Today’s technologies – wind, solar, storage – have widely differing cost and operating characteristics to fossil fuels. So the way customers are made to cover those costs – assigning different rates to different customer classes – should change. Jim Lazar and Mark LeBel at RAP explain why and how, referencing their comprehensive manual “Electric Cost Allocation for a New Era”. They describe how the full range of technologies now establishing themselves – from smart meters and networks to distributed generation – can be linked to make efficient cost allocation much easier. The growing availability of hourly-based data can make methods impossible in the past a practical reality today. For example, rich data means different sources of energy can be priced differently, and at different times. Customers can be rewarded for timing their energy use, or installing their own storage to help both themselves and the grid. There’s more on transmission, distribution and electricity markets. The authors describe it as “a well-choreographed ballet”. The monitoring technology is available. It only needs the regulators to guide the players into the dance. The reward is far greater, untapped levels of efficiency and fairer ways to charge customers.
The need for change in how we measure the cost of providing electric service by customer class is obvious to any attentive observer of the dramatic changes now underway in the electric utility industry.
Electric Cost Allocation for a New Era, the manual RAP published at the beginning of 2020, provides detailed guidance on the preparation of embedded and marginal cost studies. It also gives guidance on how to use today’s dramatically better data to ensure that these studies reflect changing technologies, costs and usage patterns.
This task falls mostly to utility technical analysts who prepare these studies, and to parties in rate cases who analyse them. But a significant duty falls on utility regulators to set policy and insist on visionary and rigorous analysis of new issues.
Today we have resources such as wind, solar and storage, providing energy and capacity in different ways and with different cost and operating characteristics than fossil energy resources. We are redeploying transmission lines, originally built to connect remote coal and nuclear baseload power plants, to instead support variable renewable resources and facilitate market transactions that reduce energy costs.
Where once we required remote generation and transmission, we now have smarter distribution networks and distributed energy resources that provide modern energy, capacity and grid services. All of this points to the need for reforms in cost allocation.
Modern cost allocation
The modern cost allocation study must do many things that studies of past years may not have considered:
- Separate the treatment of different kinds of generating plant, such as baseload, intermediate, peaking and non-dispatchable variable renewables.
- Recognise the multiple purposes of transmission facilities: to connect baseload units, to connect remote baseload and variable generation, and to facilitate market transactions buying energy from the nearby market where it’s cheapest.
- Identify the nature of distribution system component functions, no longer simply to connect customers to a centralised grid, but also to facilitate demand response, energy efficiency, time-shaping of consumption, and integration of distributed energy resources that may serve all customers.
- Recognise a wide variety of costs that have benefits across functional areas, including demand-side resources of all kinds and advanced metering.
Much better data
The modern cost study requires better data and more attention to detail on the part of the cost analyst. While [U.S.] federal law has included a PURPA standard for time-of-use cost allocation analysis since 2005, nearly all cost studies prepared a decade and a half later continue to ignore this. Fortunately, modern smart meters and the associated data collection systems now in place for more than half of U.S. electricity consumers can quite easily provide the needed granular data to support time-of-use analysis.
This allows utilities to measure individual and class loads on an hourly basis and unlocks a wide array of potential analytical improvements. For example, baseload resource costs can be properly assigned to all hours, and other generation costs on a time-varying basis — to the appropriate hours when they are used to provide service.
Customer class rate designs that rewards behaviour
The modern utility regulator is also faced with a broader challenge of an energy system transition including the gradual introduction of improved customer class definitions and improvements to rate design. Cost allocation studies, and particularly the underlying analyses in those studies, can be a core part of these important reforms.
The result should be a set of customer classes, cost allocations, and ultimately rates that properly reward the types of cost-minimising behaviour that is now available. Customers able to flex their loads to fit the least costly time periods should be able to do so, and when they do, should reduce the costs allocated to their class and to their own consumption. This will include:
- Customers shifting loads, such as space heating and cooling, water heating, electric vehicle charging, industrial process needs, and ultimately, smart appliances down to and including laundry, lighting and data processing.
- Customers installing on-site energy storage, which may be controllable by the utility to provide grid services in addition to customer services.
- Behavioural changes in consumption due to time-varying cost periods flowing into time-varying pricing.
- Cost savings in generation, transmission and distribution cost from a network that takes advantage of both central and distributed resources, increasingly functioning as a well-choreographed ballet involving efficient markets, efficient data transfer and efficient consumer actions.
The monitoring technology is available. The regulators need to enable it
Achieving these goals will not be easy. It will require smart systems, smart system operators and smart regulators. The technology to help achieve all of this is available. The skills to use modern data, design modern studies and implement smart changes may be elusive without significant guidance from regulators.
Regulators will also need to maintain oversight to ensure that data collection, data analysis, costing model design, presentation of study results, and proposals for changes in class definition and cost allocation are done in an open, collaborative and constructive fashion. This can maximise both the net benefits to be achieved and the equitable sharing of those benefits.
This article is published with permission