Steel is the material of choice for a large number and very diverse industrial applications. Surface qualities along with other properties are the most important quality parameters, particularly for flat-rolled steel products. Traditional manual surface inspection procedures are awfully inadequate to ensure guaranteed quality-free surface. To ensure stringent requirements of customers, automated vision-based steel surface inspection techniques have been found to be very effective and popular during the last two decades. Considering its importance, this paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills. It is observed that majority of research work has been undertaken for cold steel strip surfaces which is most sensitive to customers' requirements. Work on surface defect detection of hot strips and bars/rods has also shown signs of increase during the last 10 years. The review covers overall aspects of automatic steel surface defect detection and classification systems using vision-based techniques. Attentions have also been drawn to reported success rates along with issues related to real-time operational aspects.

The augmentation in electricity demand, power system privatization as well as efficacy of renewable resources has paved the way for power system companies and researchers to exploit the field of grid connected distributed generation (DG) and its issues, islanding being a dominant one. Several research works have been conducted to mitigate the issues of islanding detection (ID). In context of this, the paper gives a comprehensive review of islanding issues, standard test systems, criteria and shifting of research trends in islanding detection methods (IDMs). The significant contributions pertain to categorization of IDMs, evaluation of non-detection zone (NDZ) for each test system, disquisition on evolution and advancement of IDMs and its comparisons based on criteria such as NDZ, run on time, nuisance tripping percentage, applicability in multi DG system and implementation cost to draw out the strength and shortcomings of individual methods that will come to aid to the companies or researchers for establishing the applicability and appropriateness of such method for their concerned domain.

Rapid advancements pertaining to measurements and computational technology have brought a paradigm shift for operational architecture of power grids across the globe. Self-healing, a vital operational feature of emerging power grids, necessitates real-time identification and localisation of transmission line faults for the entire power network. This study proposes a novel support vector machine-based fault localisation methodology to precisely identify and localise all types of transmission line faults occurring at any location in the power grid based on phasor measurement unit (PMU) measurements. Detection of fault is achieved through PMU measurements only from a single generator bus for the entire grid. Bus associated with fault, faulty branch and location of fault in faulty branch are calculated using fast Fourier transform analysis of variations pertaining to equivalent voltage phasor angle (EVPA) and equivalent current phasor angle (ECPA). The proposed methodology has been validated through extensive case studies for Western System Coordinating Council (WSCC)-9 and IEEE-14 bus systems. The main contribution of the proposed methodology is that the fault location information can significantly contribute to system protection center for restoration of the line within shortest time span and initiate appropriate wide area control actions to maintain stability.

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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.

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