Probabilistic optimal allocation of biomass fueled gas engine in unbalanced radial systems with metaheuristic techniques

• Improvement for the optimal siting and sizing of distributed generation.
• This paper presents a probabilistic three phase load flow in radial distribution networks.
• The model takes into account the random nature of lower heat value of biomass.
• A shuffled frog-leaping algorithm and probabilistic load flow are used.
• Acceptable solutions are reached in a small number of iterations.

This paper shows that in order to solve a probabilistic three phase load flow in radial distribution networks, it is necessary to apply effective techniques that take into account their technical constraints. Among these constraints, voltage regulation is one of the principal problems to be addressed in distributed generation. To evaluate the performance of this distribution system, this paper has developed a probabilistic model that takes into account the random nature of lower heat value of biomass and load. This paper applies a new method utilizing shuffled frog-leaping algorithm and three phase probabilistic load flow combined with the Monte Carlo method to solve this problem. The proposed method determines the nodes where biomass fueled gas engines are connected and their mean power output in order to minimize the voltage unbalances at the nodes.Acceptable solutions are reached in a small number of iterations. Results prove that the proposed method can be applied for the keeping of voltages within desired limits at all load buses of a distribution system with biomass fueled gas engines. Numerical applications are presented and considered regarding the unbalanced distribution system IEEE 13-nodes. The results obtained show the decrease of the unbalance factor due to the presence of distributed generation.