The Impact of Economic and Non-Economic Incentives to Induce Residential Demand Response—Findings from a Living Lab Experiment

Abstract

This study assesses the impact of economic and non-economic incentives to induce demand response in private households. The experiment was realized by a three-months residential phase in which two tenants lived in the Energy Smart Home Lab, an experimental lab with the equipment of a modern smart home. The tenants received calls to action (CtAs) on a regular basis, incentivized economically or by moral nudges with a social or environmental background. A mixed-methods approach, consisting of smart meter data analysis, a value scale assessment, surveys and interviews, assessed the tenants’ reactions on their energy consumption behavior towards the CtAs. The smart meter data shows that the tenants performed the majority of CtAs, revealing no significant difference between economic or non-economic incentives. Results from the value scale, the interviews and the surveys indicate that this behavior might be due to the tenants’ high tendency towards biospheric and altruistic values and a high self-efficacy. Furthermore, the consequences of the COVID-19 pandemic caused a 100% home-office situation, suggesting a higher flexibility of the tenants. Although the results are not representative and need further experiments to be confirmed, the incentives show a promising potential to evoke residential demand response.

Holistic Evaluation of Demand Response Events in Real Pilot Sites: From Baseline Calculation to Evaluation of Key Performance Indicators

“…In this subsection, we present the results when applying the univariate regression model to the Spanish pilot site. The obtained formula for the predicted energy consumption baseline is the following: Energy(t) = 0.619 × Energy(t − 1) + 0.0759 (6) As for the Cypriot pilot site, Energy(t) represents the predicted energy consumption for one particular interval, whereas Energy(t − 1) represents the energy consumed for the particular interval the previous day. In this case, we have 30 min intervals for the available historical data.…”

“…However, it is fundamental to have residential demand response in order to make the most out of the available flexibility and also transform end users into active players of the smart grid. There have been several works conducted in this regard: in [6], a study has been made in order to analyse how people react to economic or noneconomic incentives for residential demand response; and in [7], a novel algorithm is presented that schedules the functionality of house appliances in order to alleviate power peaks and minimize costs for end users.…”

A Behavioral Science Perspective on Consumers’ Engagement With Demand Response Programs

“…For example, modeling studies often assume a certain level of participation in DR programs or examine the load shifting capability of certain household appliances, but it is uncertain whether residential consumers would take the behavioral steps to harness this potential (Schuitema et al, 2017). Recent studies have aimed to close this gap by examining certain behavioral aspects underlying DR, such as people's participation in dynamic tariffs (e.g., Nicolson et al, 2018;Parrish et al, 2020;Scharnhorst et al, 2021). However, effective DR requires consumers to engage consistently in a set of different behaviors beyond mere participation.…”