Performance Assessment of DVR in a Solar-Wind Hybrid Renewable Energy Connected to Grid Using ANN

Abstract

AbstractThe accessibility of renewable energy (RE) resources is getting cheaper day by day using technological advancement and the connectivity with the conventional grid is very common nowadays. The hybrid power generation has been rising exponentially in order to meet the power demand. In such constraint, the distribution lines are becoming more complex to analyse the real-time operation when there is any disturbances occur. It not only initiate several power quality problem at industrial and utility consumer end but also disturbs the performance of the line. Therefore, study of performance assessment is important in a grid connected solar-wind hybrid renewable energy in the presence of dynamic voltage restorer (DVR). In this paper, DVR is connected to the grid under abnormal condition as the generation of solar-wind hybrid power varies from time to time. To access the system reliability and effectiveness of the scheme, different types of shunt fault cases are conducted with and without DVR. The result of this paper shows that during small transient disturbances or the fault cases, DVR helps to mitigate the sudden decrease of voltage magnitude by injecting the reactive power. The wind turbine (WT) and solar photovoltaic (PV) duo system when connected to the conventional grid (CG) should follow standard grid codes (GC). Further to validate the fault case, an attempt is considered using artificial neural network (ANN).KeywordsDynamic voltage restorer (DVR)Hybrid PV-WTFault assessmentGCANN