Quantifying the Impact of Override Behavior on a Summer Demand Response Program
Topics:
Keywords: air conditioning, demand response, direct load control, reliability, effective load carrying capability
Abstract Type: Paper Abstract
Authors:
Pamela Jordan Wildstein, University of Michigan
Michael T. Craig, University of Michigan
Parth Vaishnav, University of Michigan
,
,
,
,
,
,
,
Abstract
Demand response (DR) programs are an important tool for maintaining grid reliability. Summer residential air condition (AC) direct load control (DLC) is a common DR program in which consumers cede control of their thermostat to the DR provider for a small number of events to reduce AC load. DLC programs often allow participants to override DR provider control. Existing research has not used empirical data to quantify the impact of override behavior on the reliability contribution of a DLC program, so likely overestimates the reliability value of DLC programs. We fill this gap by applying household indoor temperature, AC electricity usage, and system reliability models to observed DLC participation data for 403 ecobee thermostats in Southern California Edison’s 2019 Smart Energy Program. We find that accounting for overrides reduces the reliability value by 10%. Overrides led to a 50% reduction in cooling load savings, with override impacts increasing with DLC event duration. After 160 minutes of a DLC event, overrides actually lead to an increase in load relative to a counterfactual where no thermostats were enrolled in the program. Our results indicate that planners should account for override behavior when evaluating the reliability contribution of DLC programs. DLC events yield smaller reductions the longer they last and may even increase loads if they last for several hours. Scaling up our insights for our 403 households to the CA single-family housing stock suggests that overrides reduce the reliability value of the program by 25%.
Quantifying the Impact of Override Behavior on a Summer Demand Response Program
Category
Paper Abstract