The role of social learning on consumers’ willingness to engage in demand-side management: An agent-based modelling approach

Smart Energy(2024)

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摘要
Achieving a sustainable energy future requires a clean, affordable energy supply and active consumer engagement in the energy market. This study proposes to evaluate and simulate energy consumers' willingness to participate in demand-side management programs using an agent-based modelling approach to address the social learning effect as a key factor influencing energy consumer behaviour. The proposed agent-based model simulates households' electricity consumer interactions examining how the willingness to shift electricity usage is encouraged through the social environment, while accounting for the diversity among consumers. Data from a survey conducted in Portugal, including questions about the influence of recommendations from friends or family members on individuals' willingness to engage in demand response activities, are used to test the proposed simulation. The findings reveal that social learning significantly impacts demand response acceptance, yet the extent of this influence varies depending on the socio-economic characteristics of households’ electricity consumers. The study confirms agent-based model as an effective approach for capturing social dynamics and supporting electricity market decision making, providing valuable insights for devising consumers engagement strategies.
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关键词
Demand response,Social learning,NetLogo,Consumer behaviour,Simulation
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