Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs

Abstract

The cheap and reliable primal energy source for BESS refueling necessitates a special attention for combining RERs with 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 LV VSC-based microgrids by exploiting SVMs. The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the PCC, namely RMS value of voltage and current (RM SV , RM SI ), THD of voltage and current (T HDV , T HDI ), frequency (f ), and also active and reactive powers (P , Q). This approach is based on passive monitoring and therefore, it does not affect the 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 DGs at the same PCC. Simulations based on the model and parameters of a real-life practical PV 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.

A novel hybrid downsampling and optimized random forest approach for islanding detection and non‐islanding power quality events classification in distributed generation integrated system

“…It has been tested for 100 disturbance cases each in different noisy scenario and the average detection times are illustrated in Table 9. In terms of detection time, the efficacy of DEMD-ORFA technique is found to be better than a recent publication [32] that uses SVM for islanding detection.…”

Novel hybrid signal processing approach based on empirical mode decomposition and multiscale mathematical morphology for islanding detection in distributed generation system

“…The demerit of technique is, it is only tested with a single PV‐based system and decision tree suffers from biased output results. In [42] recently support vector machine (SVM) proposed to detect islanding in a PV‐based microgrid with 40 ms, but SVM ask for a greater number of parameter settings which makes the classifier difficult to design. In [43] an active ROCOF relay has been proposed which reduces NDZ to zero but not tested in fault and capacitor switching events.…”

A Support Vector Machine Learning-Based Protection Technique for MT-HVDC Systems

“…Although this technique differs from ANN, some authors sometimes declare SVM as a special type of ANN [46,47]. A rigorous mathematical and statistical approach is employed for the development of SVM [48][49][50][51][52][53]. Both binary and multi-class classification problems are the root cause of the development of its mechanism.…”