Value-Based Data Governance and Security Protection for Virtual Power Plants Aggregated by Demand-Side Flexible Loads

Virtual power plants (VPPs) aggregated by demand-side flexible loads have become a key mechanism for balancing supply and demand in power systems. However, compared with conventional power plants, VPPs generate vast and heterogeneous datasets that are challenging to manage and protect effectively. Existing solutions often fail to unlock the full value of these data while imposing excessive security costs. This paper proposes a value-based data governance and security protection framework tailored for VPPs aggregated by demand-side flexible loads. Within this framework, a real-time data value assessment model is developed to dynamically assess the value of demand-side flexible load data. Furthermore, a fine-grained data management and protection strategy is introduced to enable differentiated governance and security measures. These measures are applied across different stages of the data life cycle according to the assessed data value levels. Numerical results demonstrate that the proposed framework enhances both data protection and operational performance while reducing security costs. Moreover, it promotes data circulation and value creation, and supports the sustainable and intelligent transformation of modern power systems.