Adaptation of the simulated evolution algorithm for wind farm layout optimization

Abstract

Wind energy is a potential replacement for traditional, fossil-fuel-based power generation sources. One important factor in the process of wind energy generation is to design of the optimal layout of a wind farm to harness maximum energy. This layout optimization is a complex, NP-hard optimization problem. Due to the sheer complexity of this layout design, intelligent algorithms, such as the ones from the domain of natural computing, are required. One such effective algorithm is the simulated evolution (SE) algorithm. This paper presents a simulated evolution algorithm engineered to solve the wind farm layout design (WFLD)optimization problem. In contrast to many non-deterministic algorithms, such as genetic algorithms and particle swarm optimization which operate on a population, the SE algorithm operates on a single solution, decreasing the computational time. Furthermore, the SE algorithm has only one parameter to tune as opposed to many algorithms that require tuning multiple parameters. A preliminary empirical study is done using data collected from a potential location in the northern region of Saudi Arabia. Experiments are carried out on a 10 × 10 grid with 15 and 20 turbines while considering turbines with a rated capacity of 1.5 MW. Results indicate that a simulated evolution algorithm is a viable option for the said problem.