This article presents the Reliability Assessment (RA) of renewable energy interfaced Electrical Distribution System (EDS) considering the electrical loss minimization (ELM). ELM aims at minimizing the detrimental effect of real power and reactive power losses in the EDS. Some techniques, including integration of Renewable Energy Source (RES), network reconfiguration, and expansion planning, have been suggested in the literature for achieving ELM. The optimal RES integration (also referred to as Distributed Generation (DG)) is one of the globally accepted techniques to achieve minimization of electrical losses. Therefore, first, the locations to accommodate these DGs are obtained by implementing two indexes, namely Index-1 for single DG and Index-2 for multiple DGs. Second, a Constriction Factor-based Particle Swarm Optimization (CF-PSO) technique is applied to obtain an optimal sizing(s) of the DGs for achieving the ELM. Third, the RA of the EDS is performed using the optimal location(s) and sizing(s) of the RESs (i.e., Solar photovoltaic (SPV) and Wind Turbine Generator (WTG)). Moreover, a Battery Storage System (BSS) is also incorporated optimally with the RESs to further achieve the ELM and to improve the system’s reliability. The result analysis is performed by considering the power output rating of WTG-GE’s V162-5.6MW (IECS), SPV-Sunpower’s SPR-P5-545-UPP, and BSS-Freqcon’s BESS-3000 (i.e., Battery Energy Storage System 3000), which are provided by the corresponding manufacturers. According to the outcomes of the study, the results are found to be coherent with those obtained using other techniques that are available in the literature. These results are considered for the RA of the EDS. RA is further analyzed considering the uncertainties in reliability data of WTG and SPV, including the failure rate and the repair time. The RA of optimally placed DGs is performed by considering the electrical loss minimization. It is inferred that the reliability of the EDS improves by contemplating suitable reliability data of optimally integrated DGs.

The study of this work is to highlight the key metrics of various topologies in terms of output power, Fill Factor (FF), Mismatch Losses (ML) and efficiency. The idea behind this work is to analyze and obtain the performance of different topologies under various shading patterns. The major problem which comes across the path of Photovoltaic (PV) system performance is partial shading. The solution to this problem is to reconfigure the panels to achieve better results under shading conditions. For this, different configurations such as Series Parallel (SP), Total Cross Tied (TCT), Physical Relocation of Module with Fixed Electrical Connections (PRM-FEC), SuDoKu and Magic Square (MS) has been discussed, analyzed and compared using MATLAB/SIMULINK. Simulation approach is used to describe the working and evaluation of all configurations. By the results obtained, it is clearly visible that MS method have achieved largest output power of 2877 W, highest efficieny of 10.24 %, FF is 0.481 and lowest ML of 772 W among all the configurations under Long Narrow (LnN) pattern.

The paper presents the performance analysis‐based reliability estimation of a self‐excited induction generator (SEIG) using the Monte‐Carlo simulation (MCS) method with data obtained from a self‐excited induction motor operating as a generator. The global acceptance of a SEIG depends on its capability to improve the system's poor voltage regulation and frequency regulation. In the grid‐connected induction generator, the magnetizing current is drawn from the grid, making the grid weak. In contrast, in the SEIG stand‐alone operation, an external capacitor arrangement is implemented to render the reactive power support. This capacitor arrangement is connected across the stator terminals during the stand‐alone configuration of SEIG. The capacitor serves two purposes, which include voltage build‐up and power factor improvement. Therefore, the paper deals with obtaining the minimum capacitor value required for SEIG excitation in isolated mode applications, including stand‐alone wind power generation. The SEIG performance characteristics have been evaluated for different SEIG parameters. The simulation and experimental results are then compared and found satisfactory. Then, SEIG reliability is estimated considering the MCS method utilizing SEIG excitation's failure and success rates during experimental work in the laboratory. Finally, the SEIG reliability evaluation is performed considering different wind speeds.

This paper proposes an Improved Magnetic Circuit (IMC) model for the optimal design and characteristics evaluation of the Five-Phase Permanent Magnet Synchronous Generator (FP-PMSG) for wind power application. Along with the Finite Element Method (FEM), the IMC model is also preferred for its faster result generation capabilities. The proposed model is used for optimal designing and performance evaluation of FP-PMSG by considering parameters such as leakage fluxes, properties of core material for rotor and stator, properties of rotor permanent magnet sleeve material, effect of saturation and armature reaction. To compute the armature reaction flux, the winding function approach has been opted. Furthermore, extensive analysis is done with respect to different sleeve and core materials along with improvising various dimensional parameters like magnet height, Magnet to Magnet (M-M) gap and sleeve length for high quality performance of FP-PMSG. To validate the results obtained from IMC model and FEM, an experimental prototype is developed and the electromagnetic performances such as generated voltage, Percentage Total Harmonic Distortion (THD) of generated voltage, terminal voltage vs load current, generated Electromotive Force (EMF) vs speed, rectified Direct Current (DC) Voltage vs DC current, output DC Power vs load resistance and percentage (%) efficiency vs current are evaluated. Through fabrication of the prototype of FP-PMSG in the laboratory, a substantial amount of engineering values have been acquired.

This paper describes the controller design aspects of DFIG‐based wind turbine system (WTS) using gravitational search algorithm (GSA). The appropriate control schemes are required for efficient and reliable functioning of the DFIG‐based wind energy conversion system (WECS). The control algorithms are implemented in converters which are placed in the rotor end and grid side of the WECS. The controller design schemes are optimized for accurate, reliable and stable operations of WECS using GSA. The most commonly used other design techniques are bacterial foraging optimization (BFO), and particle swarm optimization (PSO). Moreover, the transfer function modeling of DFIG is also described in this paper. The results show that the proposed GSA technique with sixths order transfer function model of DFIG improves the transient performance including time of rising the response to 90%, settling time, and amplitude of peak overshoot. The proposed GSA technique is compared with the techniques already implemented in the previous research works including PSO and BFO. The DFIG‐based WTS's output waveforms of voltage at dc‐link, reactive power, and active power are improved using GSA based design technique. Finally, it is concluded that the GSA technique gives better results as compared with the PSO and BFO techniques.

This paper presents the design and development of an innovative device TRINETRA: A sensor based vision enhancement system for obstacle detection on railway tracks. The TRINETRA is termed as Technological Research and Innovation for National Empowerment of Trains to Reduce Accidents. The authors have developed a prototype of TRINETRA, which promises easy passage for trains in unknown environments such as zero visibility situations, fog, smog, and heavy rain. The prototype is based upon the integration of a camera, Radio Detection and Ranging (RADAR), and Infrared (IR) Light Amplification by Stimulated Emission of Radiation (LASER). The camera used in the prototype catches a long-range view of the track and presents it live on a mini screen fixed in the loco pilot cabin. A combined short, mid, and long-range radar sensor system is used to detect obstacles continuously in loco pilot blind spots on the track, particularly for collision avoidance assistance at high speed. The present work proposes a long-range laser IR illuminator with a wide range of color and mono cameras to aid clear and precise monitoring in zero visibility conditions, which is fixed on the front portion/engine of the locomotive/engine. The prototype experimental results for 2 m - 2 km distances have been performed on a live running train, which shows that the developed prototype tracks obstacles effectively during fog and smog conditions. The design concept, observation, prototype model, and other technical specifications have been presented, and satisfactory results were found.