A Topological algorithm for observability analysis with PMU measurements

This study proposes a compensation strategy to deal with both current and voltage measurement errors in the three-phase PWM rectifier system. The DC offset and scaling errors in the voltage and current measurements cause the injection of undesired DC and unbalanced currents into the three-phase input current and subsequently lead to voltage ripple at the DC output voltage. This paper proposes a compensation scheme for current measurement error where the DC offset and scaling errors in the current measurement are estimated from the characteristic of the DC output voltage ripple combining with simple band-pass and low-pass filters. Meanwhile, an advanced current controller designed with a proportional integral plus two resonant controllers tuned at the fundamental grid frequency (ω <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</inf> ) and 2ω <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</inf> in the synchronous (d-q) reference frame is suggested to reject the impact of the DC offset and scaling errors in the voltage measurement. The proposed compensation method is developed without the need of extra hardware circuit, sensor, or precise information of system parameters so that it can be considered as more cost effective and robust solution. The effectiveness of the proposed solution is verified by experimental results.

The knowledge of line parameters is fundamental for building a network model that can become the basis for all the monitoring and management applications. Network line impedances are employed, for instance, for the state estimation or for protection applications in relay setting. The Phasor Measurement Units (PMUs), thanks to the synchronized voltage and current phasor measurements, provide the accurate information that can be used to evaluate the network parameters of the monitored branches. Nevertheless, the impact of instrument transformers (ITs) makes the parameter estimation a hard task. For this reason, in this paper an estimation paradigm is proposed that includes the estimation of both systematic errors (mainly due to ITs) and line parameters. The proposed method, particularly focused on distribution systems, is designed to perform simultaneous estimations across different branches of the network, aiming at exploiting the links between the involved parameters, due to topology and operating conditions. The estimation is based on a sound and detailed model of the uncertainty sources.

This paper proposes a novel fault location method for active distribution networks. The voltage and current phasor measurements at each terminal of the network are typically required. The overall model of the active distribution nenvork with fault is established with the distribution line model of each section. The three phase matrix representation of physical laws of the distribution line is utilized to consider the asymmetrical distribution circuit. Moreover, the line shunt admittance can be considered in the proposed method to obtain more accurate fault location results. The proposed fault location algorithm first identifies the faulted line section and afterwards adopts state estimation method to identify the fault location. The benefits of considering line shunt admittances are also discussed. Numerical experiments verify that the proposed method can work for the unbalanced distribution system and asymmetrical lines. It is also shown that the consideration of line shunt admittances yields better fault location results.

In this paper an approach towards databased fault diagnosis of linear electromagnetic actuators is presented. Time and time-frequency-domain methods were applied to extract fault related features from current and voltage measurements. The resulting features were transformed to enhance class separability using either Principal Component Analysis (PCA) or Optimal Transformation. Feature selection and dimensionality reduction was performed employing a modified Fisher-ratio. Fault detection was carried out using a Support-Vector-Machine classifier trained with randomly selected data subsets. Results showed, that not only the used feature sets (time-domain/time-frequency-domain) are crucial for fault detection and classification, but also feature pre-processing. PCA transformed time-domain features allow fault detection and classification without misclassification, relying on current and voltage measurements making two sensors necessary to generate the data. Optimal transformed time-frequency-domain features allow a misclassification free result as well, but as they are calculated from current measurements only, a dedicated voltage sensor is not necessary. Using those features is a promising alternative even for detecting purely supply voltage related faults.

The interaction of an atmospheric pressure plasma jet with two different surfaces (conducting and dielectric) is investigated using a setup with two ring electrodes around a dielectric capillary. For diagnostics, phase resolved ICCD-imaging, current measurements and surface charge measurements are applied. The results show the correlation of plasma dynamics with the deposition of surface charge and electrical current signals. Further, the influence of the distance between surface and jet capillary on the surface charge distribution is presented. A complex discharge dynamic is found with a dielectric barrier discharge between the ring electrodes and back-and-forth bullet propagation outside the capillary. A conducting channel connecting the jet nozzle and the surface is found. This correlates well with the observed charge exchange on the surface. The number of formed channels and the average deposited charge density on the surface is found to be strongly sensitive to the jet distance from the surface.

The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed.

To design motor drives for optimal motion control, and to obtain precise Brushless DC motor model, accurate measurement of motor parameters like phase current, speed and torque are required. Speed and current are also required to provide feedback between the BLDC motor and its controller to develop a robust BLDC motor control algorithm. In this paper, phase current, speed and torque measurement technique for Hub BLDC motor is presented to analyze its performance for low power electric vehicle applications. For the phase current measurement, the Hall-Effect current sensor ACS712 is used. The speed of the motor is calculated using an internal hall sensor that is connected to dsPIC33F’s input capture pin that generates an interrupt whenever a change in the hall sensor signal value occurs. Further, an experimental setup is established in the laboratory to measure the torque at varying load and to determine the relationship between motor torque, input current, output power, speed and efficiency.

Guest Editorial: Situational awareness of integrated energy systems

Luquire et al.'s impedance change model of a rectangular cross section probe coil above a structure with an arbitrary number of parallel layers was used to study the principle of measuring thicknesses of multi-layered structures in terms of eddy current testing voltage measurements. An experimental system for multi-layered thickness measurement was developed and several fitting models to formulate the relationships between detected impedance/voltage measurements and thickness are put forward using least square method. The determination of multi-layered thicknesses was investigated after inversing the voltage outputs of the detecting system. The best fitting and inversion models are presented.

