| The European Green Deal has set ambitious short-term targets for reducing CO2 emissions and achieving climate neutrality. In communal living spaces, the associated challenges involve the exploitation of energy from renewable sources in order to reduce indirect CO2 emissions caused by grid electricity consumption, and the satisfaction of the residents, with their individual appliance-scheduling preferences that often conflict with their objective of minimizing associated billing charges. This paper tackles this multi-objective optimization problem by proposing a multi-objective evolutionary algorithm based on decomposition with decision making. The algorithm produces a set of optimal trade-offs between maximizing the satisfaction of resident appliance-scheduling preferences and minimizing their billing charges, with decision making opting for the trade-off offering minimal deviation from the use of green energy, consequently limiting the CO2 footprint. Our experimental evaluation, based on the energy consumption patterns of 10 UK households as recorded in the REFIT public dataset, demonstrates that the proposed approach clearly outperforms alternative state-of-the-art approaches. |
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