Calculating an Electrification Subsidy that does not Raise Electricity Rates

Hypothesis: There is an amount of capital every utility could spend on a customer’s electrification asset per kWh of incremental new load without raising electricity rates.

Every utility generates earnings based on a specific revenue formula set by their local regulatory commission. That formula determines the electricity rate ($/kWh) that the utility’s customers need to pay in order for the utility to cover its operating expenses and earn a modest return (set by the regulators). The formula tracks two major categories of spending by the utility: 1) operating expenses that the utility simply needs to recover dollar for dollar and 2) capital on which the utility is entitled to earn a profit. Capital spending is generally on the physical infrastructure that makes-up the grid and has many years of useful life. The accumulation of this capital spending over the years (taking into account the depreciation of that infrastructure eventually rusting and deteriorating) is referred to as a utility’s “rate base.” The general form of a utility’s “revenue requirement” formula looks like:

If we assume that we are examining a deregulated utility that cannot own, and therefore rate base, generation then we can disaggregate this equation a bit:

Now, our goal is as follows:

For deregulated utilities, the cost of procuring energy is an operating expense on which the utility earns no profit. Deregulated utilities can only rate base investments that are part of the “delivery” service of the grid (i.e. transmission, distribution, and arguably other downstream equipment that helps ensure reliable and low cost service). Therefore, the following simplification can be made:

For the sake of producing a simpler, first-order result, one more simplify assumption can be made: a utility’s annual non-energy operating expenses are constant regardless of the amount of energy delivered. In other words:

This assumption is easy to agree with for small increases in behind-the-meter load (e.g. if I buy an electric car, the wires running to my house do not get more expense to maintain). In fact, this assumption may be easy to believe as long as the load being added is within the hosting capacity of the existing wires. However, it admittedly breaks down when very large changes in load are considered or when the power draw from many smaller increases in load are coincident (or the timing of those loads causes excessive wear on the distribution system). For the purposes of evaluating residential and small/medium commercial electrification subsidies, this assumption seems reasonable.

Now, to complete our analysis, we simply take the derivative of the rate base with respect to the load:

Further, we could take the inverse derivative and get:

So what does this mean?

A utility could offer a subsidy of approximately $1 per kWh of new annual load to any customer looking to invest in a behind-the-meter electrification project so long as that project was within the hosting capacity of the customer’s existing distribution service. Any project that provides less than 1 kWh of new annual load per dollar of subsidy (added to rate base) will have the effect of increasing electricity rates, whereas any subsidy that provides more than 1 kWh of new annual load per dollar of subsidy will have the effect of reducing electricity rates.

It is important to keep in mind that this is a simplified model for the sake of producing a clean analytical solution. Analytical solutions are nice for the purposes of initiating strategic conversations about how utilities and regulators can rationalize the financing of behind-the-meter electrification:

Knowing just a utility’s rate of return and non-energy electricity rate, regulators can get a ballpark estimate of how much they can subsidize electric vehicles and heat pumps without unfairly socializing the cost.

Like most things, however, the complexities of the real world require a numerical approach to provide the accuracy and precision that the analytical solution cannot. For instance, the analysis above is a slightly high estimate of such a subsidy because depreciation, customer behavior, and 2nd order distribution system cost increases have not been factored in. Properly implementing a behind-the-meter subsidy for electrification assets requires a customer-by-customer understanding of 1) how much their low-voltage distribution system can support in the context of surrounding customers’ choices, 2) how the customer will use the new electric load, 3) how much it would cost to install on that specific building, 4) how much value it could provide to the grid in that location if it were to be partially operated by the utility, and 5) how the operations of the asset affected its depreciation off the rate base. Further, public utility commissions may have other social priorities than holding rates constant (especially in a post-COVID world). They may prefer to hold “average customer bills” constant or want to pursue the overall least cost path to decarbonization or progressively weight the subsidy towards lower-income households. Each utility region will have different sociopolitical priorities (large utility regions may have different priorities from town to town or county to county). Addressing all of these questions and constraints requires assembling data that is geographically granular, temporally granular, and comprehensive enough to put each utility customer into context. One could even imagine using such data to rank order which behind-the-meter electrification projects provide the most bang for their buck (i.e. the highest capital efficiency as calculated on a building-by-building basis), allowing utilities to quantitatively demonstrate prudent investment plans.

Jake Jurewicz offers professional consulting at 1st Principles Consulting, LLC.