This paper proposes a position estimation method for the planar switched reluctance motor (PSRM). This method estimates the mover position of the PSRM using a sliding mode observer (SMO). The proposed method directly estimate the position of the mover according to the terminal measurement of phase voltage and current, without a need for additional detection devices or internal memory, achieving a more compact and cost-effective PSRM drive. Sensorless closed-loop control strategy without position sensor for the PSRM is proposed based on the SMO. A simulation model of the SMO is built, and the effectiveness of the position estimation method for the PSRM is verified by simulation.

This article proposed a novel method for current sensing of multicore cables utilizing a tunnel-magnetoresistance (TMR) sensor array. In fact, multicore cables belong to multi-conductor systems. A trans-impedance is built to describe the mathematical relationship between the current phasors of the multi-conductor system and the output voltage phasors of all the magnetic sensors, based on which the current phasors can be recovered by simply performing matrix multiplication. The determination of the trans-impedance is dependent on the identification of the geometry parameters of the conductors (i.e., positions and tilt angles). Based on the output voltage phasors of the magnetic sensors at fundamental frequency, these conductor parameters can be identified by solving over-determined equations which are formulated in a form of one nonlinear least square (NLLS) problem. The value of the gain factor of the designed TMR sensor is almost a constant and the value of the corresponding phase shift is approximately zero. A real trans-impedance matrix can be obtained converted from the complex one, based on which real time current waveforms reconstruction can be achieved. Simulation study and laboratory experiments are conducted to verify the validation of the proposed current sensing method. From the simulation study, it is found that a value of lower than 5% for the maximum relative current amplitude error and the corresponding value of less than 4° for the maximum phase error can be achieved though the tilt angles of the conductors are arbitrarily varied. A probe-like current sensor is fabricated and experimentally characterized. Laboratory experiments including current phasor measurement at fundamental frequency and real-time current waveforms reconstructing are conducted. For both balanced and unbalanced three-phase cases, the testing results for current phasor measurement at fundamental frequency show that a value of lower than 8.24% for the maximum relative current amplitude error and a value of smaller than 4.46° for the corresponding maximum phase error can be achieved. Meanwhile, the current waveforms for three-phase currents having plenty of harmonics are successfully recovered in real time through experiments.

Better reliability of power is assured with the inculcation of distributed generations in a distribution network. Smart sensors and latest grid communication protocols has led to the development of intelligent microgrids (MG). Protection of such grids are a key concern for power engineers, as conventional protection schemes fails while operating in microgrids. This paper presents, data analysis based fault isolation and its location prognosis. The proposed approach takes post fault, one cycle three phase voltage and current measurements as the inputs for developing a fault isolation module (FIM) and fault locator module (FLM). These modules are supposed to be available at central protection system (CPS), designed through meticulous data training, using Gaussian process regression (GPR) for fault location prediction and support vector machine (SVM) for fault identification. The effectiveness of proposed methodology is represented by considering practical grid scenarios such as varying load and DG penetration. A 14 bus meshed AC microgrid structure has been modelled in SIMULINK having three DGs and two grid sources. Data analytics tools of MATLAB 2018a has been explored to develop machine learning based protection strategy for microgrids.

Low pressure inductively coupled plasmas (ICP) operated in neon at 27.12 MHz with capacitive substrate biasing (CCP) at 13.56 MHz are investigated by phase resolved optical emission spectroscopy, voltage, and current measurements. Three coupling mechanisms are found potentially limiting the separate control of ion energy and flux: (i) Sheath heating due to the substrate biasing affects the electron dynamics even at high ratios of ICP to CCP power. At fixed CCP power, (ii) the substrate sheath voltage and (iii) the amplitude as well as frequency of plasma series resonance oscillations of the RF current are affected by the ICP power.

When the vector control is performed using PWM three phase inverter in AC motor drive system, three phase current are obtained by measuring voltage between shunt resistors. The PWM inverter obtaining three phase current by shunt resistor is comparatively cheaper than the method that measures three phase current by Current Sensor. And it reduces the size of AC motor drive system. However, the method sensing the phase current using shunt resistor cannot perform the vector control in high motor speed since there is the area that cannot measure three phase current. In this paper, the boundary where phase currents cannot be obtained is defined and the method reconstructing the phase current is proposed by predicting phase current through load modeling in the area which phase current measurement is impossible. The proposed method can restore phase current up to maximum output voltage of SVPWM inverter in linear area and validity of proposed method is proved through simulation.

This paper develops an integrated state estimation and control methodology of networked battery systems that require only terminal voltage and current measurements for reduced cost and complexity. Without direct internal voltage/current measurements and individual control on each battery pack in the system, a networked battery system is inherently uncontrollable and unobservable. By employing bypass power electronics, we show that the networked system can be made controllable and observable by switching control. To coordinate switching control for integrated state of charge (SOC) estimation and control, this paper introduces switching control algorithms that use time division, duty cycle control, and periodic switching. It is shown that under noisy terminal voltage and current measurements, state estimation algorithms are convergent, and the control algorithms can achieve balanced SOC control during operation. The proposed hardware and methodology framework is useful for networked battery systems that can accommodate battery packs of different types, ages, and power/capacity ratings. Case studies using production batteries demonstrate convergence behavior for both state estimation and SOC consensus control under time-varying charging current profiles. The approach will be especially useful for managing battery storage systems to support power grids with renewable energy sources where the battery systems are required to operate continuously.