The electric industry hasn't seen so much upheaval since Thomas Edison threw the switch at the Pearl Street Station. Full retail access to competitive markets in generation and supply will...
Real-Time Pricing: Ready for the Meter? An Empirical Study of Customer Response
greater response to real-time pricing than do customers in other groups. Those seven SIC groups are reserved for: Mining (SIC code 14); paper (26); stone, clay, and glass (32); primary metals (33); machinery and equipment (35); water and sanitary services (49); and hospitals (80).
For customers without on-site generation, 86 percent of those in the seven listed SIC groups respond significantly to hourly prices, as opposed to 65 percent of all other customers. Their flexibility parameters average about three times the magnitude of customers in other SIC groups (.12 compared to .04).
Nevertheless, despite these general observations, few empirical studies have been published on customer response to RTP. To add to the available pool of evidence, in this article we present an empirical study using 1995 data that calibrates own-price elasticity of demand under real-time pricing for a group of four anonymous industrial customers.
Overall, our study confirms that customers can and do shift their usage patterns in response to real-time rates. Our study breaks out the data into two sets, corresponding to prices below and above 6 cents per kilowatt-hour. This breakout shows that the coefficient of own-price elasticity was more likely to be negative (showing a drop in purchases of electricity as price increased) for price levels above 6 cents than for prices below that threshold level.
Is temperature relevant to the price response?
In our study the data were taken from the summer months. A large portion of the electricity could have been consumed by the air-conditioning and ventilation systems. To measure this, we obtained hourly weather readings and included temperature as an explanatory variable. Surprisingly, however, the effect of temperature on consumption of electricity appeared mixed and inconclusive in our study. One explanation might be that some industrial processes are sensitive to temperature and are shut down as the mercury rises, thus reducing overall power demand. Another possible explanation is that the presence of on-site generation may alter demand for electricity.
Some Factors That
Average statistics for customer response to real-time pricing can mask considerable variability among customers with different characteristics. Responsiveness depends on a number of key factors. These factors can be divided into the following three main categories: incentive, ability, and willingness. That is, the greater the financial incentive that a customer has to shift load, the greater is the likely response. The size of the incentive depends on the amount of price variation and the relative importance of electricity costs as a share of overall operating costs. Similarly, a customer's ability to shift load depends in part on factors such as the presence of on-site generation that can be used to replace purchased power, and the flexibility of the customer's production process. Examples of the latter include the sensitivity of the production process and the ability to store product on-site. Finally, even with an incentive and the ability to respond, a customer may have the willingness to take the initiative to review the transmitted hourly prices and change its operations. Various business needs or operating styles of both management and operating personnel are