As more offshore wind energy projects are implemented, the risk of interactions between farms becomes more pronounced. While reduced surface roughness over water enhances airflow stability, it can also extend wake effects on downstream turbines. The study aims to enhance the understanding of wake interactions and efficiency variations based on the distance between neighboring farms. To assess the impact of neighboring farms across different scenarios and features, a methodology is developed to achieve computational optimality using an open-source Python-based library, PyWake, then verified by a well-established CFD software, Meteodyn. Then, the methodology is applied to a Brazilian offshore wind project currently under licensing as a reference point. The results indicate a 1–3% reduction in Annual Energy Production following the current Brazilian regulation for onshore projects of 20 times the blade tip height, as the minimum distance. This reduction translates to an approximate 3% increase in the Levelized Cost of Energy and a nearly 24% decrease in Net Present Value. These findings are crucial for offshore wind energy planning and its sustainable growth, indicating the need to define a minimum distance for the regulatory bodies. This would not only avoid future disputes but also enhance investor confidence.