Chris Lewis, Cognera Corp.
If modification of customer behavior is a goal of America’s smart grid, then dynamic pricing is the one tool that should make this goal a reality. Like any well-deserved goal, however, there is no easy way to make this happen.
Dynamic pricing is not new. Airlines have used a variable pricing scale that increases as flights become more popular, as have hotels. One of the best examples of dynamic pricing is in e-commerce. The advent of the Internet as a sales channel powered by technology allows for prices to respond quickly to signals of supply and demand, and dynamic pricing is really a discussion on supply and demand.
In the electricity industry, the signals of supply and demand vary moment to moment. Supply-side variables that change include fuel costs and type, generation unit age and efficiency, transmission system congestion and the order of units that must be called on to meet the demand. Demand side fluctuates even faster. The act of a large industrial user starting a new process, say the elevators all operating in a downtown core or Christmas lights turning on in the homes in your city, all impact electricity demand instantly, and, therefore, impact the amount of electricity that must be ready to supply these demands. In an industry with no storage of the output product, the only way to adequately match supply and demand is with lots of data.
The evolution of the power industry is calling for a vast increase in data, transmitted as frequently as every 15 minutes, and eventually moving to real time. The goal is to know how much is required and consumed by every home, business and streetlight. We might know down to the process or appliance in our homes what consumes the most electricity, and utilities hope we can learn to manage that power use to decrease the amount used at the highest times.
As KEMA stated in its “Texas Smart Energy Report,” “If it’s not about saving money, consumers don’t care.”
The only way the average consumer would actively begin to manage power consumption is if there were a significant enough incentive to do so.
Other disruptive technologies that have changed the lives of the standard citizen have done so on the back of incentive. Often, these incentives have not been blatantly economic. Personal computers brought the power of mainframes into homes. E-mail changed the lives of basically everyone in the developed world because of the convenience of chatting instantly. Satellite TV brought hundreds of channels to our fingertips. Cell phones brought portable communication and a previously unknown sense of security to people. And the Internet brought access to instant information.
In many of these cases, the new technology benefits cost people more, but the benefits of the technology itself was worth the extra cost. Let’s apply that concept to the smart grid and the prospect of adjusting behavior to reduce consumption.
It is hard to imagine the long-term, large-scale benefits of smart grid being within the immediate future. These things take time, whether they are improved convenience, security, access to something valuable or greater choice. Furthermore, the benefit of environmental stewardship and emission reduction will appeal to a small subset of the population. The best, most recognizable incentive to make smart grid technology common is an economic benefit. Enter dynamic pricing.
Making pricing variable and more closely linked to actual costs that utilities face will produce price signals that will be considerably higher at certain times of the day and times of the year. Pilots with critical peak pricing and real-time pricing options have seen reductions of up to 44 percent, showing that there is a direct correlation between price and customer behavior if incentives are recognizable.
The challenges, however, are twofold. First, how can the utility impact the actual execution of the behavior change from participants? Second, how can the unbundled energy and capacity provide a clearer price signal for participants?
A study of participants in the CNT Energy Power Smart Pricing Program showed that while 88 percent of participants changed energy use after joining the program, only 62 percent of participants ever checked prices, and only 30 percent of those checked daily.
This evidence of participant ambivalence of the dynamic pricing structures is a cause for concern and guided optimism. The general public is not concerned with the pricing models themselves but in the result these structures produce. So what does this mean to the utility?
First, it might mean that the dynamic pricing methodology being deployed in products and services is not meeting the areas of concern for consumers. The utility must ask if the data it is collecting provides ample proof that the pricing structures it uses provide the proper incentives—positive and negative—to establish the behavioral change it desires. Typically this means looking deeper than surface-level data and requires a consumer-focused product development process.
Building products and services with consumers at the center is not a developed strength of the industry. Utilities must learn from proven industries around them. Building pricing products must recognize the value of time and convenience for the subset of consumers. It must recognize that many small businesses, although theoretically set up to adjust behavior, will not compromise their businesses for a few dollars.
That might be where the biggest challenge of dynamic pricing lands. To affect the changes desired by utilities, the onus must be on two key things:
- 1. The utility to define the product structures that are meaningful, and
- 2. The pricing signals must be punitive enough to generate a genuine comparison between the consumer’s current state and the new cost of that current state.
A comparison of average electricity prices from regions around the world shows that the U.S. has one of the lowest costs for electricity (see chart). This creates a challenge that even a substantial change in behavior may have a minimal economic impact—pulling all of the fixed and variable costs of generation together in real time to produce real price signals for the end consumer. Many costs that translate into the price of electricity are not known or calculated in real time and, therefore, not available to provide these real-time price signals. Even in markets that use a central or spot market for power prices there are still multiple iterations of settling the final costs to achieve the actual price in any given time. By simply reviewing the chart, you can see that the variance in pricing from one place to the next in Europe is wide. The difference in the final price of electricity in the U.S. would not be very different from state to state. When the actual prices are calculated and coal is no longer an option, the prices will likely not be so different. How is this challenge overcome?
Overcoming the Challenges
First, smart grid investments are focused on better analysis and collection of data along the supply side. This data will provide as close as possible to the actual costs associated with the generation, transmission and distribution of electricity.
A continued focus must be on this side of the smart grid to assure that the pricing information can be close to real time without multiple adjustments. Dynamic pricing and the consumer-side initiatives become less enticing if there is no faith in the pricing signals that trigger new behaviors.
Second, in the first phase of smart grid, price signals inevitably will begin to be more variable, and the average costs will go up considerably. These new, higher prices will become the reality for most consumers, in a way no different than the increase in the price of gas for our cars. This negative incentive will be the foundation for ongoing savings through behavior changes. If average prices began to approach the levels of France, the U.K. or Germany, behaviors would change quickly.
The final challenge is consumer ambivalence. This provides an opportunity for “set it and forget it” technologies to be the center of the consumer smart grid experience. Through technology vendors and utilities themselves, the opportunity to build products and services that are low-contact and even controlled by the utility or a third party will speed the adoption of dynamic pricing and the benefits it promises.
The combination of the following will make dynamic pricing the tool of choice for smart grid goal achievement:
- Increases in supply side technology,
- Consumer understanding of pricing structures,
- Electricity costs that produce negative incentives that are aligned with the reality of the global costs of electricity, and
- Products and services that will speed the adoption of demand side technology.
Chris Lewis is manager of sales and marketing for Cognera Corp. He has held leadership positions with Enmax Energy and Direct Energy. Prior to his work in the utilities industry, Lewis was a professional football player and a former member of the Calgary Stampeders in the CFL.