Metaheuristic and probabilistic techniques for optimal allocation and size of biomass distributed generation in unbalanced radial systems

In this study, a method for solving a probabilistic three-phase power flow in radial distribution networks and taking into account the technical constraints of the system is presented. Regulation of voltage is one of the main problems to be taken into account in networks with distributed generation. The present study introduces a probabilistic model to determine the performance of the distribution system. This study considers the random nature of lower heating value of biomass and loads. This study presents a new hybrid technique combining the shuffled frog leaping algorithm with probabilistic three-phase power flow that is solved by Monte Carlo method. Feasible results are achieved in a few iterations. The results show that the proposed technique can be applied to keep the voltages within the limits specified at each node of a distribution network with biomass power plants. The outcomes are attained using the unbalanced distribution system IEEE-13 node and connecting biomass power plants at some nodes. This study shows that the power losses and voltage unbalance are reduced as a result of the inclusion of distributed generation.