Optimization of radial systems with biomass fueled gas engine from a metaheuristic and probabilistic point of view

Loads and distributed generation production are modeled as random variables. Distribution system with biomass fueled gas engines. Random nature of lower heat value of biomass and load. The Cornish–Fisher expansion is used for approximating quantiles of a random variable. Computational cost is low enough than that required for Monte Carlo simulation. This paper shows that the technical constraints must be considered in radial distribution networks, where the voltage regulation is one of the primary problems to be dealt in distributed generation systems based on biomass fueled engine. Loads and distributed generation production are modeled as random variables. 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. 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. The Cornish–Fisher expansion is used for approximating quantiles of a random variable. This work introduces a hybrid method that utilizes a new optimization method based on swarm intelligence and probabilistic radial load flow. It is demonstrated the reduction in computation time achieved by the more efficient probabilistic load flow in comparison to Monte Carlo simulation. Acceptable solutions are reached in a smaller number of iterations. Therefore, convergence is more rapidly attained and computational cost is significantly lower than that required for Monte Carlo methods.