Fault in a power system is cleared by a protection scheme which comprises of different components such as relay, circuit breaker and accessories. Collective action of all elements in a protection scheme is necessary to correctly identify and isolate a fault selectively. Failure of any element in such a protection arrangement may lead to unwanted line trip risking further outages in the network. This work proposes a wide area measurement system (WAMS) data-based technique for online identification of failure of protection element for a transmission line. Synchronised voltage–current phasors along with relay decision and circuit breaker status signals are used to calculate indices which identify the failed component. The proposed method is tested for 39-bus New-England system and found to be accurate.

A fault-transient synchrophasor is computed over a window of pre-fault and fault samples. A fault synchrophasor is computed over a window of fault samples only. Fault-transient synchrophasors are discarded and are generally not used in the synchrophasor applications. Recently, an algorithm has been proposed to compute fault synchrophasor from fault-transient synchrophasor in phasor data concentrator (PDC). The accuracy of the existing algorithm deteriorates due to fault-induced transients and inaccurate fault starting time. A robust algorithm has been proposed to compute fault synchrophasor from fault-transient synchrophasor in PDC. The proposed algorithm does not use fault starting time in the calculations. It also performs better than the existing algorithm when fault-induced transients are present in the signal. The proposed algorithm is simple, non-iterative and performs satisfactorily in various investigated scenarios. The advantage of the proposed algorithm has been demonstrated in the context of fault location application.

Smart power grids (SPGs) entail comprehensive real-time smart monitoring and controlling strategies against contingencies such as transmission line faults. This study proposes a novel methodology for identifying and classifying transmission line faults occurring at any location in a power grid from phasor measurement unit measurements at only one of the generator buses. The proposed methodology is based on frequency domain analysis of equivalent voltage phase angle and equivalent current phase angle at the generator bus. Equivalent voltage and current phase angles are the angles made by three-phase equivalent voltage and current phasors with respect to reference axis. These angles are estimated through Park's transformation and frequency domain analysis is performed over a fixed time span equal to inverse of system nominal frequency using fast Fourier transformation. The proposed methodology can be utilised for relaying purposes in case of single transmission lines as well as for system protection centre (SPC) applications in power grid. The significance of the fault information from the methodology is for assisting SPC in SPGs for transmission line fault detection and classification to restore the transmission lines at the earliest and initiate wide-area control actions to maintain system stability against disturbances generated by occurrence and clearance of fault.

Loss-of-mains protection is an important component of the protection systems of embedded generation. The role of loss-of-mains is to disconnect the embedded generator from the utility grid in the event that connection to utility dispatched generation is lost. This is necessary for a number of reasons, including the safety of personnel during fault restoration and the protection of plant against out-of-synchronism reclosure to the mains supply. The incumbent methods of loss-of-mains protection were designed when the installed capacity of embedded generation was low, and known problems with nuisance tripping of the devices were considered acceptable because of the insignificant consequence to system operation. With the dramatic increase in the installed capacity of embedded generation over the last decade, the limitations of current islanding detection methods are no longer acceptable. This study describes a new method of loss-of-mains protection based on phasor measurement unit (PMU) technology, specifically using a low cost PMU device of the authors’ design which has been developed for distribution network applications. The proposed method addresses the limitations of the incumbent methods, providing a solution that is free of nuisance tripping and has a zero non-detection zone. This system has been tested experimentally and is shown to be practical, feasible and effective. Threshold settings for the new method are recommended based on data acquired from both the Great Britain and Ireland power systems.

Phasor measurement units (PMUs) are one of the key sensor technologies for real-time wide area monitoring to realise the smart power grid vision. Before deploying the PMUs, it is important to test and validate performance of this sensor to ensure high reliability and accuracy under different operating scenarios of the power system. However, PMU testing needs to be made simpler, easier, automated and cost-effective to encourage the PMU vendors and utilities to get their PMUs tested. This has been the driving motivation for the development of a new procedure and tool for testing PMUs in this study. The results and findings of PMU testing and analysis using a newly developed software application named ‘PMU Performance Analyzer' (PPA) have been discussed in this study. PPA can work with a real-time digital simulator and a phasor data concentrator to make the PMU testing simple, easy, mostly automated, less time-consuming, highly accurate and cost-effective.

