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The worldwide major blackout events of power network are highlighting the need for technology upgradation in traditional grid. One of the major upgradations required is in the area of early warning generation in case of any grid disturbances such as line contingency leading to cascade failure. This paper proposes a proactive blackout prediction model for a smart grid early warning system. The proposed model evaluates system performance probabilistically, in steady state and under dynamical (line contingency) state, and prepares a historical database for normal and cascade failure states. A support vector machine (SVM) has been trained with this historical database and is used to predict blackout events in advance. The key contribution of this paper is to capture the essence of the cascading failure using probabilistic framework and integration of SVM machine learning tool to build a prediction rule, which would be able to predict the scenarios of the blackout as early as possible. The proposed model is validated using the IEEE 30-bus test-bed system. Proactive prediction of cascade failure using the proposed model may help in realizing the grid resilience feature of smart grid. [ABSTRACT FROM PUBLISHER]

The detection and classification of power quality (PQ) disturbances have become a pressing concern due to the increasing number of disturbing loads connected to the power line and the susceptibility of certain loads to the presence of these disturbances; moreover, they can appear simultaneously since, in any real power system, there are multiple sources of different disturbances. In this paper, a new dual neural-network-based methodology to detect and classify single and combined PQ disturbances is proposed, consisting, on the one hand, of an adaptive linear network for harmonic and interharmonic estimation that allows computing the root-mean-square voltage and total harmonic distortion indices. With these indices, it is possible to detect and classify sags, swells, outages, and harmonics–interharmonics. On the other hand, a feedforward neural network for pattern recognition using the horizontal and vertical histograms of a specific voltage waveform can classify spikes, notching, flicker, and oscillatory transients. The combination of the aforementioned neural networks allows the detection and classification of all the aforementioned disturbances even when they appear simultaneously. An experiment under real operating conditions is carried out in order to test the proposed methodology. [ABSTRACT FROM PUBLISHER]

This paper describes a computationally efficient approach for mapping rotor power loss in permanent magnet (PM) machines. The PM loss mapping methodology discussed here utilizes a small number of time-step finite-element analyses (FEAs) to determine the parameters of a functional representation of loss variation with speed (frequency) and stator current and is intended for a rapid evaluation of machine performance over the entire torque–speed envelope. The research focus is placed on field-oriented-controlled brushless AC PM machines with surface-mounted PM rotor construction, although the method could be adapted for other rotor formats. The loss mapping procedure accounts for the axial segmentation of the PM array through the use of an equivalent electrical resistivity of the segmented PM array, which is obtained from three-dimensional (3-D) FEA. The PM loss can be accurately mapped across the full operational envelope, including the field-weakened mode, through a single 3-D and four two-dimensional time-step FEAs. The proposed methodology is validated on an 18-slot 16-pole surface-mounted brushless AC PM machine design. The loss mapping procedure results closely agree with the computationally demanding alternative of direct 3-D finite-element prediction of the PM power loss undertaken at each of the machine's operating points. [ABSTRACT FROM PUBLISHER]

Voltage flicker is one of many serious power quality disturbances, which would deteriorate the stability and operation efficiency of a power system. Effective evaluation of flicker severity plays an important role in the monitoring and control of developing advanced metering infrastructure. Since the evaluation process for voltage flicker is complicated, some inaccurate intermediate results may give rise to the propagation of estimation errors. Therefore, an accurate solution procedure for the calculation of voltage flicker components is proposed in this paper. With the extraction technique for envelope signal and high-frequency resolution mechanism for flicker spectral analysis, the superior performance to achieve the instantaneous flicker severity evaluation can be obtained. [ABSTRACT FROM PUBLISHER]

This paper proposes a repetitive controller with phase-lead compensation for an unfolding-type Cuk continuous conduction mode (CCM) inverter operating in the CCM. The Cuk CCM inverter features medium power capacity, step up/down ability, and low input/output current ripples, so it is well suited to distributed power generation systems. To achieve accurate tracking of the reference output current, we make the use of the repetitive controller coupled with a conventional proportional-integral controller and a nominal duty ratio. In developing the proposed controller, we use the average model of the Cuk CCM inverter in the grid-connected case. The two right-half plane (RHP) zeros in the transfer function of the Cuk CCM inverter cause phase lag of the closed-loop system; to compensate for the phase lag, we implement a phase-lead compensation algorithm in the repetitive control scheme. We also provide detailed and practical design guidelines of the control parameters to develop a stable Cuk CCM inverter. Experimental tests using a 500-W Cuk CCM inverter demonstrate the desirable performance of the proposed control approach. [ABSTRACT FROM PUBLISHER]

