Wind Farm Layout Optimization Based on ROA

Animals possess unique forms of wisdom. In recent years, scientists have increasingly favored methods for emulating animal behaviors to solve problems. Inspired by the unique reproductive behavior of Rhodeus Ocellatus (RO), which involves adaptive trade-off strategies while searching for clams, we proposed the Rhodeus Ocellatus Algorithm (ROA) to solve strongly nonlinear problems like wind farm layout optimization (WFLO). Experimental results indicate that ROA ranks first across all three CEC test suites. It outperforms other metaheuristic algorithms, demonstrating excellent robustness and the ability to find better solutions for strongly nonlinear problems. In real-life WFLO cases, the ROA significantly improves the annual energy performance (AEP) by 9.47% and reduces the levelized cost of electricity (LCOE) by 8.65% compared with the actual layout. The results also show that ROA ranks first as well in solving the WFLO problem.