A performance-based incentive sharing mechanism for communities of residential end users leveraging an ontology-driven approach

Abstract

Energy sharing, whether physical or virtual, is crucial for optimizing the use of locally generated renewable energy within communities of residential end users, including Renewable Energy Communities (RECs) and Collective Self-Consumption (CSC) groups. By sharing energy, participants can increase self-consumption of renewables while reducing reliance on the grid. To encourage participation, many frameworks provide economic incentives for shared energy, offering financial benefits to those who contribute to community energy goals. However, ensuring a fair allocation of both shared energy and its associated incentives remains a challenge.

This study introduces a novel performance-based incentive-sharing mechanism that dynamically adjusts the allocation of economic benefits based on user ability to shift consumption in response to surplus availability. Different from traditional approaches, the mechanism integrates a dynamic baseline selection process with an ontology-driven metadata model, using SAREF and its domain-specific extensions to ensure interoperability and automation. This semantic framework enables scalable deployment across heterogeneous community configurations while reducing setup complexity.

The process was tested over a seven-month period within a collective self-consumption group of 13 residential users who virtually share energy from a centralized PV system. Results show that users who adjusted their consumption to match surplus availability increased their daily incentives by up to 40% compared to a standard sharing mechanism, while those who performed below expectations experienced a corresponding decrease. These findings highlight the potential of structured data-driven approaches, supported by ontologies, to improve decision-making in community energy management.