Managing human involvement in an energy community: Application to a subway station

Abstract

Energy communities become increasingly diverse, as sharing mechanisms and artificial intelligence become an important component of the cooperation between people and energy systems. This cooperation can play an important role at municipality level, where transportation systems that consume huge quantities of energy (i.e. subway networks) could become more efficient and sustainable, with the active involvement of people. In this context, we propose a method to manage the involvement of people in the cooperation mechanism established between an energy community and a subway station. The method relies on a multi-objective recommendation strategy that provides the members the optimal times to commute in order to provide a positive environmental and economical impact at municipality level, while also considering human dissatisfaction. The strategy is simulated in a multi-agent model, where agents represent commuting passengers. Results show that important economical and environmental performances may still be obtained when both the system performance and human dissatisfaction are minimised.