Active Power Measurement Research Articles

Analysis of Smart Power Sockets Implementation

In this paper an analysis of implementation alternatives of smart electrical power sockets is presented. Smart socket (SSoc) functionality include power measurement, wireless connectivity, and load control. Power measurement uncertainty is defined by SSoc design and calibration. We investigate influence of voltage and current waveforms quantization errors and influence of Hall current sensor noise upon the active power measurement uncertainty. Voltage and current measurement module is calibrated by estimating corresponding gain factors using reference power analyser. Then calibration errors influence upon power measurement errors is studied. SSoc internal power dissipation is analysed by means of alternative power supply modules prototyping.DOI: http://dx.doi.org/10.5755/j01.eee.21.6.13754

A New Method of Active Power Measurement Based on Power Load Wiener-G Functionals Models

For the problem of electrical energy measurement could not be united under the condition of non-stationary distortion signals, in the paper, the functionals series was used to modeling the signals. Firstly, the Wiener kernel of nonlinear load was acquired; the output signal of nonlinear load was expressed using functionals series under the condition of sinusoidal excitation; and then, we used the wavelet transform to processed and acquired component of fundamental and distortion; and though the acquisition component of voltage and current, we analyzed the power flow of nonlinear load, and according the result of power flow, we proposed a new method of active power measurement. The simulation result shows that the result of theoretical analysis is the same as the new method, and the new method of electric energy measurement based on the functional series can achieve the reasonable electrical energy measurement.

Characteristic Function of Fundamental and Harmonic Active Power in Digital Measurements Under Nonsinusoidal Conditions

This work provides the analytical derivation of the characteristic function of noisy digital measurements of fundamental and harmonic active power in electrical systems. Knowledge of the characteristic function, in fact, allows a complete statistical description of the measured active power since both the probability density function and the distribution function can be readily derived. Moreover, from the characteristic function all the statistical moments can be evaluated, whereas in the existing literature only the first- and second-order moments of the fundamental component were provided. More specifically, it is well known that voltage and current waveforms in electrical systems under non-sinusoidal conditions are digitized through analog-to-digital conversion and transformed into the frequency domain. Each waveform spectral line is processed to evaluate active power at the corresponding frequency. Since spectral lines are affected by additive noise the measured active power can be properly treated as a random variable. In particular, harmonic active power is more sensitive to additive noise since it is given by low-magnitude spectral lines. In the paper, the probability density function corresponding to the derived characteristic function is validated through numerical simulation of the whole measurement process and the impact of waveform and sampling parameters is investigated.

A New Method of Active Power Measurement Under the Conditions of Distortion Signals Based on Multiple Wavelets

It is discussed that a new method for active power measurement under the conditions of distortion signals. Accurate measurement of the power consumed by the distorted signals has been focused on in recent years due to its practical utilities. In this work, a mathematical description of powers is deducted in the conditions of distorted signals according to a simplified model of the electrical network. Then, a rational measuring method of the electric energy for distorted signals is proposed on the basis of the analysis of the power flow. Also, a measuring method based on multiple wavelets was employed for measuring the active power in the conditions of unsteady distorted signals. Experimental results demonstrate that, by using the simulated typical distorted signals, the proposed measurement method can produce extremely accurate results compared to theoretical results.

Identification of synchronous generator model with frequency control using unscented Kalman filter

In this paper, phasor measurement unit (PMU) data-based synchronous generator model identification is carried out using unscented Kalman filter (UKF). The identification not only gives the model of a synchronous generator's swing dynamics, but also gives its turbine-governor model along with the primary and secondary frequency control block models. PMU measurements of active power and voltage magnitude, are treated as the inputs to the system while the measurements of voltage phasor angle, reactive power and frequency are treated as the outputs. UKF-based estimation is carried out to estimate the dynamic states and the parameters of the model. The estimated model is then built and excited with the injection of the inputs from the PMU measurements. The outputs of the estimation model and the outputs from the PMU measurements are compared. Case studies based on PMU measurements collected from a simulation model and real-world PMU data demonstrate the effectiveness of the proposed estimation scheme.

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.

