<p>As Cognitive Radio Networks (CRNs) advance toward more adaptive and efficient spectrum management, energy sustainability remains a significant challenge. The integration of renewable energy sources, such as wind energy, offers a promising solution to power these networks in remote or energy-scarce environments. However, the intermittent nature of wind energy introduces complexities in balancing energy harvesting with the operational requirements of CRNs. This paper addresses the challenge of optimizing the duration of wind energy harvesting and sensing operations in CRNs. We propose an optimization framework that integrates wind energy dynamics with cognitive radio sensing needs to determine the optimal allocation of time between these two functions. By considering factors such as wind speed variability, energy storage characteristics, and sensing performance metrics, our approach aims to enhance the overall efficiency and effectiveness of wind-powered CRNs. Simulation results demonstrate the efficacy of the proposed strategies in improving energy utilization and network performance under various environmental conditions. This study provides a foundation for developing practical solutions to manage wind energy in CRNs, contributing to the advancement of sustainable and efficient wireless communication systems. We also optimize harvesting and sensing durations using wind and Reconfigurable Intelligent Surfaces (RIS).</p>