Nowadays, the DC distribution system has been suggested, as a replacement for the AC power distribution system with electric propulsion. This idea signifies a fresh approach of issuing energy for low-voltage installations. It can be used for any electrical application up to 20 MW and works at a nominal voltage of 1000 V DC. The DC distribution system is just an extension of the multiple DC links that previously available in all propulsion and thruster drives, which typically comprise more than 80% of the electrical power consumption on electric propulsion vessels. A fault detection and islanding scheme for DC grid connected PV system is presented in this paper. Unlike traditional ac distribution systems, protection has been challenging for dc systems. The goals of this paper are to classify and detect the fault in the PV system as well as DC grid and to isolate the faulted section so that the system keeps operating without disabling the entire system. The results show the measured values of power at PV panel and DC grid side under different fault condition, which indicates the type of fault that occurs in the system.

Albeit the government buoy up the penetration of renewable energy sources (RES) particularly solar photovoltaic (PV) system, the dependency on fossil fuels is still growing. The power generation using solar PV system may enhance when the enactment of solar PV system is improved. The faults occurred in the system is an important performance degradation factor. Incessant studies have been performed to identify and mitigate the faults. Currently, several smart techniques are utilized to identify the faults rapidly. In this study, Back Propagation Neural Network (BPNN) has been implemented to identify the faults. The output power get degraded when the faults happened in source side, Maximum Power Point Tracking (MPPT), DC-DC converter, rectifier and grid. The investigations has performed on 100 kW solar PV system using Matlab. The outcomes imply that the proposed method has detected the faults quickly, economically and effectively.

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The subarray antenna techniques are much focused for flexible beamforming in envisioned smart antenna applications. The aim of this subarray arrangement of antenna elements is greatly motivated by bandwidth enhancement and interference minimization in the upcoming 5G next generation networks infrastructure. The optimization is required for effective placement of nulls in the desired direction of interferes from known sensed and verified disturbance angles. In this three dimensional radiation pattern optimization, the number of phase shift elements and constructive values for pointing focused beam and destructive strength in the obstacles is crucial. In this paper we proposed a firefly algorithm for dynamic management of the radiation pattern. It is possible with the optimization of the weight parameters of the subarray antenna. From the given Direction of Arrival we investigate the possibilities of deep placing of nulls is simulated and analyzed with the antenna parameters.