A distributed power generating system can run in an off-grid or off grid mode and can be powered by either sustainable or nonrenewable energy sources. The widespread use of renewable energy sources, like grid-connected solar systems, presents distribution networks with additional technological difficulties, such as accidental islanding. Utility employees who are islanding may not be aware that a circuit is still energized, which might be harmful. On islanding detection in gird-connected PV systems, several proposed solutions were considered. In order to examine their current limits, this study aims to develop an islanding detection system for grid connected solar systems under various fault conditions using intelligent detection method (IDM). To use and monitor the many grid-connected PV system characteristics in this context, numerous sensors and controllers were proposed. The controller will carry out the islanding detection based on the sensor data’s categorization of defect. The circuit breaker will do the islanding, and an intelligent technique has been proposed to identify the islanding condition under different fault condition. For real-time realization, a 1 kW grid-connected solar system had been used, and an artificial neural network (ANN) was employed as a smart approach to identify the islanding mode under various fault conditions.