Unlocking Demand-Side Flexibility for Reliable Energy Systems: The Impact of Information Support on Household Search for Load Shifting Under Dynamic Pricing

Abstract

To improve the reliability of energy system operations, utilities are increasingly addressing ways to promote the active and timely deployment of demand-side resources. Although previous literature has confirmed that dynamic pricing is effective for managing electricity peak demand, it presents complexity challenges attempting to modify households’ consumption decisions. This study improves our understanding of households’ decision-making processes and limitations, suggesting the possible role that information about behavioral alternatives and payoffs, decision-relevant information, can play in unlocking demand-side flexibility. We draw on the NK model, perform stylized simulations to propose a micro-level foundation for households’ adaptive search and role of decision-relevant information, and conduct a randomized field experiment to put these insights into practice under a dynamic tariff setting. While the households indeed curtail peak demand, those received such information exhibit a three standard-deviation greater demand response without reducing overall daily consumption. Confirming our simulation results, the individual households’ demand response also differs by their pre-experimental consumption patterns, with the effect of the informational support diminishing over time. Utility planners are encouraged to provide decision-relevant information not only to reduce peak demand but also to enhance public acceptance of dynamic pricing by promoting load-shifting that alleviates discomfort from reduced electricity consumption.

Keywords: Energy-Related Operations; Randomized Field Experiment; NK Model; Simulation; Econometric Analysis