Testing and validation of an algorithm for configuring distribution grid sensor networks

The control of Smart Grids depends on a reliable set of measurement information such that distributed generation and demand can be effectively managed. The cost of procuring and installing sensors at multiple nodes in the grid is prohibitive and choosing the optimum strategy with regards to sensor location, accuracy, number and type is very important. This report describes the testing of a sensor placement algorithm developed to determine measurement strategies for distribution grids. This testing was performed on a laboratory microgrid at the University of Strathclyde. The ability of the algorithm to choose the optimal subset of measurements was tested by comparing the estimated power flow with the measured power flow of a fully instrumented grid. The chosen subset is found to have the close to the lowest overall error and all estimates agree with the rejected measurements within the calculated uncertainties

Evaluating the robustness of an active network management function in an operational environment

This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance

Validation of the sensitivity analysis method of coordinate measurement uncertainty evaluation

The paper presents the results of the tests carried out to validate a new method for evaluating the uncertainty of coordinate measurements categorised as the Sensitivity Analysis (SA). This method concerns measuring dimensions and geometrical deviations. Measurement uncertainty is evaluated on the basis of information given in the Maximum Permissible Error (MPE) formula for a Coordinate Measuring Machine (CMM). Measurement models express the measured characteristics as a function of differences of coordinates of a small number of appropriately selected points of the workpiece. If reverification test results for the CMM used are available, then the estimated uncertainty takes into account the actual accuracy of the CMM. General formulae are given to calculate the uncertainty of measurement of a circle diameter and coaxiality. The relevant experiment is based on ISO 15530-3 recommendations. A calibrated cylindrical square was used for validation. 17 circles’ diameters and 84 different combinations of datum length and distance of the toleranced element from the datum for measuring coaxiality were adopted as validated characteristics. The validation results are presented in tables and graphs and the chi-square test for equality of variances was used to confirm that the method is correct. The validation results are positive

Evaluation of automated flexible gauge performance using experimental designs

An essential part of assessing whether a measurement or gauging system meets its intended purpose is to estimate the measurement uncertainties. This paper employs the design of experiments (DOE) approach to implement a practical analysis of measurement uncertainty of Renishaw Equator automated flexible gauge. The factors of interest are measurement strategy, part location, and environmental effects. The experimental results show the ability of the versatile gauge to effectively meet its measurement capability in both discrete-point probing and scanning measuring modes within its whole measuring volume and, in particular, at high scanning speeds and under workshop conditions

Modelling uncertainty associated with comparative coordinate measurement through analysis of variance techniques

Over the last few years, various techniques and metrological instruments have been proposed to achieve accurate process control on the shop floor at low cost. An efficient solution that has been recently adopted for this complex task is to perform coordinate measurement in comparator mode in order to eliminate the influence of systematic effects associated with the measurement system. In this way, more challenging parts can be inspected in the shop floor environment and higher quality products can be produced while also enabling feedback to the production loop. This paper is concerned with the development of a statistical model for uncertainty associated with comparative coordinate measurement through analysis of variance (ANOVA) techniques. It employs the Renishaw Equator comparative gauging system and a production part with thirteen circular features of three different diameters. An experimental design is applied to investigate the influence of two key factors and their interaction on the comparator measurement uncertainty. The factors of interest are the scanning speed and the sampling point density. In particular, three different scanning speeds and two different sampling point densities are considered. The measurands of interest are the circularity of each circular feature. The present experimental design is meant to be representative of the actual working conditions in which the automated flexible gauge is used. The Equator has been designed for high speed comparative gauging on the shop floor with possibly wide temperature variation. Therefore, two replicates are used at different temperature conditions to decouple the influence of environmental effects and thus drawing more refined conclusions on the statistical significance

Developments in automated flexible gauging and the uncertainty associated with comparative coordinate measurement

Traditional manufacturing uses coordinate measuring machines (CMMs) or component-specific gauging for in-process and post-process inspection. In assessing the fitness for purpose of these measuring systems, it is necessary to evaluate the uncertainty associated with CMM measurement. However, this is not straightforward since the measurement results are subject to a large range of factors including systematic and environmental effects that are difficult to quantify. In addition, machine tool errors and thermal effects of the machine and component can have a significant impact on the comparison between on-machine measurement, in-process measurement and post-process inspection. Coordinate measurements can also be made in a gauging/comparator mode in which measurements of a work piece are compared with those of a calibrated master artefact, and many of the difficulties associated with evaluating the measurement uncertainties are avoided since many of the systematic effects cancel out. Therefore, the use of flexible gauging either as part of an automated or manually-served workflow is particularly beneficial

Sensitivity analysis of sensor networks for distribution grids

This speech explores the sensitivity analysis of sensor networks for distribution grid

Determination of uncertainty of coordinate measurements on the basis of the formula for EL,MPE

according to ISO/TS 15530-1, developed at University of Bielsko-Biała, is presented. Measurement uncertainty is estimated on the basis of information contained in the formula for the maximum permissible error (EL,MPE) of the applied coordinate measuring system (CMS) and on the basis of its acceptance or reverification test results. Measurement models are of the nature of close mathematical dependencies expressing the measured characteristic in the form of a distance which is a function of coordinates differences of a low number of essential points, properly selected on the workpiece. Measurement models for dimensions and various geometrical deviations were developed. Thanks to the applied vector notation the models are in the form of cross and dot products and they are easily programmable in software such as Matlab, Maple or Python. Detailed examples of the uncertainty analysis for two characteristics (position deviations of the axes of the holes in relation to the datum system) of a car steering knuckle are provided

The quantum metrology triangle and the re-definition of the SI ampere and kilogram; Analysis of a reduced set of observational equations

We have developed a set of seven observational equations that include all of the physics necessary to relate the most important of the fundamental constants to the definitions of the SI kilogram and ampere. We have used these to determine the influence of alternative definitions being considered for the SI kilogram and ampere on the uncertainty of three of the fundamental constants (h, e and mu). We have also reviewed the experimental evidence for the exactness of the quantum metrology triangle resulting from experiments combining the quantum Hall effect, the Josephson effects and single-electron tunnelling.Comment: 16 pages, 3 figures & 5 table