The transition of a conventional energy system to a sustainable one requires the availability of flexible loads on the consumption side. Coupling several individual residential consumers can provide a high degree of flexibility, which can help the energy system during times of need. This paper aims to analyze the potential enrollment of Finnish residential consumers in demand response by using an agent-based model. The motivators determining consumer enrollment are personal satisfaction, the neighborhood effect, and the social effect. In this paper, the geospatial dataset of Finland including the EV registrations are utilized and simulated for the year 2019. A sensitivity analysis is performed to analyze the effect of varying parameters in the simulation. The results highlight the high enrollment rates during the beginning of the year and lower enrollment rates during the summer months.

Residential Demand Response Enrollment Scenarios: A Geospatial Case Study of Finland

Sridhar, Araavind;Ruiz, Fredy;
2025-01-01

Abstract

The transition of a conventional energy system to a sustainable one requires the availability of flexible loads on the consumption side. Coupling several individual residential consumers can provide a high degree of flexibility, which can help the energy system during times of need. This paper aims to analyze the potential enrollment of Finnish residential consumers in demand response by using an agent-based model. The motivators determining consumer enrollment are personal satisfaction, the neighborhood effect, and the social effect. In this paper, the geospatial dataset of Finland including the EV registrations are utilized and simulated for the year 2019. A sensitivity analysis is performed to analyze the effect of varying parameters in the simulation. The results highlight the high enrollment rates during the beginning of the year and lower enrollment rates during the summer months.
2025
International Conference on the European Energy Market, EEM
Agent-based modeling
Decision-making
Demand response
geospatial analysis
Residential consumers
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1308447
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