1. A Method for Noninvasive Remote Monitoring of Energy Meter Error Using Power Consumption Profile
- Author
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Stefano Rinaldi, Zilvinas Nakutis, Pranas Kuzas, and Robertas Lukocius
- Subjects
Electrical load ,Computer science ,business.industry ,020208 electrical & electronic engineering ,Real-time computing ,02 engineering and technology ,AC power ,Power (physics) ,Electricity meter ,0202 electrical engineering, electronic engineering, information engineering ,Benchmark (computing) ,Distribution grid ,Electricity ,Electrical and Electronic Engineering ,business ,Instrumentation - Abstract
In this article, a noninvasive remote monitoring method of error of electricity energy meter (EM) is introduced and its achievable precision is investigated. The aim of the method is to determine remotely the smart EM active power relative measurement error using the reference EM connected at the input of a low-voltage distribution grid segment. The meter error estimation is carried out despite other customers’ electrical load changes observable by the reference meter and power fluctuations in the distribution network. The method is based on the real-time analysis of natural customer power consumption profiles without any additional load injection for error-monitoring needs. A power step in the customer power consumption profile is detected by the meter under test and then the step magnitude is delivered for the comparison with the power step magnitude estimated synchronously by the reference meter. The analysis of the method error is conducted by applying simulation of the benchmark distribution grid which includes 26 EMs and utilizing the open data power consumption profiles. It is shown that after two to three days of averaging (including approximately 170 power steps) of the meter error estimates, it becomes possible to achieve an uncertainty of meter error estimation approximately 0.63%. The feasibility of the method implementation scenarios with the state-of-the-art EM data collection protocols in advanced measurement infrastructure (AMI) by means of occupancy index modeling is performed. more...
- Published
- 2020
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