Should real-time or dynamic rates be the default option for retail customers?
If we really want to allocate resources as efficiently as possible, customers should receive a price signal that reflects the value of electricity at any given time of day. That is the best way, say many economists, for demand reduction to compete with generation during peak periods. Some people argue that dynamic retail rates should be the default option, and customers should have to opt out of them in favor of a fixed rate.
In Texas, we have a retailer called Griddy, whose customers were happy to pay dynamic retail rates when prices were relatively low, but very unhappy when prices spiked last August: https://www.houstonchronicle.com/business/energy/article/Griddy-customers-feel-bite-of-soaring-wholesale-14352985.php
Maybe people are willing to pay a premium for price certainty? Do we need dynamic retail rates?
No, real-time or dynamic rates should not be the default option for retail customers. I say "no" based on the assumption that the desired outcome is the least costly, reliable, and minimally polluting electricity delivered to the consumer.
I also admit that my "no" is in the category of Bill Maher's comedy routine"I can't prove it but I know it's true". As a community, we do not know of a fair way to do an experiment to test all of the alternatives.
But, I am fascinated by the fact that both statistics and individual behaviors affect power system costs. As an example, in Austin, as in most of the US, the standard is for every house to have 200 amp service. With an input voltage of 110 volts, that means every house is capable of drawing 22 kW. Austin Energy tends to serve 6 - 8 houses with one distribution transformer. The transformers are rated at 50 kW or 75 kW, not the 200 kW that would guarantee peak load. Smaller transformers save the consumer money if they are sufficient and they are.
A fundamental reason the smaller transformer is sufficient is that the peak-to-average ratio of loads is large, but from house to house, the loads are relatively uncorrelated. There is some obvious correlation in that everyone sees day and night at the same time, but their reactions to nightfall, for example, have significant differences from house to house. One of our former students was part of an experiment in the Netherlands that investigated the manner by which a neighborhood failed if unusual correlation occurred, e.g., correlated widespread behavior if, for example, one's country is playing a night World Cup game [Hoogsteen, Gerwin, et al. "Charging electric vehicles, baking pizzas, and melting a fuse in Lochem." CIRED-Open Access Proceedings Journal 2017.1 (2017): 1629-1633.]
How to take best advantage of the statistical knowledge available to the utility and the preferences of the customer is the subject of research [van der Klauw, Thijs, et al. "Assessing the potential of residential HVAC systems for demand-side management." 2016 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). IEEE, 2016; Zhao, Changhong, et al. "Design and stability of load-side primary frequency control in power systems." IEEE Transactions on Automatic Control 59.5 (2014): 1177-1189.]
A problem with the centralized average cost is that it is blind to consumer flexibility. A problem with consumer real-time pricing is that the benefit to an individual consumer tends to be minimal or negative over the year compared to levelized pricing. So the consumer ends up with too much work for too little benefit.
The future will likely bring us an improved system than the predominant averaging we use today, but I'm confident that it will not be real time consumer pricing unless it is driven by a flawed, but popular, economic theory rather than reality.