scholarly journals Geometric system analysis of ILMD-based LID measurement systems using Monte-Carlo simulation

2022 ◽  
Vol 2149 (1) ◽  
pp. 012015
Author(s):  
M Katona ◽  
K Trampert ◽  
C Schwanengel ◽  
U Krüger ◽  
C Neumann
Keyword(s):  
Monte Carlo ◽  
Intensity Distribution ◽  
System Analysis ◽  
Uncertainty Budget ◽  
Luminous Intensity ◽  
Light Sources ◽  
Measuring Device ◽  
Measurement Systems ◽  
Kinematic Transformations ◽  
Set Up

Abstract Imaging Luminance Measuring Device (ILMD) based luminous intensity distribution measurement systems are an established method for measuring the luminous intensity distribution (LID) of light sources in the far field. The advantage of this system is the high-resolution acquisition of a large angular range with one image. For the uncertainty budget, the mathematical description of the system can be divided into photometric and geometric contributions. In the following, we will present a Monte-Carlo approach to analyse the geometric contributions which are the uncertainty of measurement direction and measurement distance. Therefore, we set up a geometric system description based on kinematic transformations that describes the connection between detector and light source position. To consider all relevant input quantities we simulate the adjustment and measurement process. Finally, an analysis of the geometric input parameters is shown.

scholarly journals Calibration of On-Board Energy Measurement Systems Installed in Locomotives for AC Distorted Current and High Voltage Waveforms and Determination of Its Uncertainty Budget

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7967
Author(s):  
Abderrahim Khamlichi ◽  
Fernando Garnacho ◽  
Pascual Simon ◽  
Jorge Rovira ◽  
Angel Ramirez
Keyword(s):  
High Voltage ◽  
Uncertainty Budget ◽  
Power Source ◽  
Active Power ◽  
Energy Measurement ◽  
Reference Measuring ◽  
Measurement Systems ◽  
Council Directive ◽  
Rail Systems ◽  
Set Up

Periodic calibrations of Energy Measurement Systems (EMS) installed in locomotives must be carried out to demonstrate the required accuracy established in the EN 50463-2 standard according to European Parliament and Council Directive 2008/57/EC on the interoperability of rail systems within the Community. As a result of the work performed in the “MyRailS” EURAMET project an AC calibration facility was developed consisting of a fictive power source was developed. This fictive power source can generate distorted sinusoidal voltages up to 25 kV-50 Hz and 15 kV-16.7 Hz as well as distorted sinusoidal currents up to 500 A with harmonic content up to 5 kHz or phase-fired current waveform stated in EN50463-2 standard. These waveforms are representative of those that appear during periods of acceleration and breaking of the train. Reference measuring systems have been designed and built consisting of high voltage and high current transducers adapted to multimeters, which function as digital recorders to acquire synchronized voltage and current signals. An approved procedure has been developed and an in-depth uncertainty analysis has been performed to achieve a set of uncertainty formulas considering the influence parameters. Different influence parameters have been analyzed to evaluate uncertainty contributions for each quantity to be measured: rms voltage, rms current, active power, apparent power and non-active power of distorted voltage and current waveforms. The resulting calculated global expanded uncertainty for the developed Energy Measuring Function calibration set up has been better than 0.5% for distorted waveforms. This paper is focused on presenting the complete set of expressions and formulas developed for the different influence parameters, necessary for uncertainty budget calculation of an Energy Measuring Function calibration.

Markov Jump Linear System Analysis of a Microgrid Operating in Islanded and Grid Tied Modes

2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball
Keyword(s):  
Monte Carlo ◽  
Power Systems ◽  
Power System ◽  
System Analysis ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Markov Jump ◽  
Numerical Application ◽  
Conditional Moments ◽  
Markov Jump Linear Systems

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>

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