The price of most goods we purchase is generally based on the costs associated with the goods’ production, including the raw materials used to generate them, the labor associated with their manufacturing, and so on. However, when it comes to pricing residential electricity, many regulators choose to use a flat price per unit of electricity (kilowatt-hours, or kWh) that unfortunately fails to adequately reflect the underlying costs of generating and delivering energy to our homes.

This creates incorrect incentives for conservation and investments in distributed energy resources (like rooftop solar, energy storage, and demand response). Getting these incentives right can go a long way in creating more opportunity for efficiency and clean energy resources.

Pricing electricity generation

The cost of generating electricity from large-scale power plants varies significantly over the course of a day. When demand is low, electricity providers call upon the most efficient and inexpensive power plants to produce electricity. As demand increases, they also must utilize more inefficient and expensive power plants. So, for the price of generation to accurately reflect these costs, it, too, must vary with the time of day. Time-variant pricing charges customers more for using electricity during periods of high demand (such as during hot afternoons) and less when demand is not as great. This pricing system is an accurate reflection of generation costs.

In contrast, flat rates that don’t vary over time incentivize customers to consume more electricity when it’s most valuable to them, even though consuming during times of high demand places a larger cost on the system. Thus, the current, static pricing system creates incorrect incentives for conservation and electricity use.

Pricing electricity delivery

At the other end of the system, we have the local delivery of electricity, which relies on infrastructure such as substations and distribution lines. To understand the challenges associated with pricing this part of the electricity system, a useful analogy can be found in bike share programs – such as Citibike in New York City.

These programs are made up of certain resources – a number of stations and bikes at different locations – that are difficult to increase in the short run even though demand for these bikes is shifting throughout the day, year, and location. Currently, customers usually pay a fixed fee for having access to bikes at any location and time. However, this way of pricing can cause problems: during peak times, increased demand from commuters reduces the availability of bikes at the most popular stations. Accurate pricing could alleviate this.

For example, customers could be charged extra for using bikes during peak periods, and potentially even charged more for renting at popular locations. This would reduce the demand for bikes at these key times and locations. We can extrapolate the same kind of logic to pricing electricity delivery, where the infrastructure and, thus, the costs are generally fixed in the short run. However, high demand can cause constraints, forcing utilities to replace strained infrastructure or expand the system, leading to greater costs in the long run.

Unfortunately, similar to the Citibike example, most customers pay only a flat fee per unit of electricity they use in order to pay for these infrastructure costs. This charge does not send the signal that high demand during peak times causes constraints and increased costs on the delivery system.

There are different possible approaches to efficiently recovering the costs associated with the delivery system. One option is to implement time-variant pricing as described above, where electricity use during the delivery system’s peak hours is more expensive.

Peak demand charges

Another option is to use peak demand charges. These charges make it more expensive to use a lot of electricity simultaneously during certain high demand hours of the day (e.g., running your dishwasher, dryer, and TV all at once). This is because in doing so, you are demanding more from the electric grid at one time, increasing the need to expand the system over time.

It’s like timed lights for merging onto a freeway. If all the cars were to merge at once, there would be constant back up at high traffic times and locations, which could lead to a widening of the freeway on-ramp. Instead, the lights stagger the cars, lessening the traffic and the need for expensive construction. So, by giving customers an incentive to stagger their appliance use throughout the day, the maximum demand would be lower and grid planners could reduce the size of the system, saving money.

Utilities have not implemented peak demand charges in a widespread manner for residential customers, but they present a promising new price option when carefully and thoughtfully carried out.

There is an important caveat. While employing these tools can have positive effects on the electric grid and reduce costs, regulators and utilities need to ensure they do not harm low-income customers — people who already bear a heavier energy burden than others. Studies show solutions like time-variant pricing work well for these customers, but education and technology enablement are essential for success. By providing people with tailored information about these tools and access to technology that can help them take advantage of them, they can shift their energy use and save money on their monthly bill.

Pricing environmental impacts

Electricity charges that more accurately reflect the cost of generating and delivering electricity can help send the correct price signals to customers for conservation and distributed energy resource investments. But, something is still missing: how do we price the environmental costs of electricity production? These external costs (including greenhouse gas emissions, water consumption, and local air pollutants) can be quite large, and are currently not reflected in the price we pay for electricity.

Importantly, each unit of electricity has a different amount of external costs associated with it, depending on the efficiency and cleanliness of the power source. If each generator were responsible for paying the external costs, then cleaner, more efficient generators would pay less than their dirty counterparts, making clean electricity cheaper. This would have two impacts:

First, in a well-functioning market, the dirtier generators would have higher costs, and would therefore be utilized less, leading to a reduction in harmful pollution from these sources.

Second, because these prices would be passed on to customers, electricity would be cheaper when it is cleaner. Time-variant pricing that incorporates these environmental costs can thereby prompt customers to use less energy during times of the day when the system relies on dirty power.

By ensuring these costs are internalized by the generators, time-varying electricity prices can reflect these external costs, helping us reduce harmful pollution and other negative impacts on the environment.

When electricity prices reflect costs, everybody wins

Electricity pricing that accurately reflects the underlying internal and external costs of producing electricity can lead to better, more efficient use of energy, more targeted distributed energy resource investments, and a direct reduction in emissions, resulting in a cleaner and more efficient electric system for all.

Beia Spiller is a senior economist with the Environmental Defense Fund. Kristina Mohlin is an economist with the EDF. This blog post is part three in a four-part series that takes a deep dive into economics of the electric system and the role pricing can play in accelerating the clean energy economy. It originally appeared at the website of the Environmental Defense Fund.