Abstract
Background: To transition our energy system toward sustainable production and consumption, it is important to successfully engage consumers to become active
participants in this process. One form this can take is manual demand response, where end users respond to fuctuations in energy production and help balance the grid through adjustment of their consumption. This paper presents a trial of
such a system that took place with tenants in subsidized housing in Catalonia, Spain. The aim of the trial was to motivate the load shifting behavior of the participants by forecasting expected consumption curves and tailoring suggestions for optimized behavior. The forecasts and suggestions were based on the users’ past consumption patterns and the hourly day-ahead electricity prices. This information was made available to the users on a web-based platform, and participants were actively informed with text messages sent to their mobile phones in case of attractive saving potentials for the following day. The trial was carried out in 2 phases from November 2019 to May 2020 (Phase 1) and from August to October 2020 (Phase 2). Data were collected on interaction with the platform, the perceived user experience of the platform and text messages, and the perceived energy saving success.
Results: Our results showed that there is a general interest of the participants in the concept, but that there are also important barriers to integrating load shifting behavior into everyday life. The biggest barriers here are limitations in
the fexibility potential of households and limited perceived benefts. Feedback from our participants also suggests high acceptance and relevance of more automated demand-side management (DSM) concepts.
Conclusions: Based on this, we recommend paying special attention to the accommodation of varying fexibility potential in manual demand response (DR) programs, ensuring that communicated benefts are sufciently attractive to motivate behavior change, and consideration of a phase of manual DR as an entry point to automated DSM.
participants in this process. One form this can take is manual demand response, where end users respond to fuctuations in energy production and help balance the grid through adjustment of their consumption. This paper presents a trial of
such a system that took place with tenants in subsidized housing in Catalonia, Spain. The aim of the trial was to motivate the load shifting behavior of the participants by forecasting expected consumption curves and tailoring suggestions for optimized behavior. The forecasts and suggestions were based on the users’ past consumption patterns and the hourly day-ahead electricity prices. This information was made available to the users on a web-based platform, and participants were actively informed with text messages sent to their mobile phones in case of attractive saving potentials for the following day. The trial was carried out in 2 phases from November 2019 to May 2020 (Phase 1) and from August to October 2020 (Phase 2). Data were collected on interaction with the platform, the perceived user experience of the platform and text messages, and the perceived energy saving success.
Results: Our results showed that there is a general interest of the participants in the concept, but that there are also important barriers to integrating load shifting behavior into everyday life. The biggest barriers here are limitations in
the fexibility potential of households and limited perceived benefts. Feedback from our participants also suggests high acceptance and relevance of more automated demand-side management (DSM) concepts.
Conclusions: Based on this, we recommend paying special attention to the accommodation of varying fexibility potential in manual demand response (DR) programs, ensuring that communicated benefts are sufciently attractive to motivate behavior change, and consideration of a phase of manual DR as an entry point to automated DSM.
Original language | English |
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Article number | 15 |
Number of pages | 14 |
Journal | Energy, Sustainability and Society |
Volume | 13 |
DOIs | |
Publication status | Published - 25 May 2023 |
Research Field
- Former Research Field - Capturing Experience
Keywords
- Energy feedback
- demand response
- user experience
- Energy information interfaces