The impacts of energy community members’ willingness to adapt their energy behavior: economic, environmental and social perspectives

This study explores how different levels of willingness among residential energy community members to adjust their consumption habits affect the community’s overall performance. A model of a Renewable Energy Community is presented, which incorporates strategies for shifting the use of household appliances in time, with the goal of increasing self-consumption and reducing dependencies on the electricity from national grid. Households are grouped into five behavioral categories, ranging from fully cooperative to entirely inflexible, depending on their readiness to alter appliance usage schedules. A Mixed Integer Linear Programming approach is used to optimize energy flow within the REC while respecting user preferences. To evaluate the outcomes, a set of performance indicators (including energy self-consumption, self-sufficiency, cost savings, carbon emissions, and user discomfort) is analyzed across four distinct behavior-based scenarios. A Monte Carlo simulation framework is applied to capture behavioral variability. Findings indicate that greater user engagement leads to improved economic and environmental outcomes, as well as better alignment with local renewable generation, though it comes with increased scheduling discomfort for participants.