Theory of Run-Length Domain Modal Decomposition for Assessing Dynamic Errors in Electricity Meter

In scenarios involving photovoltaic power generation and electrical dynamic loads, complex electricity metering signals often exhibit strong randomness and rapid fluctuations. These characteristics frequently lead to substantial errors in electricity metering, thereby affecting fair and equitable energy transactions. This paper presents a novel modal decomposition theory in the run-length domain. Such a theory is developed to map signals from the amplitude domain to run sequences in the run-length domain. Subsequently, it decomposes signals into a quasi-steady, slowly varying mode, and another dynamic, rapidly fluctuating mode, facilitating the extraction of sensitive characteristics over prolonged durations. Furthermore, the paper proposes characteristics representation method for complex electricity metering signals by constructing parameters and characteristic functions in the run-length domain. Additionally, the paper specifically extracts sensitive characteristics for photovoltaic complex electricity metering signals using the modal decomposition theory in the run-length domain. Finally, experimental validation is conducted to elucidate the impact of these sensitive characteristics on electricity meter errors with the maximum dynamic error observed at −15.53%.