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Lately, there has been major development in distributed energy resources (DERs) technologies due to the constraints on traditional power generation. However, due to the volatility of renewable power, the integration of this new type of generation in the existing network is highly problematic when a reliable planning is required. This paper investigates a stochastic planning model to minimise the lifecycle cost of distributed power generation (DG) and reduce power loss in transmission lines under the energy reliability criterion, namely the loss of load probability. In the proposed techniques, two stages are involved: the modelling of DERs stage and optimal placement and capacity of DG stage. Statistical moments including mean and variance are utilised to model the wind and solar power volatility and load uncertainty. Computer simulations based on MATLAB using multiobjective genetic algorithm (GA) are used to find the best siting and sizing of the DERs with multi-system constraints. A real section of the 66 kV transmission network of Mauritius is used to evaluate the optimization process. From the results it can be observed that the proper siting and sizing of DG are important to reduce total system cost and power loss in transmission lines while achieving a reliable planning method.