Residential demand-side flexibility in energy communities: a combination of optimization and agent modeling approaches

Abstract

Energy communities are gaining momentum as they may impact demand and reshape the design of future energy systems. This paper exploits the contribution that residential demand-side flexibility can provide to an energy community by combining multi-agent systems (MAS) modeling and genetic algorithms (GA) to minimize both electricity costs and end-users' dissatisfaction. The overall community self-sufficiency in different generation scenarios is quantified by assessing how much energy demand can be locally supplied. The results reveal that important economic benefits can be obtained through the management of local energy resources, confirming that community members benefit of being involved in a communal environment.