Earlier protection methods mainly focused on using communication channels to transmit trip signals between the protective devices (PDs), with no solutions provided in the case of communication failure. Therefore, this paper introduces a dual-layer protection system to ensure secure protection against fault events in the Distribution Systems (DSs), particularly in light of communication failures. The initial layer uses the Total Harmonic Distortion (THD), the estimates of the amplitude voltages, and the zero-sequence grid voltage components, functioning as a fault sensor, to formulate an adaptive algorithm based on a Finite State Machine (FSM) for the detection and isolation of faults within the grid. This layer primarily relies on communication protocols for effective coordination. A Second-Order Generalized Integrator (SOGI) expedites the derivation of the estimated variables, ensuring fast detection with minimal computational overhead. The second layer uses the behavior of the positive- and negative-sequence components of the grid voltages during fault events to locate and isolate these faults. In the event that the first layer exposes a communication failure, the second layer will automatically be activated to ensure secure protection as it operates, using the local information of the Protective devices (PDs), without the need for communication channels to transmit trip signals between the PDs. The proposed protection system has been assessed using simulations with MATLAB/Simulink and providing experimental results considering an IEEE 9-bus standard radial system. The obtained results confirm the capability of the system for identifying and isolating different types of faults, varying conditions, and modifications to the grid configuration. The results show good behavior of the initial THD-based layer, with fast time responses ranging from 6 to 8.5 ms in all the examined scenarios. In contrast, the sequence-based layer exhibits a protection time response of approximately 150 ms, making it a viable backup option in the event of a communication failure.

The integration of Distributed Generators (DGs) into distribution systems (DSs) leads to more reliable and efficient power delivery for customers. However, the possibility of bi-directional power flow creates new technical problems for protection schemes. This poses a threat to conventional strategies because the relay settings have to be adjusted depending on the network topology and operational mode. As a solution, it is important to develop novel fault protection techniques to ensure reliable protection and avoid unnecessary tripping. In this regard, Total Harmonic Distortion (THD) can be used as a key parameter for evaluating the grid\'s waveform quality during fault events. This paper presents a comparison between two DS protection strategies that employ THD levels, estimated amplitude voltages, and zero-sequence components as instantaneous indicators during the faults that function as a kind of fault sensor to detect, identify, and isolate faults. The first method uses a Multiple Second Order Generalized Integrator (MSOGI) to obtain the estimated variables, whereas the second method uses a single SOGI for the same purpose (SOGI-THD). Both methods rely on communication lines between protective devices (PDs) to facilitate coordinated protection. The effectiveness of these methods is assessed by using simulations in MATLAB/Simulink considering various factors such as different types of faults and DG penetrations, different fault resistances and fault locations in the proposed network. Moreover, the performance of these methods is compared with conventional overcurrent and differential protections. The results show that the SOGI-THD method is highly effective in detecting and isolating faults with a time interval of 6-8.5 ms using only three SOGIs while requiring only 447 processor cycles for execution. In comparison to other protection methods, the SOGI-THD method exhibits a faster response time and a lower computational burden. Furthermore, the SOGI-THD method is robust to harmonic distortion, as it considers pre-existing harmonic content before the fault and avoids interference with the fault detection process.

One of the most critical concerns in power system reliability is the timely and accurate detection of transmission line faults. Therefore, accurate detection and localisation of these faults are necessary to avert system collapse. This paper focuses on using Artificial Neural Networks in faults detection and localisation to attain accuracy, precision and speed of execution. A 330 kV, 500 km three-phase transmission line was modelled to extract faulty current and voltage data from the line. The Artificial Neural Network technique was used to train this data, and an accuracy of 100% was attained for fault detection and about 99.5% for fault localisation at different distances with 0.0017 μs of detection and an average error of 0%-0.5%. This model performs better than Support Vector Machine and Principal Component Analysis with a higher fault detection time. This proposed model serves as the basis for transmission line fault protection and management system.

The rapid growth of the distributed generators (DGs) integration into the distribution systems (DSs) creates new technical issues; conventional relay settings need to be updated depending on the network topology and operational mode as fault protection a major challenge. This emphasizes the need for new fault protection methods to ensure secure protection and prevent undesirable tripping. Total harmonic distortion (THD) is an important indicator for assessing the quality of the grid. Here, a new protection system based on the THD of the grid voltages is proposed to address fault events in the electrical distribution network. The proposed protection system combines the THD with the estimates of the amplitude voltages and the zero-sequence component for defining an algorithm based on a finite state machine (FSM) for the detection, identification, and isolation of faults in the grid. The algorithm employs communication lines between all the protective devices (PDs) of the system to transmit tripping signals, allowing PDs to be coordinated. A second order generalized integrator (SOGI) and multiple SOGI (MSOGI) are used to obtain the THDs, estimated amplitude voltages, and zero-sequence component, which allows for fast detection with a low computational burden. The protection algorithm performance is evaluated through simulations in MATLAB/Simulink and a comparative study is developed between the proposed protection method and a differential relay (DR) protection system. The proposed method shows its capability to detect and isolate faults during different fault types with different fault resistances in different locations in the proposed network. In all the tested scenarios, the detection time of the faults has been between 7-10 ms. Moreover, this method gave the best solution as it has a higher accuracy and faster response than the conventional DR protection system.

A novel fiber Bragg grating (FBG)-based passive sensor architecture, which can be used to protect the fiber cut and monitor the multiple sensors simultaneously, is proposed and experimentally demonstrated. Here, we employ a wavelength-tunable erbium-doped fiber (EDF) laser scheme with 25 km cavity length acting as the detecting light source in central office (CO). Each FBG sensor, serving as a feedback element, is used in proposed sensor architecture. By tuning the tunable bandpass filter (TBF) placing inside cavity to match the corresponding Bragg wavelength of FBG over the amplification bandwidth, we can retrieve the related wavelength lasing for the FBG sensing and monitoring simultaneously. Moreover, the survivability and capacity of the passive FBG sensor architecture can be also enhanced.