CPUC Commissioner Florio proposed a similar pilot relying on utilities to identify areas where DERs can defer distribution investments in exchange for a percentage return on the DER investment equivalent to the regulated rate of return on a traditional capital investment, less the IOU’s cost of capital. Both models incent the utility to identify latent value in the distribution system in response to increased shareholder returns tied to system optimization. Both models end up saving customers money and improving utility performance. But regulators may not know until after implementation whether they over- or underpaid to change utility behavior.
Is there a better approach?
Where regulators end up on the spectrum between an “information-intensive” approach and an “outcome-focused” approach may reflect a philosophical position – should regulators allow less stringent review and focus on outcomes, or does their role require a heavy-handed approach to reviewing monopoly investments?
But the question can be reframed as “what are the costs of each approach to overcoming information asymmetry?” Regulators can compare the upfront costs of the “information-intensive” approach with the costs of utility incentives under the “outcomes-focused” approach, along with the benefits of each for meeting policy goals.
Where regulators end up on this spectrum will depend on the appetite for experimentation, the regulatory resources, and the unique nature of “public interest” for customers in each utility service territory. But in an era of ever-increasing options for power system optimization and ever-rising information asymmetry, regulators will have to find ways to improve outcomes through a combination of utility incentives and improved data access.