Decoder-Complexity-Aware Encoding of Motion Compensation for Multiple Heterogeneous Receivers

For mobile multimedia systems, advances in battery technology have been much slower than those in memory, graphics, and processing power, making power consumption a major concern in mobile systems. The computational complexity of video codecs, which consists of CPU operations and memory accesses, is one of the main factors affecting power consumption. In this article, we propose a method that achieves near-optimal video quality while respecting user-defined bounds on the complexity needed to decode a video. We specifically focus on the motion compensation process, including motion vector prediction and interpolation, because it is the single largest component of computation-based power consumption. We start by formulating a scenario with a single receiver as a rate-distortion optimization problem and we develop an efficient decoder-complexity-aware video encoding method to solve it. Then we extend our approach to handle multiple heterogeneous receivers, each with a different complexity requirement. We test our method experimentally using the H.264 standard for the single receiver scenario and the H.264 SVC extension for the multiple receiver scenario. Our experimental results show that our method can achieve up to 97% of the optimal solution value in the single receiver scenario, and an average of 97% of the optimal solution value in the multiple receiver scenario. Furthermore, our tests with actual power measurements show a power saving of up to 23% at the decoder when the complexity threshold is halved in the encoder.

A Comparison Between the NIST PJVS-Based Power Standard and the NRC Current- Comparator-Based Power Standard

This paper presents the results of a comparison of active/reactive power meter calibrations between the National Institute of Standards and Technology and National Research Council. The comparison was implemented using a transfer standard consisting of a highly stable commercial sampling-type power/energy meter. Active and reactive power measurements were made at 120 V, 5 A, 50 Hz, and 60 Hz. For active power, the measurements were made at applied current phase angles of 0°, +60°, and -60°. For reactive power, the measurements were made at applied current phase angles of +60°, +90°, -60°, and -90° . The results of the comparison indicate agreement to within the stated uncertainties of the participants.

Rogowski coil current transducer compensation method for harmonic active power error

In the harmonic active power measurement, the highest uncertainties are generally introduced by the current and voltage transducers. In a previous paper, the authors showed that the current transformer (CT) can introduce significant errors in such measurement, especially if the phase shift between voltage and current is close to ±90°. In such condition the errors on harmonic power measurement are mainly due to the CT phase displacement. This paper shows that better results can be achieved with more linear transducers, such as the Rogowski coil current transducers (RCCTs), whose metrological performance in distorted condition can be improved, by means of a proper compensation method. The proposed method for RCCTs compensation is based on the frequency response and it allows to reduce the errors on harmonic power measurement, also for phase shift close to ±90°. The study is supported by several experimental tests.

Simultaneous Estimation of the Time of Disturbance and Inertia in Power Systems

Offnominal power system frequency regimes play a key role in the propagation of disturbed system conditions and blackouts. The evolution of power systems will make the availability of frequency-control services more uncertain, increasing the risk of large frequency deviations. Furthermore, the reduction in the inherent inertia of power systems and their increased variability will be a critical threat to the quality of frequency control. This paper proposes an online algorithm for estimating the time of disturbance and inertia after a disturbance. This is in contrast to previous inertia estimation methods that operated offline. The algorithm processes wide-area measurements of frequency and active power and could provide support for adaptive frequency control. Simulations, laboratory tests, and real transmission system measurements have been used to demonstrate the algorithm's ability to correctly detect a disturbance, accurately estimate the time of the disturbance and the inertia, and prevent false disturbance detections.

A New Improved Walsh Function Algorithm for Active and Reactive Power Measurement

This paper present improved Walsh function (IWF) algorithm as an alternative approach for active and reactive power measurement in linear and nonlinear, balanced and unbalanced sinusoidal three phase load system. It takes advantage of Walsh function unified approach and its intrinsic high level accuracy as a result of coefficient characteristics and energy behaviour representation. The developed algorithm was modeled on the Matlab Simulink software; different types of load, linear and nonlinear were also modeled based on practical voltage and current waveforms and tested with the proposed improved Walsh algorithm. The IEEE standard 1459-2000 which is based on fast Fourier transform FFT approach was used as benchmark for the linear load system while a laboratory experiment using Fluke 435 power quality analyzer PQA which complies with IEC/EN61010-1-2001standards was used to validate the improved algorithm for nonlinear load measurement. The results showed that the algorithm has the potential to effectively measure three phase power components under different load conditions.

