Multiple Measurement Devices Research Articles

A Novel Topology Identification Algorithm Fusing Multi-Source Measurement Data in Distribution Network

With the development of new power systems, large amounts of decentralised clean energy and flexible loads will be connected to the smart grid, making the topology of the distribution network even more complex. At the same time, the demand for efficient interaction of “source-network-load” also makes the distribution network topology change with time, which makes it more difficult to identify the distribution network topology. However, topology identification is the basic data for power system regulation and safe optimal operation. Considering the above problems and requirements, this paper investigates and proposes a novel method to identify the topology of a distribution network based on the collaboration of data from multiple measurement devices. Firstly, a method based on multi-source data time synchronization method of μPMU measurement data is proposed, and generate additional data based on linear extrapolation to expand the available data set. Then, a method of topology optimization model identification based on least square method is proposed. Finally, the proposed algorithm is simulated in an example of the IEEE 33 bus feeder system standard. The results show that the scheme is effective in identifying the topology of the distribution network and improves the accuracy compared to traditional methods.

Reachability-Based False Data Injection Attacks and Defence Mechanisms for Cyberpower System

With the push for higher efficiency and reliability, an increasing number of intelligent electronic devices (IEDs) and associated information and communication technology (ICT) are integrated into the Internet of Things (IoT)-enabled smart grid. These advanced technologies and IEDs also bring potential vulnerabilities to the intelligent cyber–physical smart grid. State estimation, as a primary step of system monitoring and situational awareness, is a potential target for attackers. A number of other smart grid applications, such as voltage stability assessment and contingency screening, utilize state estimation results as input data. False data injection (FDI) is a specific way to attack state estimation by manipulating input data. Existing research mainly focuses on the mathematical analysis of FDI attacks; however, in these methods, discussions of reachability requirements to compromise measurements considering cyberinfrastructure are limited. Reachability is defined as a measure that estimates the number of hosts to compromise for the possible FDI. Most of the existing FDI attack methods require the simultaneous manipulation on multiple measurement devices in different substations, in order to bypass the bad data detection, which may be impractical. In this paper, a new type of reachability-based FDI attack considering the cybernetwork with a practical attack is proposed and validated on two IEEE test systems. The corresponding defence mechanisms are (a) decentralized state estimation (DSE), (b) DSE with additional backup computational nodes, (c) communication network rerouting, and (d) intrusion detection system, and they were developed and presented with validation for two IEEE test systems with superior performance for an IoT-enabled intelligent smart grid system.

The Effects of Distraction Type and Difficulty on Older Drivers’ Performance and Behaviour: Visual vs. Cognitive

Driver distraction is an important contributing factor to increase crash risks. The effect of secondary task engagement may vary by interaction types and driver age. Thus, it is essential to understand the impacts of distraction type and age on driving performance for improving the safety of in-vehicle secondary task design. This paper aims to assess potential risks induced by visual and auditory secondary tasks while driving. Thirty drivers, consisted of fifteen younger drivers aged 25 ∼ 35 and fifteen older aged 60 ∼ 69, were recruited and asked to drive in a simulator. They conducted two driving sessions, one for visually distracted driving and the other for cognitive distraction. The order in which secondary tasks were presented was counter-balanced. Driving performance and behaviour data were collected continuously using multiple measurement devices for vehicle speed, lane position, electrocardiogram, and gaze pattern. Differences in younger and older drivers’ performance while conducting the secondary tasks were compared. The result indicated that the effect of interaction types, i.e., visual and auditory, on older drivers’ performance was significant. More difficult secondary task creates greater age difference in driving performance. However, eye movement and physiological response were not significantly different between younger and older drivers. This result could suggest older drivers’ lower risk awareness of cognitive distraction.

Comprehensive validation of halcyon 2.0 plans and the implementation of patient specific QA with multiple detector platforms.

PurposeTo perform a comprehensive validation of plans generated on a preconfigured Halcyon 2.0 with preloaded beam model, including evaluations of new features and implementing the patient specific quality assurance (PSQA) process with multiple detectors.MethodsA total of 56 plans were generated in Eclipse V15.6 (Varian Medical System) with a preconfigured Halcyon treatment machine. Ten plans were developed via the AAPM TG‐119 test suite with both IMRT and VMAT techniques. 34 clinically treated plans using C‐arm LINAC from 24 patients were replanned on Halcyon using IMRT or VMAT techniques for a variety of sites including: brain, head and neck, lung, breast, abdomen, and pelvis. Six of those plans were breast VMAT plans utilizing the extended treatment field technique available with Halcyon 2.0. The dynamically flattened beam (DFB), another new feature on Halcyon 2.0, was also used for an AP/PA spine and four field box pelvis, as well as ten 3D breast plans. All 56 plans were measured with an ion chamber (IC), film, portal dosimetry (PD), ArcCHECK, and Delta4. Tolerance and action limits were calculated and compared to the recommendations of TG‐218.ResultsTG‐119 IC and film confidence limits met those set by the task group, except for IMRT target point dose. Forty‐four of 46 clinical plans were within 3% for IC measurements. Average gamma passing rates with 3% dose difference and 2mm distance‐to‐agreement for IMRT/VMAT plans were: Film – 96.8%, PD – 99.9%, ArcCHECK – 99.1%, and Delta4 – 99.2%. Calculated action limits were: Film – 86.3%, PD – 98.4%, ArcCHECK – 96.1%, and Delta4 – 95.7%. Extended treatment field technique was fully validated and 3D plans with DFB had similar results to IMRT/VMAT plans.ConclusionHalcyon plan deliveries were verified with multiple measurement devices. New features of Halcyon 2.0 were also validated. Traditional PSQA techniques and process specific tolerance and action limits were successfully implemented.

