Comparison of Monte Carlo Simulation and Genetic Algorithm in Optimal Wind Farm Layout Design in Manjil Site based on Jensen Model

An optimal arrangement of turbines in wind farms is very important in order to achieve maximum energy at the lowest cost. In the present work, the use of Vestas V-47 wind turbine and uniform one-way wind in achieving the optimal arrangement of horizontal axis turbines in Manjil using the genetic and Monte Carlo algorithms is investigated. The Jensen model is used to simulate the wake effect on the downstream turbines. The objective function is considered as the ratio of cost to power of the power plant. The results obtained show that the Monte Carlo method compared to the genetic algorithm will give a better result. Under the same conditions, the Monte Carlo algorithm will give 29% and 40% better results in terms of the number of turbines and output power, respectively. In terms of optimization, in the Monte Carlo algorithm, its fitness value is 16% less than the genetic algorithm, which indicates its better optimization.

Automated summary

An optimal arrangement of turbines in wind farms is crucial for maximizing energy output at the lowest cost. In a study comparing genetic and Monte Carlo algorithms for turbine placement, it was found that the Monte Carlo method outperforms the genetic algorithm in terms of turbine quantity and output power. The results showed that the Monte Carlo algorithm provides a more efficient optimization with a 16% lower fitness value compared to the genetic algorithm.