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Islanding condition means the case of feeding the loads from any distributed generator (DG) with a complete disconnection of the utility grid at the point of common coupling. The main technical issue in DG integration with the primary grid is the islanding condition. Hence, islanding must be detected using an appropriate anti-islanding technique which is needed to be faster in terms of time detection and accuracy. This paper illustrates the phenomenon of islanding and the passive methods which are used for preventing it. The main contribution of this paper is to detect this phenomenon as fast and accurately as possible using the technique of rate of change of power (ROCOP) based on the terminal voltage (TV) (ROCOP-TV) of the Photovoltaic (PV) inverter. The results of the proposed technique have been studied through extensive simulations using the MATLAB/Simulink platform. The ROCOP-TV technique results are compared with various types of passive detection relays after synchronization between the grid side and PV side. Furthermore, the proposed technique was not only able to detect islanding at the instance of its occurrence but also can distinguish between islanding and regular grid faults. The simulation results illustrate the proposed scheme's effectiveness and flexibility based on the MATLAB/Simulink platform.

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This paper presents an adaptive fuzzy controller for a class of unknown nonlinear systems over network. The network-induced delays can degrade the performance of the networked control systems (NCSs) and also can destabilize the system. Moreover, the seriousness of the delay problem is aggravated when packet losses occur during a transmission of data. The proposed controller uses a filtered tracking error to cope the time-varying network-induced delays. It is also robust enough to cope some packet losses in the system. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions that appear in the tracking controller. Based on Lyapunov stability theory, the constructed controller is proved to be asymptotically stable. Stability of the adaptive fuzzy controller is guaranteed in the presence of bounded external disturbance, time-varying delays, and data packet dropouts. Simulated application of the inverted pendulum tracking illustrates the effectiveness of the proposed technique with comparative results.