Tool for Designing Dynamic Rates

The tool to calculate price elasticity of electric demand and design future dynamic pricing programs is a Microsoft Excel based application that was funded by DOE Office of Electricity Delivery and Energy Reliability (OE) and developed by Argonne National Laboratories and Energy and Environmental Resources Group, LLC (E2RG). This tool is used to calculate elasticity of substitution and own-price elasticities of electric demand using the augmented Constant Elasticity of Substitution model. Using the calculated elasticity values, the tool can further project changes in electricity loads as a function of electricity prices and temperatures as specified by utilities; conversely, the tool is capable of calculating the pricing structure necessary to achieve utility-defined objectives for peak load reduction and revenue, under a given set of temperatures.

• Provides Elasticity of Substitution and Own-price elasticity values for Critical peak pricing days and Time-of-Use pricing days separately.
• Can be used for a 2 period or a 3 period dynamic pricing program.
• Accounts for temperature by using the Cooling degree hours for each hour during the study period. (The base temperature can be changed. Default value is 72). The tool is designed for summer peaking utilities (that is utilities who desire to reduce peak loads during summer days.)
• Can be used for up to 10 groups/cohorts (using more well defined groups would give a better understanding of the different customers response to time-varying prices).
• Allows calculating new dynamic pricing program structure based on reduction in peak load, change in revenue and forecasted temperature (Variant A). Also a new dynamic pricing program structure can be calculated by providing desired fixed price differentials between the various pricing periods and the forecasted weather (Variant B).
• Forecasted weather can be entered by matching with control group/treatment group or increasing the control group.s existing temperature dataset by a fixed percentage or an absolute value for each period or by completing a new temperature dataset.

For more information, contact CEEESA.