As the electrical power system has increased in its geographical sprawl, adequate measures for reliability analysis for the wide area measurement system (WAMS) and phasor measurement units (PMUs) have become necessary. However, existing PMU reliability models are constrained by the assumption that PMU failures may be encountered either because of hardware failures or because of software failures only. Most modem safety critical systems, like the PMU are characterised by close proximity of hardware and software operations which leads to correlated failures. This is referred to as hardware–software interaction failure and is disregarded by contemporary PMU reliability models. In this paper, a modelling framework has been developed using Markov process that captures hardware–software interaction failures, apart from the hardware specific and software specific failures, and presents a Markov model-based unified PMU reliability model. This paper also offers a novel Monte Carlo simulation (MCS) technique to estimate PMU failure data to account for scanty PMU failure data from field installations. The novel algorithms for MCS based PMU failure estimation are expounded along with detailed methodologies for fitting the simulated failure data to the unified reliability model. The results presented herein demonstrate the improved accuracy of the proposed method.

The wide-area situational awareness (SA) aims at an early detection of impending system instability and to alert system operator to take necessary actions. Since a critical situation may be triggered in a system because of various reasons, a wide-area monitoring system needs to consider several practical factors while deploying phasor measurement units (PMUs) in the grid. This study proposes a systematic framework for analysing the suitability of limited candidate PMU locations with respect to multiple applications, which, in turn, would enhance the SA of the system operator. Five factors are chosen for assessing the potential of a PMU site viz., improving state estimation, assessing voltage, angular stability, monitoring tie-line oscillations and the availability of communication infrastructure. To quantify the contribution of each application in enhancing the SA, five respective factors are proposed. These five factors are finally integrated in the proposed framework using fuzzy technique for order of preference by similarity to ideal solution. The scope of this work, however, is not limited only to these five factors. PMU locations can be evaluated for any number of practical criteria. The proposed scheme is demonstrated on IEEE 14-bus system and Northern Regional Power Grid 246-bus Indian system. The proposed methodology enhances the SA by ranking and recognising the potential PMU locations, and placing them in a phased manner.

This study proposes a robust technique for accurate estimation of single-phase grid voltage fundamental amplitude and frequency. The technique relies on a quadrature signal generator (QSG) based on a fixed frequency tuned second-order generalised integrator (SOGI) and an infinite-impulse-response differentiation filter (DF). The DF is used to estimate the fundamental frequency from the instantaneous phase angle obtained from the generated orthogonal voltage waveforms. The estimation technique is robust and offers an easy tuning process as there is no interdependent loop between the orthogonal voltage system and the frequency estimation. Additionally, the technique is computationally efficient and can also reject the negative effects caused by the direct current offset and harmonics. Furthermore, the frequency estimation is less sensitive to harmonics when compared with a similar technique relying on the QSG based on the fixed frequency tuned SOGI and least-squares method. Simulation and real-time experimental results are provided to validate the robustness of the proposed technique.

The diesel-photovoltaic (PV) based hybrid AC microgrid systems with conventional control philosophies deliver very good performance in the grid connected mode. However, once the microgrid is isolated from the main grid the same philosophies which control the PV at its maximum power can make the microgrid unstable. In this connection, this study proposes a novel neuro-fuzzy controller to ensure the smooth transition of microgrid from grid connected mode to isolated mode, to retain the system stability even in isolated mode and to deliver the superior performance in grid connected mode as well. The considered artificial neural networks is trained with P _MPP –Temp against V _MPP characteristic, first of its kind. The fuzzy part of the controller derives the reference voltages subjected to the limits provided by the ANN. This study describes how well the data analytics can be utilised to retain the power system stability in emergencies. The proposed controller has been evaluated under different operating conditions and is exhibiting superior performance in achieving the desired control objectives. Results from the numerical simulations are confirmed from the experiments in real-time environment.