Demand Response Analysis

NREL analysts evaluate the potential value of demand response to future bulk power systems. Demand response can be interpreted broadly as any modification of end-use electricity load operation for the purpose of providing grid services.

NREL uses production cost and capacity expansion modeling to capture capacity, energy, and ancillary service value achieved through demand response, via a combination of electricity load reductions at peak times (capacity, contingency reserves, peak-load energy value), energy shifting, and load-following or regulation reserves.

Featured Project

Demand Response in Florida

In The Value of Demand Response in Florida, NREL examined future Florida power systems under a range of photovoltaic (PV) penetrations and flexibility options. In addition to demand response, the project team analyzed to what extent more flexible operations and battery energy storage might increase the economic carrying capacity of solar PV. Flexibility becomes a potentially important component of preserving PV value at penetrations around 15% of annual energy.

Chart showing annual solar PV penetration versus incremental PV value, with different scenarios of flexibility and demand response plotted. Value tends to decrease as PV penetration increases, and flexibility becomes a potentially important component of preserving PV value at penetrations around 15% of annual energy.

Based on NREL's scenario assumptions, demand response can provide flexibility similar in overall impact to 1 gigawatt of 6-hour battery energy storage spread throughout the Florida Reliability Coordinating Council (FRCC) power system, with important differences concerning which types of generation are displaced by the two resource types.

The value of demand response to the FRCC system was also analyzed more generally, in terms of production cost savings and operational impacts. Production cost savings for the high-demand-response scenario (applied in the absence of any other flexibility options) ranged from $76 million to $259 million, depending on PV penetration. Greater savings were found for higher PV penetrations, even though higher PV penetrations also depress overall production costs. As such, the percentage savings range was even wider, from 0.5% to 2.2%.

Flexibility almost uniformly reduces the number of gas generator (combined-cycle units and combustion turbines) number of starts. Additional system flexibility, including demand response, often actually increases the number of coal starts because the additional flexible resource can be the difference between being able to keep a coal plant off for the full minimum downtime.

NREL is also researching interactive effects between demand response and battery energy storage operations.

Related Publications

Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification, NREL Technical Report (2020)

Demand Response in Bangalore: Implications for Electricity System Operations, NREL Technical Report (2020)

Demand Response for Variable Renewable Energy Integration: A Proposed Approach and Its Impacts, Energy (2020)

Potential Roles for Demand Response in High-Growth Electric Systems with Increasing Shares of Renewable Generation, NREL Technical Report (2018)

Integrating Solar into Florida's Power System: Potential Roles for Flexibility, Solar Energy (2018)

Demand Response Potential from the Bulk Grid Perspective, NREL Presentation (2017)

The Value of Demand Response in Florida, Electricity Journal (2017)

Capturing the Impact of Storage and Other Flexible Technologies on Electric System Planning, NREL Technical Report (2016)

On the Inclusion of Energy: Shifting Demand Response in Production Cost Models: Methodology and a Case Study, NREL Technical Report (2015)

Demand Response and Energy Storage Integration Study, U.S. Department of Energy Technical Report (2016)

Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model, NREL Technical Report (2013)


Brady Cowiestoll

Senior Engineer – Economics and Forecasting