Journal of Bionic Engineering (2024) 21:1522–1540https://doi.org/10.1007/s42235-024-00498-3

An Adaptive Strategy?incorporated Integer Genetic Algorithm for Wind Farm Layout Optimization

Tao Zheng1 · Haotian Li1 · Houtian He1 · Zhenyu Lei1 · Shangce Gao1 

1 Faculty of Engineering, University of Toyama, Toyama 9300887, Japan

Abstract

Energy issues have always been one of the most signifcant concerns for scientists worldwide. With the ongoing over exploitation and continued outbreaks of wars, traditional energy sources face the threat of depletion. Wind energy is a readily available and sustainable energy source. Wind farm layout optimization problem, through scientifcally arranging wind turbines, signifcantly enhances the efciency of harnessing wind energy. Meta-heuristic algorithms have been widely employed in wind farm layout optimization. This paper introduces an Adaptive strategy-incorporated Integer Genetic Algorithm, referred to as AIGA, for optimizing wind farm layout problems. The adaptive strategy dynamically adjusts the placement of wind turbines, leading to a substantial improvement in energy utilization efciency within the wind farm. In this study, AIGA is tested in four diferent wind conditions, alongside four other classical algorithms, to assess their energy conversion efciency within the wind farm. Experimental results demonstrate a notable advantage of AIGA.

Keywords Wind farm layout optimization problem · Meta-heuristic algorithms · Adaptive · Integer genetic algorithm