As I wrote
recently , technologically, the current U.S. grid system has not changed much over the last few decades. The old systems provide little understanding of the actual usage until the meter is read on a monthly basis, allowing little maneuverability to utilities during high electric usage. As electricity usage increases over time, particularly with increased popularity of electrical vehicles, utilities need to be able to properly manage peak time usage in order to avoid overtaxing their systems, or worse, blackouts.
One of the advantages of upgrading the grid infrastructure with IT bells and whistles is visibility into real time usage, which leads to the concept of 'dynamic pricing,' also known as time-of-use pricing. This allows utilities to charge based on a pre-determined time of day or week, much as airlines charge differently for flights at different times of day or the week. The idea is to encourage consumers to use electricity at non 'peak time' to avoid overtaxing the grid system.
Pricing variance and complexity
Electricity prices in United States are notably lower compared to European nations, as well as other industrial nations. With relatively low prices, the entities most affected by price change (and therefore most likely to change behavior) are very high-use entities such as industrial businesses, and low income consumers who are sensitive to slight price changes. So, unless the punishment for peak time use or the incentives for non peak time use are very high, I'd be surprised to see mass behavior change in time-of-use from average consumers strictly based on price movements. And if the price increases are severe enough to instigate behavior change, the utilities will most likely face equally severe backlash from consumer groups and business organizations.
Clearly, not all users will be treated equally. Various types of dynamic pricing are currently being employed or being considered for implementation around the country including two-part pricing, real-time pricing, critical peak pricing, and peak time rebates. Considering the complexity of each of these pricing structures, it would be presumptuous to believe anyone other than the most sophisticated users such as industrial businesses and a small percentage of consumers would understand the pricing structure, let alone change their behavior for compliance. The question becomes, which one of a variety of pricing structures will be suitable for each customer type, and how will the utilities prepare the user community for these changes.
Consumer education critical to behavior change
Several utilities have experienced mishaps in the rollout of their smart meters including incorrect billing and problems with integrating the new technologies with solar panels . I consider these problems to be of a technical nature, and expect eventual fixes for them.
However, the main challenge utilities will face is to educate the user community to switch from a flat-rate pricing model to dynamic pricing structure based on multiple variables. The utilities will need to engage in thorough communications with consumers and businesses to avoid backlashes from unsuspecting customers who suddenly face price increases.
Rate stability and rate transparency will be important factors to both residential and business customers, and super-complex structures will be limited to industrial businesses, and a simpler, easy to understand rate structure will be more suitable for residential users.
A word about consumption feedback
Allowing the consumers to view their own electricity usage from their smart meters is viewed as one way to reduce usage or behavior change. While this sounds like a valid proposition, it most likely fails in practice .
A recent study by Boston Consulting Group found that 'the majority of consumers surveyed are willing to tap into the information from smart meters to conserve energy.' That sounds great until it's revealed that the survey was conducted online (I bet my octogenarian father wasn't surveyed; 'smart what?' I can just imagine him saying). And having performed several market research studies, I'll have to be somewhat skeptical about the survey subjects' utopian ideas of what they think they will do vs. what they will actually do in practice.
If I sound skeptical about behavior change based on feedback, it's because I am. These studies need to be performed on large and varied groups of subjects and over a long period of time to be considered valid. Consumer behavior is difficult to change, particularly relating to a topic as mundane as electricity usage (we're not talking about sexy iPhone applications here). Other studies have measured the effect of feedback on conservation, and the reported variance of 'negative to 18 percent' conservation based on feedback is too high to substantiate actionable results. The same studies showed that 'feedback provided in conjunction with dynamic pricing can have an incremental effect on peak reduction in the 0 to 2 percent range', perhaps significant in severe circumstances but not significant enough in terms of mass behavior change.
Dynamic pricing or dynamic peak time?
With the increasing adoption of solar and wind energy on the supply side, and electric vehicles on the demand side, electric utilities will face new challenges in determining the new peak time compared to their historic norms. Will EV users plug in their cars when they go to work in the morning, or when they get home after work? How will peak time shift when a significant number of solar panels kick in mid-day, currently considered the historic peak time? And if industrial users and consumers are pushed enough to change their consumption behavior, wouldn't that shift 'peak time' even further?
The expected fluctuating nature of the grid peak time needs to be considered into the implementation of any dynamic pricing structure. I would further argue that the discussion should shift from 'dynamic pricing' to 'dynamic peak time' prior to any valid pricing considerations. But if we insist on a change in pricing structure, perhaps the pricing structure can dynamically shift for users surpassing a significant threshold from a simple structure to a more sophisticated structure. Or maybe utilities can implement control systems so that users with special needs (such as EV owners) can allow the utilities to shift non-urgent electricity use to pre-determined times. One can dream up all kinds of scenarios, but that would be one 'smart' grid system.
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Edited by
Michael Dinan
