Achieving the smart grid’s potential requires a revolution in electricity pricing. Smart metering and smart rates might yield surprising and beneficial changes in the U.S. utility industry. But...
Energy Strategy: Flat Bills, Peak Satisfaction?
Why a risk-hedging product for small customers isn’t the gamble you may think.
won’t approve it.
If that’s your reaction, you are not alone. These are what we consider the “norms” or “the box.” To think outside of this barrier, we have to define each of these norms and then challenge them.
Quashing the Misperceptions
Challenging the norms is the strategy we adopted at Georgia Power in pursuing a flat bill option for our small customers. The result was a flat bill pilot program rolled out June 1, 2000, and involving 500 residential and small business customers. The goal of the program was to understand the myths about the mysterious “flat bill.”
To begin with, we examined the potential hurdles and were surprised to discover that there were few. On the surface, the idea of a pure flat bill in the electric market is frightening, posing potential threats in terms of capacity constraints, the price premium, revenue risk and regulations. But when we challenged these norms through market research, load shape modeling and product testing, we found an exciting new pricing opportunity. Let’s examine each of these perceived threats and the realities we came to understand.
Norm 1: System Capacity Will Suffer. The primary reason flat bills are uncommon in our industry is the fear that customers will change their behavior, leading to a dramatic increase in their load demand. Although this worry is a norm, we have been unable to find quantitative research to support it.
We used a three-prong approach to challenge this belief. First, customers were surveyed to learn how they would behave on such a pure flat program. Then those results were applied to a modeling program that analyzed and projected the impact of these customers’ behavior change on their load shape. Finally, we conducted a pilot that metered the participants’ actual energy and peak consumption. This information was normalized to account for weather and compared to the previously measured behavior for these customers. The results were measured empirically using test and control groups.
Reality Check. We found that there was an increase in both energy and demand consumption. However, the impact was minimal; better yet, it occurred mostly during off-peak periods. That can be explained by the fact that most of the growth was the result of customers lowering their thermostat setting during the summer months. The effect of this action was minimal during peak hours because the electric cooling system was running full speed regardless of whether the thermostat was set at 76 degrees or lowered to 74 degrees. But during the off-peak times, when the weather had cooled, the threshold of the thermostat setting had a greater impact on the running time of the cooling system.
Though we found a minimal increase in energy consumption, we believe the program can be energy-efficient. This program is the only one for residential customers that can accurately measure participants’ change in behavior in terms of the financial impact on their annual bills. Typical volumetric pricing used by weather-sensitive residential or small business customers reveals a change in behavior from month to month, or month to the same month of the previous