This study proposes a novel fault feature extraction that could be used in fault detection and classification schemes for power system transmission lines, based on single-end measurements using time shift invariant property of a sinusoidal waveform. Various types of faults at different locations, fault resistance and fault inception angles on a 400 kV–361.65 km power system transmission line are investigated. The determinant function is used to extract distinctive fault features over various data window sizes namely, 1/4, 1/2 and a cycle of post-fault data. In addition, various delays were introduced before taking the post-fault measurements. The performance of the feature extraction scheme was tested on a machine intelligent platform WEKA by using three types of feature selection techniques: information gain, gain ratio and SVM. The result shows that, the determinant function defined over the phase current and neutral current is sufficient to classify ten types of short-circuit faults on doubly fed transmission lines; however, the scheme did not differentiate between 3 phase line faults (LLL) and 3 phase lines to ground faults (LLLG), the two types of faults are treated as the same type of fault, balanced fault. An accuracy between 95.95 and 100% is achieved.

The quasi-impedance source inverters/quasi-Z source inverters (Q-ZSIs) have shown improvement to overwhelmed shortcomings of regular voltage-source inverters (VSIs) and current-source inverters (CSIs) in terms of efficiency and buck-boost type operations. The Q-ZSIs encapsulated several significant merits against conventional ZSIs, i.e., realized buck/boost, inversion and power conditioning in a single power stage with improved reliability. The conventional inverters have two major problems; voltage harmonics and boosting capability, which make it impossible to prefer for renewable generation and general-purpose applications such as drive acceleration. This work has proposed a Q-ZSI with five-level six switches coupled inverter. The proposed Q-ZSI has the merits of operation, reduced passive components, higher voltage boosting capability and high efficiency. The modified space vector pulse width modulation (PWM) developed to achieve the desired control on the impedance network and inverter switching states. The proposed PWM integrates the boosting and regular inverter switching state within one sampling period. The PWM has merits such as reduction of coupled inductor size, total harmonic reduction with enhancing of the fundamental voltage profile. In comparison with other multilevel inverters (MLI), it utilizes only half of the power switch and a lower modulation index to attain higher voltage gain. The proposed inverter dealt with photovoltaic (PV) system for the stand-alone load. The proposed boost inverter topology, operating performance and control algorithm is theoretically investigated and validated through MATLAB/Simulink software and experimental upshots. The proposed topology is an attractive solution for the stand-alone and grid-connected system.

The majority of rail vehicles worldwide use diesel as a primary fuel source. Diesel engine carbon emissions harm the environment and human health. Although railway electrification can reduce emissions, it is not always the most economical option, especially on routes with low vehicle demand. As a result, interest in hydrogen-powered trains as a way to reduce greenhouse gas (GHG) emissions has steadily grown in recent years. In this paper, we discuss advancements made in hydrogen-powered freight and commuter trains, as well as the technology used in some aspects of hydrogen-powered vehicles. It was observed that hydrogen-powered trains are already in use in Europe and Asia, unlike most developing countries in Africa. Commuter trains have received most of the research and development (R&D) attention, but interest in hydrogen-powered freight trains has recently picked up momentum. Despite the availability and use of gray and blue hydrogen, green hydrogen is still the preferred fuel for decarbonizing the rail transport sector.

Electrical power grids are often susceptible to voltage instability and have been a growing concern. In this study, the authors propose techniques based on network response structural characteristics for voltage stability assessment and for the identification of important nodes in electrical power grids. First, the network response structural characteristic indices (NRSCIs) which are inherent in the conventional power grids in terms of the Kirchhoff matrix is formulated. The eigenvalue decomposition (ED) technique is then applied to a submatrix of the Kirchhoff matrix to determine the topological strength of the electrical network graph. The vertex (node) that has a minimum eigenvalue is taken as the critical mode, from which its contributions to the entire graph is identified using the proposed network response structural characteristics theory participation factor (NRSCTPF). To demonstrate the magnitude of the concept formulated, the known degree centrality is modified in terms of the established NRSCI, which are then used to determine the important nodes of the network graph. The results obtained show that the proposed NRSCTPF and the degree centrality based on the NRSCI can be used for voltage stability assessment and identification of important nodes. The proposed approach is also less computationally intensive compared with the traditional approach.