The model that was used to describe the subject of this study was based on the National Demand Response Potential Model, produced for the American Federal Energy Regulatory Commission by The Brattle Group, Freeman, Sullivan & Co. Global Energy Partners, LLC, in June 2009. The model has been adjusted to reflect the specifics of the situation that is studied in this research. The following is an overview of the American model's functions.
The National Demand Response Potential Model is a flexible tool that is useful for estimating the amount of demand response (DR) that could potentially be achieved under a variety of assumptions about installed technology, programs pursued, market acceptance of the programs, opt-in versus default dynamic pricing, and the overall cost-effectiveness of programs. The model is designed to provide a bottom-up assessment of demand response potential, taking into account state specific information on customers, load mix, existing demand response, advanced metering infrastructure deployment, air-conditioning saturation, and other relevant factors.
By constructing demand response potential scenarios by state and across various program types, the model enables comparisons across different regions of the U.S. to identify areas where there is opportunity for substantial growth and adoption of demand response and also enables the identification of programs with the most room for growth. In addition, demand response potential estimates are provided by customer segment, enabling assessments of potential within each segment.
The model is an Excel spreadsheet tool designed to provide users with significant flexibility. It contains user friendly drop-down menus that allow users to easily change between demand response potential scenarios, to import default data for each state, and to change input values on either a temporary basis for use in “what if” exercises or on a permanent basis if better data are available. In addition, the flexibility of the model allows users to define their own demand response potential scenarios. A key feature of the model is that it contains state specific information and inputs. When it was developed, the model was populated with the best publicly available data and was designed to facilitate input updates as more accurate or new information becomes available. While the model was designed to produce state level estimates, the user interface can also accommodate inputs for utilities, municipalities or other levels of aggregation.
The model incorporates state specific data on four customer segments and five types of demand response programs. Retail customers are divided into four segments based on common metering and tariff thresholds.
The model addresses five demand response program categories: