DT-AOF: 50,000-Step Power Line Simulation Data for Digital Twin Validation

A 50,000-step cyber-physical simulation dataset for overhead transmission lines, created by Song and published in 2026. It includes baseline physical parameters, dynamic load fluctuations, environmental disturbances, and results from algorithm comparisons. The data supports research on monitoring algorithms and digital twin applications under stochastic conditions.

Use Cases

• Benchmarking adaptive optimization frameworks based on performance metrics like Energy Consumption and MSE Estimation Error.
• Validating physics-informed models against purely data-driven approaches using ablation study data.
• Simulating power line behavior under realistic stochastic conditions like dynamic load and weather changes.
• Comparing algorithm robustness using the provided results from five distinct methodological approaches.

Strengths

• Contains 50,000 continuous time steps, providing a substantial temporal sequence for analysis.
• Includes results from a structured ablation study, allowing for component-level validation.
• Data is organized into three clear categories (RAW_INPUTS, EXPERIMENTAL_RESULTS, ABLATION_STUDY) across 8 CSV files.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for individual files is unknown, which may limit suitability assessment.
• Data is simulated, not collected from real-world physical infrastructure.

Provenance

Source

figshare, supporting a research paper published in Scientific Reports.

Collection Method

Generated from a high-fidelity cyber-physical simulation environment.

Time Range

Covers 50,000 simulated time steps.

Freshness

Last updated 2026-04-12 05:05:42; freshness should be verified.