In the context of Power Systems, scheduling maintenance activities is a recognized Non-deterministic Polynomial-time (NP) hard optimization problem. This complexity stems from the dynamic nature of Power Systems and the varied conditions and anomalies within them. When wind energy is integrated into the system through the presence of offshore wind farms and is composed of a large volume of small units, the challenges become even more remarkable due to the uncertainties introduced by wind variability and the need to coordinate a high volume of maintenance activities for all small individual units with precise manner. This paper tackles this complex optimization issue using a probabilistic-focused twin model that addresses uncertainties and enumeration with scenario analysis based on simulations. The proposed solution quantifies and optimizes a probabilistic indicator and demonstrates feasible heuristic optimization algorithms that balance computation time and accuracy, delivering reliable performance within the given scenario.