Design of an Integrated Module for Monitoring Coastal Safety Based on a Cyber Physical System

Park, M.-C. and Ha, O.-K., 2019. Design of an integrated platform for monitoring coastal safety based on Cyber Physical System. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 286-290. Coconut Creek (Florida), ISSN 0749-0208.This study proposes a common module that can integrate multiple sources of situational information for coastal safety monitoring based on a cyber physical system (CPS). Existing situational measurement devices transmit information using different methods, which leads to considerably difficulty in system operations. This study proposes a system that can monitor coastal safety using a common module that integrates signals transmitted from multiple measurement devices. A protocol for sending and receiving packets between the measurement devices and the module is designed. The packets transmitted by the network are saved and managed through an integrated monitoring system, and information is provided to various users, such as safety personnel. The results of this study can be utilized in application programs for beach monitoring, risk warnings, risk prediction, among others.

A Fusion Measurement Approach to Improve Quantum State Tomography Efficiency and Accuracy

Quantum state tomography (QST) is an important tool for estimating an unknown quantum state, which includes a measurement process and a reconstruction process. The state estimation error involves the measurement-induced (probability estimation) error in the measurement process and the calculation error in the reconstruction process. Via the mean-square error methods, we propose two fusion measurement schemes with multiple measurement devices (MMDs) to improve the efficiency and accuracy of quantum state measurement and QST by using information fusion theory. These two schemes are founded on the parallel synchronous measurements of MMDs and, therefore, can improve the efficiency of quantum state measurement and tomography. At the same time, by fusing measurement data from different measurement devices in optimal and suboptimal manners, the proposed multiple-measurement-device fusion measurement schemes achieve the improvement of quantum state measurement and tomography accuracy. Numerical simulations are presented to demonstrate the proposed method.

An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

Atmospheric conditions have a clear influence on wake effects. Stability classification is usually based on wind speed, turbulence intensity, shear and temperature gradients measured partly at met masts, buoys or LiDARs. The objective of this paper is to find a classification for stability based on wind turbine Supervisory Control and Data Acquisition (SCADA) measurements in order to fit engineering wake models better to the current ambient conditions. Two offshore wind farms with met masts have been used to establish a correlation between met mast stability classification and new aggregated statistical signals based on multiple measurement devices. The significance of these new signals on power production is demonstrated for two wind farms with met masts and validated against data from one further wind farm without a met mast. We found a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity when the wind turbines were operating in partial load.

Concepts for validating intelligent process measurements

With increased automation, operational validation is vital for effective control, maintenance and management of industrial plants and processes. Validation should be traceable, starting from the interface to the process up to the highest level of operations. At present, validation is focused at the systems level and current methods are based on condition monitoring, and fault detection and isolation techniques using functional, analytical and hardware redundancy. With the focus at the systems level, redundancy methods exploit integration and fusion of information from multiple measurement devices, and thus tend to disregard validation of the operation of the individual devices themselves. Transducers and sensors provide an interface to the process and produce measurement information. Validation of the measurement output from a sensor is imperative in situations where the cost of redundancy may be prohibitive. This paper presents concepts for validating measurements made with intelligent devices. The proposition is that an intelligent device should provide both measurement and condition information. The condition information should be used to assess the validity of the measurement by identifying metrics which describe the sensor and process conditions, respectively. This is the lowest level of validation because it occurs at the interface with the process being monitored. The information required for this level of validation can be obtained by utilizing all the components of the signal produced by a sensor, providing that the sensor has a wide frequency response. An example of a validation approach which follows from this argument is briefly described.

Teachers do not Deal in Widgets

Although the use of merit pay, incentive pay, bonus pay, and job promotion are well‐established measures in the private or corporate sector of American society, few examples of successful teacher merit pay systems exist. In 1983, the Eastern Washington University Department of Education surveyed six major private corporations to determine whether corporate merit pay programs could be applied to teachers and educational institutions. Survey findings suggest several reasons why merit pay programs for teachers will probably fail: (a) lack of monetary goals; (b) the necessity for subjective evaluation, which requires multiple measurement devices, extensive supervision, and time; (c) the absence of a many‐tiered corporate structure in most educational institutions; and (d) increased supervisory direction that could stifle creativity and flexibility.