Characterization of Measurements for Smart Grids

Abstract

The management of smart grids requires advanced and complex measuring systems because of the continuous development of electricity production, transmission, and distribution systems. These measurement systems, because of their complexity, are only based on analog-to-digital conversion. To characterise the quality of such measurements, it is necessary to evaluate their measurement uncertainty. With this aim, this paper presents an approach based on the Monte Carlo method. By using a specially designed simulator and inputting the characteristics of the employed transducers and analog-to-digital converters, the method allows not only estimating uncertainties but also getting the probability density functions associated with measurements. The proposed method can easily estimate the impact of different sources of error on the measurement uncertainty, allowing for the proper design of the measurement system and the proper choice of transducers and analog-to-digital converters.