Improving Energy Consumption Coordination in Renewable Energy Communities through Nudging
Résumé
We use nudging to increase the renewable energy consumption of an energy community, extending previous work focusing on individual households. We identify periods with available excess production through load forecasting. We introduce coordinators, which selectively notify the members of the community about these periods, by thriving to match forecasted excess with members consumption flexibility. The aim is to maximise the community self-consumption rate. We evaluate the efficiency of our pipelines on numerical simulations using semireal data, based on public consumption datasets. Results show that our coordinators are superior to the naive strategy, notifying all members about all green periods. Second, they prove efficient with respect to the so called OMEGAlpes benchmark (a reference approach using a Mixed Integer Linear Programming Solver and knowing all the information for making an appropriate use of the flexibility of the community members). Third, by refining our coordinators based on additional information about the members consumption, we show we can further improve the self-consumption rate. Finally, we discuss the implications of our results for real-world deployment.
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