Voltage sags are considered one of the worst perturbations in power systems. Distributed generation power facilities are allowed to disconnect from the grid during grid faults whenever the voltage is below a certain threshold. During these severe contingencies, a cascade disconnection could start, yielding to a blackout. To minimize the risk of a power outage, inverter-based distributed-generation systems can help to support the grid by appropriately selecting the control objective. Which control strategy performs better when supporting the grid voltage is a complex decision that depends on many variables. This paper presents a control scheme that implements a smart and simple strategy to support the fault: the maximum voltage support for the lowest phase voltage. Therefore, the faulted phase that is more affected by the sag can be better supported since this phase voltage increases as much as possible, reducing the risk of undervoltage disconnection. The proposed controller has the following features: 1) maximizes the voltage in the lowest phase, 2) injects the maximum rated current of the inverter, and 3) balances the active and reactive power references to deal with resistive and inductive grids. The control proposal is validated by means of experimental results in a laboratory prototype. [ABSTRACT FROM PUBLISHER]

This paper presents real-time implementation of a new frequency adaptive least-squares-Kalman (LSK) technique to monitor voltage flicker and fluctuations in power system. The proposed method is based on a two-level mathematical model of a voltage waveform. A simple low computation frequency tracking method is also introduced. The least-squares (LS) optimization algorithm extracts the fundamental frequency component of the voltage and updates its internal model based on the estimated frequency of the voltage waveform. The Kalman filter, which works in combination with the LS algorithm, is developed to predict the instantaneous voltage flicker level. The proposed method is robust and adaptive and is evaluated experimentally through real-time implementation with a widely available digital control board. [ABSTRACT FROM PUBLISHER]

Uninterruptible power supplies (UPSs) have been used in many installations for critical loads that cannot afford power failure or surge during operation. It is often difficult to upgrade the UPS system as the load grows over time. Due to lower cost and maintenance, as well as ease of increasing system capacity, the parallel operation of modularized small-power UPS has attracted much attention in recent years. In this paper, a new scheme for parallel operation of inverters is introduced. A multiple-input-multiple-output state-space model is developed to describe the parallel-connected inverters system, and a model-predictive-control scheme suitable for paralleled inverters control is proposed. In this algorithm, the control objectives of voltage tracking and current sharing are formulated using a weighted cost function. The effectiveness and the hot-swap capability of the proposed parallel-connected inverters system have been verified with experimental results. [ABSTRACT FROM AUTHOR]

In order to prevent unexpected electrical outage and to save on repair expenses, an online data-driven prognosis method for monitored underground cable is proposed. The method is nondestructive and nonintrusive. The field data of voltage and current were collected from an underground distribution cable lateral installed in a residential area. Potential useful features were selected based on the data-driven method using the training data. The rationality of selected features was verified in view of cable aging mechanisms; after that, the useful features were finally determined. The remaining life of cable was forecasted by predicting the time for the cumulative effect of the selected features to reach the threshold. The performance of the developed prognosis method was tested and evaluated using the field testing data. The standard deviation of the prognosis results at different arrival times is used as a source of uncertainty estimation (reverse of confidence estimation). The results demonstrate that the method can continually offer valuable remaining life prediction of the monitored underground cable as time goes on. When the predicted fault times approach the actual fault time, the standard deviation value is small. When the standard deviation value is small, there are steady forecast results and usually small residuals. [ABSTRACT FROM PUBLISHER]

In this paper, a high-performance single-phase transformerless online uninterruptible power supply (UPS) is proposed. The proposed UPS is composed of a four-leg-type converter, which operates as a rectifier, a battery charger/discharger, and an inverter. The rectifier has the capability of power-factor collection and regulates a constant dc-link voltage. The battery charger/discharger eliminates the need for the transformer and the increase of the number of battery and supplies the power demanded by the load to the dc-link capacitor in the event of the input-power failure or abrupt decrease of the input voltage. The inverter provides a regulated sinusoidal output voltage to the load and limits the output current under an impulsive load. The control of the dc-link voltage enhances the transient response of the output voltage and the utilization of the input power. By utilizing the battery charger/discharger, the overall efficiency of the system is improved, and the size, weight, and cost of the system are significantly reduced. Experimental results obtained with a 3-kVA prototype show a normal efficiency of over 95.6% and an input power factor of over 99.7%. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) modules subject to partial shading (PS) or inhomogeneous irradiation drastically decrease the PV string power output. An algorithm composed of maximum voltage point tracking (MVPT) and maximum power point (MPP) tracking (MPPT) is presented to restore part of the power loss caused by PS. The MVPT can simultaneously drive the operating point of series PV modules toward their respective MPPs and guarantee power peak uniqueness. The MVPT is performed by means of a controllable current transformer (CCT) disposed at the terminal of each PV module permitting a compatible current in the series path of a PV string. The CCT output current can be regulated using a dependent current source according to the MPPT algorithm. An appropriate CCT current determined by the MPPT algorithm can avert undue CCT activation and consequently reduces the switching and copper losses of the converter circuit. Experimental results validate that the proposed strategy can balance the PV modules' output current subject to PS and facilitate convergence to the theoretical global MPP. [ABSTRACT FROM PUBLISHER]