The nonlinear characteristics of a photovoltaic (PV) array, maximum power point tracking of the PV inverter, presence of blocking diodes, and lower irradiation prevent the conventional protection devices to trip under certain faults and lead to reduced system efficiency and fire hazards. Moreover, the PV characteristics under certain partial shading conditions are similar to that under fault conditions. Hence, it is imperative to detect faults and differentiate faults from the partial shading condition to avoid false tripping of the system. This paper proposes a simple fault detection method using the available data of array voltage and current by means of wavelet packets. The proposed scheme is simulated using MATLAB/Simulink and is experimentally tested on a 1.6-kW $\text{4}\,\times \,\text{4}$ PV array to validate its performance .

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.

In the present milieu, changes in regulations and the opening of power markets have manifested in the form of large amount of power transfer across transmission lines with frequent changes in loading conditions based on market price. Since conventional distance relays may consider power swing as a fault, tripping because of such malfunctioning would lead to serious consequences for power system stability. A frequency domain approach for digital relaying of transmission line faults mitigating the adverse effects of power swing on conventional distance relaying is presented. A wavelet-neuro-fuzzy combined approach for fault location is also presented. It is different from conventional algorithms that are based on deterministic computations on a well-defined model for transmission line protection. The wavelet transform captures the dynamic characteristics of fault signals using wavelet multi-resolution analysis (MRA) coefficients. The fuzzy inference system (FIS) and the adaptive-neuro-fuzzy inference system (ANFIS) are both used to extract important features from wavelet MRA coefficients and thereby to reach conclusions regarding fault location. Computer simulations using MATLAB have been conducted for a 300 km, 400 kV line and results indicate that the proposed localisation algorithm is immune to effects of fault inception, angle and distance. The results contained here validate the superiority of the ANFIS approach over the FIS for fault location.

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.

The smart grid aims to improve the quality and reliability of power at the generation, transmission, and distribution levels. The transmission lines can be considered the arteries of the power system, as they carry power over long distances and are exposed to difficult terrain. Transmission line protection philosophy is undergoing a change of paradigm with the advent of digital relays and high-speed broadband communication with the global positioning system (GPS). This paper explores the possibility of transmission line protection for a multigenerator system using wavelet multiresolution analysis (MRA) and computational intelligence techniques in conjunction with GPS. The inputs for the wavelet transform are the synchronized currents measured from remote telemetry units (RTUs) using GPS technology on different buses. The smart location technique uses a wavelet MRA technique to extract the features of the transient current signals based on the harmonics generated at the instant of occurrence of faults due to the abrupt changes of currents in a three-phase transmission line. These extracted features, with such computational intelligence techniques as an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN), lead the grid toward smarter strategies for locating the fault distance. A comparative study establishes the superiority of ANFIS over ANNs for more accurate and reliable smart fault location. Furthermore, the efficacy of the proposed method is validated through a Monte Carlo simulation to incorporate the stochastic (random) nature of fault occurrence in a real-time transmission line. The most significant contribution of this paper is that the proposed smart location technique is immune to the effects of the fault inception angle (FIA), fault impedance, fault distance, and power angle. The results contained in this paper validate the use of the proposed algorithm for the real-time smart grid operation of transmission lines.