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Loads and distributed generation production can be modeled as random variables. This paper shows that the proposed method can be applied for the keeping of voltages within desired limits at all load buses of a distribution system with small-scale biomass based energy systems. To measure the performance of this distribution system, this work has formulated a probabilistic model that considers the random nature of lower heat value of biomass and load. The Cornish-Fisher expansion is employed for estimating quantiles of a random variable. This paper proposes a new method that utilizes discrete particle swarm optimization and probabilistic radial load flow. It is evidenced the reduction in computation time accomplished by the more efficient probabilistic load flow in comparison to Monte Carlo simulation. Satisfactory solutions are reached in a smaller number of iterations. Hence, convergence is rapidly attained and computational cost is low enough than that required for Monte Carlo simulation.