Time-of-use (TOU) pricing might seem like the ultimate solution to ensure electric vehicle charging loads won’t overburden the grid. But will TOU rates guide drivers’ behavior when it’s time to...
Dynamic Pricing Solutions
How to account for lack of strong price signals. A hard year puts deregulation to the test.
confident that demand-side resources are as reliable as generation resources and will fully participate in the day-ahead price discovery process.
Boosting this confidence will require more than installing interval meters and extending MHP programs. It also will require clear evidence that a sufficient proportion of customers have made their operations flexible enough to curb use at the time of the system peak. Such investments only can be justified and likely to occur, if the hourly retail prices that customers face are sufficiently high for a sufficient number of hours. This creates a Catch-22: Hourly pricing customers are not likely to invest in the equipment and processes needed to enable demand response unless they are subject to significant hourly price signals. But significant hourly price signals at the time of the system peak are not likely to be forthcoming until policy makers dial back the minimum capacity requirement and the capacity demand curve. And for this to happen there would have to be evidence that a significant portion of customer load has the operating flexibility to reliably respond to hourly price signals.
Some suggest the answer is to simply pass through the NYISO’s hourly real-time price to customers, since real-time prices considerably are more volatile than day-ahead prices. Indeed, the hourly real-time price in the Albany region peaked at $1.04 in 2006 and $1.29 in 2007. But despite the volatility, the real-time price is no more likely to send a strong signal at the time of the system peak than is the day-ahead price (see Figure 3) . For example, the annual peak in the hourly real-time price in 2007 occurred at 5 p.m. on October 18, 2007, when the electric system load was far below the summer peak. More important, the hourly real-time price is posted at the end of each hour, so whatever signal the real-time price contains occurs after customers already have consumed energy. Studies show that customers subject to an hourly real-time price for default commodity service are more likely to seek out hedged commodity service to escape the volatility and stochastic nature of real-time prices. 4 In contrast, customers subject to day-ahead hourly price for their default service are more likely to remain on this service, and modify usage in response to price signals, because they know in advance what cost they will avoid by curtailing or shifting load.
Retail Capacity Rates
If we accept the premise that capacity requirements, the capacity market and the administrative demand curve are here to stay, there is still a promising way to send strong and persistent signals to customers at the time of the system-peak. Utilities can collect capacity costs in their retail commodity rates in a way that more accurately reflects when these capacity costs are incurred, and that reflects the role that customers play in driving capacity costs higher. To quote Paul Joskow, a leading figure in wholesale market design “It matters how capacity payments are reflected in retail prices.” 5
In large part, capacity costs in New York are determined by the amount of electricity that customers jointly