Analysis and compensation of active power measurement error caused by non-integer period sampling

A software compensation method is proposed in this paper to reduce the active power measurement error which is caused by non-integer period sampling in the electrical energy measurement process. In the process of electrical energy measurement, the sampling frequency is fixed, and it is an integer multiple of the standard frequency. When the grid frequency fluctuates, the real-time frequency deviates from the standard frequency, therefore, the sampling rate is not strictly the integer multiple of the grid frequency, which may leads to active power error. In this paper, we firstly calculate the analytic equation of active power error in non-integer period sampling, which includes the theory value and the error value, then the active power value of integral period sampling can be obtained by subtracting the error part. Finally, the MATLAB simulation shows the correction and effective of the compensation method, and it can significantly improve the accuracy of energy measurement.

Measurements of harmonic emission versus active power from wind turbines

This paper presents harmonic measurements from three individual wind turbines (2 and 2.5MW size). Both harmonics and interharmonics have been evaluated, especially with reference to variations in the active-power production. The overall spectra reveal that emission components may occur at any frequency and not only at odd harmonics. Interharmonics and even harmonics emitted from wind turbines are relatively high. Individual frequency components depend on the power production in different ways: characteristic harmonics are independent of power; interharmonics show a strong correlation with power; other harmonic and interharmonic components present various patterns. It is concluded that the power production is not the only factor determining the current emission of a wind energy conversion system.

On the Effectiveness of Hardware Trojan Horse Detection via Side-Channel Analysis

ABSTRACTHardware Trojan Horses (HTHs) are malicious and stealthy alterations of integrated circuits introduced at design or fabrication steps in order to modify a circuit’s intended behavior when deployed in the field. Due to HTHs’ stealth and diversity (intended alteration, implementation, triggering conditions), detecting and/or locating them is challenging. Several HTHs detection approaches have been proposed to address this problem. This paper focuses on so-called “side-channel analysis” methods, that is, methods that use power or delay measurements to detect potential HTHs. It reviews these methods and raises some considerations about the experiments made to evaluate them. Moreover, an original case study is presented in which we show that weak experiments may lead to misleading interpretations. Last, we evoke problems inherent to actual power and delay measurements.

IMeter: An integrated VM power model based on performance profiling

The unprecedented burst in power consumption encountered by contemporary datacenters continually boosts the development of energy efficient techniques from both hardware and software perspectives to alleviate the energy problem. The most widely adopted power saving solutions in datacenters that deliver cloud computing services are power capping and VM consolidation. However, without the capability to track the VM power usage precisely, the combined effect of the above two techniques could cause severe performance degradation to the consolidated VMs, thus violating the user service level agreements. In this paper, we propose an integrated VM power model called iMeter, which overcomes the drawbacks of overpresumption and overapproximation in segregated power models used in previous studies. We leverage the kernel-based performance counters that provide accurate performance statistics as well as high portability across heterogeneous platforms to build the VM power model. Principal component analysis is applied to identify performance counters that show strong impact on the VM power consumption with mathematical confidence. We also present a brief interpretation of the first four selected principal components on their indications of VM power consumption. We demonstrate that our approach is independent of underlying hardware and virtualization configurations with clustering analysis. We utilize the support vector regression to build the VM power model predicting the power consumption of both a single VM and multiple consolidated VMs running various workloads. The experimental results show that our model is able to predict the instantaneous VM power usage with an average error of 5% and 4.7% respectively against the actual power measurement.

Power containers

Energy efficiency and power capping are critical concerns in server and cloud computing systems. They face growing challenges due to dynamic power variations from new client-directed web applications, as well as complex behaviors due to multicore resource sharing and hardware heterogeneity. This paper presents a new operating system facility called "power containers" that accounts for and controls the power and energy usage of individual fine-grained requests in multicore servers. This facility relies on three key techniques---1) online model that attributes multicore power (including shared maintenance power) to concurrently running tasks, 2) alignment of actual power measurements and model estimates to enable online model recalibration, and 3) on-the-fly application-transparent request tracking in multi-stage servers to isolate the power and energy contributions and customize per-request control. Our mechanisms enable new multicore server management capabilities including fair power capping that only penalizes power-hungry requests, and energy-aware request distribution between heterogeneous servers. Our evaluation uses three multicore processors (Intel Woodcrest, Westmere, and SandyBridge) and a variety of server and cloud computing (Google App Engine) workloads. Our results demonstrate the high accuracy of our request power accounting (no more than 11% errors) and the effectiveness of container-enabled power virus isolation and throttling. Our request distribution case study shows up to 25% energy saving compared to an alternative approach that recognizes machine heterogeneity but not fine-grained workload affinity.

