Rocky Mountain Institute’s four scenarios for the future U.S. electricity system ( detailed here ) all have different penetrations and costs of demand response programs. Demand response, along with energy storage, diversification of renewable resources, and updated grid forecasting and operations, can play a huge role in facilitating the implementation of high penetrations of variable renewables.
In a fully automated demand response program, participating customers would indicate what amount of their peak demand is flexible enough to be sometimes shifted to another time of day (for example clothes washing) or eliminated entirely (like the clothes dryer). As needed, the grid operator could automatically communicate with the customer’s energy monitoring system to turn off or shift these loads, thereby reducing peak system demand. In a grid with a high penetration of variable renewable resources, when renewables are unable to meet demand at peak hours, automated demand response could potentially shave that demand by 20% or more, enabling better matching of supply and demand. Shifted loads can be “dispatched” later at hours when total renewable supply exceeds total demand, the same way that the grid operator currently dispatches flexible power plants.
To determine the maximum percentage of peak load that could be shaved in each scenario, RMI analyzed the potential for each NERC region individually (this illustrative example is based on NERC region 5). Demand response potential is highly dependent on regional characteristics: weather, consumer behavior, and urban vs. suburban.
Each of the four Reinventing Fire cases illustrates the cost to the electricity system of demand response. For example, Under the Transform case the utility or system operator would pay approximately $45/kW-yr for a 10% reduction of peak load compared to approximately $55/kW-yr for a 15% reduction of peak load. These levels of participation and costs are based on those described in the Federal Energy Regulatory Commission’s 2009 report on demand response potential.
RMI analysis using data from:
The Brattle Group, Freeman, Sullivan & Co., and Global Energy Partners, LLC. 2009. A National Assessment of Demand Response Potential. Federal Energy Regulatory Commission, June.