Research on Quality Evaluation and Optimization of Data Delivery in Modern Power Plant Security Design

To address the critical demand for quality control in data delivery for modern power plant security design, this study proposes a data delivery quality optimization system based on a multi-dimensional evaluation model. First, core delivery risk elements such as requirement deviation, format heterogeneity, and version inconsistency are identified, and a hierarchical evaluation index system incorporating three dimensions—completeness, reliability, and timeliness — is constructed. A hybrid algorithm is employed to quantify qualitative indicators, establishing an evaluation model that considers multiple quantitative parameters, including metadata standardization, parameter traceability rate, and update synchronization rate. This model effectively identifies quality shortcomings across the three dimensions, with data version traceability completeness showing significant improvement compared to traditional approaches. Based on analytical results, optimization strategies such as a digital fingerprint-based verification mechanism and dynamic weight adjustment algorithms are proposed, forming a quality enhancement path covering the entire data life-cycle from acquisition, transmission, to archiving. This research provides verifiable technical methods for digital delivery in power infrastructure.