Dynamic pricing: the facts are in
Data over perception = billions of $$ in savings
Two weeks ago, Ahmad Faruqui, a principal at The Brattle Group and pricing expert, urged an audience of regulators in Portland to trust data over anecdotes when considering dynamic pricing.
The audience, of course, was composed of regulators attending the summer committee meetings of the National Association of Regulatory Utility Commissioners (NARUC). If you're familiar with the topic and why only 1 percent of the nation is on dynamic rates, then you'll realize that addressing NARUC on dynamic pricing isn't exactly preaching to the choir.
I caught up with Faruqui after the Portland meeting by phone and we discussed what's at stake, what regulators need to know and why. Faruqui provided his presentation to NARUC, which contains a decision tree of sorts with steps regulators and utilities can take to get "there" from "here." Today's column is the first of three parts devoted to that interview.
Let me just entice you to read the details by stating upfront that:
- dynamic pricing is a least-cost route to improved load factors for individual utilities and the nation;
- contrary to fears, dynamic pricing is most equitable to low-income customers;
- it would save electricity consumers billions of dollars each year;
- it enables energy efficiency goals and load shaping.
"The first factor is the load factor," Faruqui told me. "Nationwide, the load factor is somewhere between 50 and 60 percent. It hasn't improved with each passing year. That means a lot of idle capacity for much of the year. That's the No. 1 issue."
How should regulators think about "load factor"?
"I define load factor quite simply," Faruqui responded. "Take your average load throughout the year and divide it by the peak load. If you had a perfectly flat load shape - the same amount of energy being used every hour of the year - you'd have a load factor of 100 percent. And if you are peaky on some days, your peak could be as much as two times higher than your average load. Then your load factor is 50 percent.
"In most competitive, capital-intensive industries, such as airlines or hotels," he added, "they try to have a load factor above 80 percent.
In the power industry, idle capacity is an under-utilized capital investment. Gas-fired combustion turbines used to meet peak loads only run 200 to 300 hours of the year, or about 3 percent of the year's 8,760 hours. That contributes to a low load factor. The higher the load factor, the more efficient the system and the lower the average cost.
"We are all paying more because of a low load factor," Faruqui pointed out.
"The second issue is fairness," he continued. "Flat rates mean everyone pays the same average rate. Say that rate is 10 cents per kWh. If an end-user is `peaky,' they still pay 10 cents. But that customer requires expensive peak capacity to serve. If another end-user has a flat load profile and therefore is inexpensive to serve, they also pay 10 cents. So there's a cross-subsidy. Those who are less expensive to serve subsidize those who are more expensive to serve."
Faruqui has calculated that cross-subsidy at about $3 billion annually in the United States.
What do regulators tell Faruqui about their concerns over dynamic rates?
"In my view, many regulators tend to think of flat rates as equitable," Faruqui said. "It's like a postage stamp. The same stamp will get a letter across town or across the country. I see three hurdles to changing that perception.
"First, regulators think that flat rates are equitable because everyone pays the same price," he continued. "Second, they have the idea that dynamic rates will suddenly raise prices, leading customers to scream and shout. They don't realize that prices will be lower for most hours of the year and higher for fewer hours per year. They just look at the highest prices and that scares them. The third issue is that regulators tend to think dynamic pricing requires in-home, enabling technology, which is expensive."
Three decades of data provide a factual basis for addressing these concerns.
"I've always argued for a fact-based approach, an approach based on data, to guide policy," Faruqui said, "rather than an approach based on misperceptions and fears. You can look at the load shape of low-income customers and model the results of moving them from a flat rate to a dynamic rate. How many will see higher bills? That's data."
Based on data from an unnamed Eastern utility, Faruqui examined a representative sample of average utility customers' load profiles and another sample representative of that service territory's low-income users' load profile. Then he recalculated their bills with a flat rate and with a dynamic rate. (In this example, a critical peak pricing (CPP) regime.) At this point, he did not assume that customers were responding to the rate by changing their load shapes.
Among average ratepayers, 60 percent have lower bills under CPP, but among low-income customers, 80 percent save with CPP. That means that 80 percent of low-income ratepayers are overpaying for electricity.
"This conclusion is in total contrast to the perceptions held by regulators and consumer advocates, who hold the view that low-income customers will be worse off under dynamic pricing," Faruqui concluded. "The reality is so different from the perception."
In tomorrow's column, we'll examine whether in-home, enabling technology is needed to implement dynamic rates, which pricing regime could bring "big wins" and what incremental steps regulators and utilities can take to move to dynamic pricing.
Intelligent Utility Daily