ArticleScientific reports2026
An error measurement method for electricity meters based on dynamic test signal modeling with random measurements.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Addressing the challenge of evaluating electricity meter measurement errors caused by nonlinear high-power dynamic loads in smart grids, as well as the issues of long cycle periods and high time consumption associated with traditional m-sequence test signals, this paper proposes an indirect error measurement method based on dynamic test signal modeling using random measurements. Firstly, compressive sensing theory is introduced to construct a structured Orthogonal Pseudo-Random Measurement (OPRM) matrix, generating a dynamic test signal that balances randomness and compactness. This achieves a significant dimensionality reduction of the test sequence while accurately preserving the stochastic fluctuation characteristics of actual dynamic loads. Secondly, a "Run-length Likelihood Function" for dynamic electrical energy is innovatively defined. Leveraging a high-precision synchronous gating control mechanism to eliminate time-domain random truncation effects, a rigorous mapping model is established for tracing dynamic reference energy back to the steady-state reference value. Experimental verification demonstrates that the OPRM model's capability to reflect dynamic errors is highly consistent with that of the traditional m-sequence. However, the single-test duration is drastically reduced from 197 to 49 min, achieving a 75% reduction in time cost. Concurrently, the system's test repeatability is as low as 0.0003%, and the expanded uncertainty is strictly constrained at 0.1442% (inclusion factor k = 2), pushing the comprehensive measurement accuracy of dynamic metering to a new high of better than 0.15%. This work provides core technical support for the agile and high-precision calibration of massive smart electricity meters.
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