Dataset: TEPCO Power Demand (Public) + JMA Weather Observations (Tokyo), Jan–Apr 2024
Protocol: Static Calibration → Out-of-Sample Evaluation → Immutable Hashed Audit Certificate
Root Cause: TAU_CAP_HIT
In operational time-series forecasting, "drift detection" is frequently implemented as a reactive heuristic where data boundaries, thresholds, and preprocessing parameters are adjusted post-hoc. This fluidity prevents independent researchers from reproducing the same conclusions, effectively rendering drift detection an operational artifact rather than a falsifiable scientific claim. The lack of computational reproducibility erodes the integrity of monitoring pipelines in safety-critical domains.
This report addresses this erosion by presenting a Certificate-based Audit protocol. Under this framework, drift determinations are encapsulated into an immutable "Audit Certificate," where data provenance, temporal splitting, threshold policies, and execution environments are strictly defined and verified via digital fingerprints (SHA256). Threshold estimation is restricted to the Calibration phase, ensuring that the Evaluation phase remains an unbiased out-of-sample test. This structural design proactively eliminates post-hoc parameter optimization (p-hacking). As an empirical validation, we present an audit of Tokyo Electric Power Company (TEPCO) demand and Japan Meteorological Agency (JMA) weather data for the first quadrimester of 2024.
The primary contribution of this work lies in the reduction of "drift determination" into a reproducible and falsifiable experimental unit, independent of operational biases.
Traditional monitoring allows splitting points between Calibration and Evaluation to be shifted ex-post, enabling the selection of timeframes that yield desired detection outcomes.
Detection thresholds are often adjusted to satisfy operational budgets (e.g., alert volume limits), thereby obscuring the true structural breakdown of the model's assumptions.
Conclusions are typically disconnected from specific data versioning, making it impossible to verify if the audit was performed on the original or manipulated datasets.
A lack of environmental hashing prevents third parties from discerning whether a discrepancy in results stems from a change in data or an unrecorded update in the execution environment.
The protocol enforces a strict separation between Calibration-only Parameterization and Evaluation-only Inference. To guarantee the immutability of the audit conclusion, the following five vectors are condensed into a unique SHA256 "Integrity Fingerprint."
Ghost Score Definition
$$SCORE = \max\left( \frac{|y - \hat{y}|}{THR_{RES}}, \frac{\Delta \text{Residuals}}{THR_{GRAD}} \right)$$Capturing both Magnitude (Level) and Structural (Shape) Residuals
Policy Separation Axiom
$$\tau_{used} = \min(\tau_{budget}, \tau_{cap})$$Condition: $\tau_{budget} > \tau_{cap} \implies \text{Regime Shift Confirmed}$
Load Demand Series: Retreived from TEPCO Power Grid "Electricity Forecast > Usage Data" portal. Monthly CSV archives (Jan–Apr 2024) were consolidated into a singular time-series (Collection Date: 2025/12/14 JST). The measurement unit is 10 MW (10,000 kW), strictly adhering to source granularity.
Meteorological Observations: Retreived from the Japan Meteorological Agency (JMA) Historical Download Portal. Station: "Tokyo". Parameters: Temperature, Sunshine duration, Relative humidity. Temporal resolution: Hourly (Collection Date: 2025/12/14 JST).
Raw data files are not redistributed to comply with terms of use and data governance. Reproducibility is maintained via SHA256 verification of locally archived files against the provided acquisition protocol.
Verdict
NG
Cap Hit Days
22
Drift Ratio (RMSE)
1.883
Unit
10 MW
| Timestamp (Start) | Timestamp (End) | Dur. (h) | Peak Score | Attribution |
|---|---|---|---|---|
| 2024-04-29 06:00 | 2024-04-29 22:00 | 17 | 2.763 | LEVEL_RESIDUAL |
| 2024-04-24 11:00 | 2024-04-26 10:00 | 48 | 2.740 | LEVEL_RESIDUAL |
| 2024-04-22 10:00 | 2024-04-22 13:00 | 4 | 2.357 | LEVEL_RESIDUAL |
| 2024-04-15 09:00 | 2024-04-17 19:00 | 59 | 2.251 | LEVEL_RESIDUAL |
To satisfy the requirements of rigorous academic scrutiny, the following robustness evaluations are designated as high-priority follow-up experiments: