The environmental concerns and related incentives for clean energy have prompted significant growth of renewable generation in the recent years. The distribution utilities are keen to integrate renewable resources into their distribution networks as one of the effective and viable planning options. The continuous improvement in power supply reliability with ever increasing loads is one of the major objectives for distribution utilities. For remote distribution feeders, the integration of distributed generation (DG) units could be a cost-effective solution for system reliability improvement. The DG units can be used as an alternative power supply in case the supply from substation is unavailable due to system faults. The planned islanding operation of DG units can shorten the interruption duration for some of the customers during faults, thus improving the overall system reliability. Traditionally, the conventional DG units such as diesel generators are used as a backup supply for islanding operation. The capacity of conventional DG units can be fully utilised regardless of the time when a fault occurs. In comparison with the conventional DG units, the uncertainties in the availability of power from renewable DG units may have different impacts on system reliability. Therefore, it is important to assess the impacts associated with uncertainties of such generation systems and quantify system reliability benefits on the addition of renewable DG systems. This paper presents an investigation of the distribution network reliability by taking into account the random behaviour of multiple renewable DG units and varying load demand. The time sequential Monte Carlo simulation technique is employed to quantify the distribution network reliability improvement with renewable DG units. The probabilistic models built based on long-term realistic data are used to model the stochastic nature of wind and solar resources and the variation of load demand. The commonly used reliability indices such as System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) are analysed with different DG configurations and different DG capacity factors.