Anti-Islanding Protection of PV-based Microgrids Consisting of PHEVs using SVMs

The cheap and reliable primal energy source for battery energy storage system (BESS) refueling necessitates a special attention for combining renewable energy resources with plug-in hybrid electric vehicle (PHEV) charging stations in microgrids. Rapid charging is an operation mode of PHEV for drivers which demands fast recharging of BESSs of the electric cars. This charging mode manifests as low impedance short circuit at dc side, making power transient on power grid side. This paper presents a new anti-islanding protection scheme for low-voltage-sourced converter-based microgrids by exploiting support vector machines (SVMs). The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the point of common coupling (PCC), namely, root-mean-square (RMS) value of voltage and current ( RMS_{V} , RMS_{I} ), total harmonic distortion (THD) of voltage and current ( THD_{V} , THD_{I} ), frequency ( f ), and also active and reactive powers ( P , Q ). This approach is based on passive monitoring and therefore, it does not affect the power quality (PQ). In order to cover as many situations as possible, minimize false tripping and remain selective, training, and detection procedures are simply introduced. Based on the presented sampling method and input model, the proposed method is tested under different conditions such as PHEV rapid charging, additional load change and multiple distributed generations at the same PCC. Simulations based on the model and parameters of a real-life practical photovoltaic power plant are performed in MATLAB/Simulink environment, and several tests are executed based on different scenarios and compared with previously reported techniques, this analysis proved the effectiveness, authenticity, selectivity, accuracy, and precision of the proposed method with allowable impact on PQ according to UL1741 standard, and its superiority over other methods.