Low-Carbon Community Energy Management Incorporating Data-Driven User Segmentation

Residential energy management is essential for developing clean and sustainable smart grids. Energy cooperation strategies should be developed to reduce uncertainties in distributed energy resources (DERs) and encourage citizens to live sustainably. Community energy storage (CES) received more and more attention in recent years to improve the reliability and efficiency of renewable energy consumption. To achieve cooperation between users in a community, a coordinator-owned CES is introduced to maximise the economic and environmental benefits of the whole community. The energy cost, carbon cost, and dissatisfaction cost caused by shifting customers’ demand are jointly considered in the proposed model. Specifically, a data-driven user segmentation is first proposed to cluster users in different groups according to their historical electricity consumption habits. Customers with irregular and large load profiles will be prioritised for demand shifting to minimise the inconvenience caused by demand response (DR) in the community. Then, a coordinator is designed to coordinate individual customers’ resources and goals to maximise the whole community’s benefits through cooperation between different customers via CES. Case studies with real-world datasets demonstrate the effectiveness and superiority of the proposed model.