Estimating the Customer-Level Demand for Electricity Under Real-Time Market Prices

Customer Response to RTP in Competitive Markets: A Study of Niagara Mohawk’s Standard Offer Tariff

“…This is partly true because the translog has the Cobb-Douglas form (a form that implies unitary elasticities of input substitution) as a special case. Patrick and Wolak (2001) found this to be problematic in an application of customer demand for electricity under real time pricing and argue that the GL model is superior to the TL model because it has a fixed-coefficient Leontief technology as a limiting case, and therefore, it can reflect rather modest substitution possibilities. However, these authors also note that if one imposes global concavity, the GL model loses some of its flexibility-in particular all inputs must be substitutes.…”

“…There is, however, a paucity of information in the public domain to quantify the ability of customers to respond to the imposition of RTP, a critical element of such modeling endeavors. A few empirical studies have provided measures of price responsiveness for individual firms and at an aggregate level, but typically there has been too little information to identify which customer-specific factors most influence price responsiveness (Zarnikau, 1990;Herriges, et al, 1993;Patrick and Wolak, 2001;Schwarz, et al, 2002;Boisvert, et al, 2004;Charles River Associates, 2005;Taylor, et al, 2005).…”

A Survey of Utility Experience with Real Time Pricing

“…6 Econometric studies of customers exposed to RTP have been conducted for programs offered by Niagara Mohawk Power Company (Herriges et al 1993 andGoldman et al 2004), Midlands Electricity in the U.K. (King andShatrawka 1994, Patrick andWolak 1997), Georgia Power (Braithwait and O'Sheasy 2000), Central and Southwest Services , and Duke Power (Schwarz et al 2000). A summary of results from many of these studies is provided in Christensen Associates (2000).…”

Why Did Electricity Prices Fall in England and Wales?

“…Withdrawing capacity in the day-ahead market also had the effect of driving up LOLP, and as Bunn & Larsen (1992) show, since LOLP is an extremely convex function strategically withdrawing capacity to increase Capacity Payments would substantially increase the revenues earned by generators. Patrick & Wolak (1997) note that a more high powered and difficult to detect strategy than just bidding high prices to set a high SMP would be to bid each plant at close to marginal cost and then declare capacity available in different periods throughout the day.…”