Power containers

Energy efficiency and power capping are critical concerns in server and cloud computing systems. They face growing challenges due to dynamic power variations from new client-directed web applications, as well as complex behaviors due to multicore resource sharing and hardware heterogeneity. This paper presents a new operating system facility called "power containers" that accounts for and controls the power and energy usage of individual fine-grained requests in multicore servers. This facility relies on three key techniques---1) online model that attributes multicore power (including shared maintenance power) to concurrently running tasks, 2) alignment of actual power measurements and model estimates to enable online model recalibration, and 3) on-the-fly application-transparent request tracking in multi-stage servers to isolate the power and energy contributions and customize per-request control. Our mechanisms enable new multicore server management capabilities including fair power capping that only penalizes power-hungry requests, and energy-aware request distribution between heterogeneous servers. Our evaluation uses three multicore processors (Intel Woodcrest, Westmere, and SandyBridge) and a variety of server and cloud computing (Google App Engine) workloads. Our results demonstrate the high accuracy of our request power accounting (no more than 11% errors) and the effectiveness of container-enabled power virus isolation and throttling. Our request distribution case study shows up to 25% energy saving compared to an alternative approach that recognizes machine heterogeneity but not fine-grained workload affinity.

Measurement of active power using fiber bragg grating and a piezo‐electric transducer

AbstractThis article develops an optical fiber sensor using fiber Bragg grating (FBG) and a piezo‐electrical transducer (PZT) to measure active power.Mounting an FBG on a PZT bar, a dynamic strain simulator was constructed. The equivalent voltage produced by active power applied to the PZT was converted to the dynamic variation of the FBG Bragg wavelength. The active power was attained by measuring the changing value of the wavelength. Thus, the sensor can be used to measure active power without the use of a traditional power meter. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:682–686, 2013; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27394

Low Power Consumption Solutions for Mobile Instant Messaging

Instant messaging (IM) services enable real-time text and multimedia exchange and online presence awareness. Users typically log onto instant messaging services persistently to discover available friends and also to be discovered. However, our analysis shows that the frequency exchange of presence information incurs massive power consumption to mobile devices over cellular or wireless local area networks. Such power consumption penalty can render persistent-instant messaging infeasible for battery-powered mobile devices. In this paper, we propose several solutions to mitigate the power consumption problem. By reducing the network access and keeping mobile devices in the sleep mode as much as possible, these solutions achieve significant power saving. The power consumption of the proposed solutions is derived analytically in this paper and the proposed solutions are implemented using a Jabber-based architecture. Actual power measurement results show that the power consumption of the proposed solutions agrees well with our analysis, and significant power saving can be achieved on mobile handsets with our low power consumption solutions implemented.

Comparison of the Performance of Vector Control and Direct Power Control of Induction Generator in Wind Energy Conversion System

The conventional approach for independent control of active and reactive powers handled by the machine is stator flux oriented vector control with rotor position sensors. The performance of the system in this case depends on the accuracy of computation of the stator flux and the accuracy of the rotor position information derived from the position encoder. In vector control, power is controlled by rotor current injection. Direct power control is a rotor side control of a doubly fed induction generator by which decoupled control of stator active and reactive power can be obtained. It is based on the measurement of active and reactive power on the grid side where voltages and currents are alternating at fixed frequency. The active and reactive powers are made to track references using hysteresis controllers. The measurements are taken on stator side and the control is made on rotor side. This control system eliminates the need for rotor position sensing and gives an excellent dynamic performance with simulation results for a variable speed constant frequency induction generator system. The system can be operated below, at and above synchronous speed. The controlling schemes are explained and the modelling of the complete system is done in MATLAB–SIMULINK.