A robust control scheme for optimized pitch angle estimation of offshore wind turbine under varied climatic conditions using Osprey algorithm

This study presents a data-driven framework for optimizing power generation control in hybrid power networks, with a particular focus on enhancing performance and mitigating frequency fluctuations in systems integrated with offshore wind energy. The increasing complexity of modern power grids, driven by the growing penetration of renewable energy sources, presents significant challenges in maintaining grid stability. Offshore wind farms, as key contributors to sustainable energy, are central to this research, which evaluates their operational efficiency within a multi-area network under varying offshore climatic conditions. At the heart of this approach is an advanced control strategy that combines precise pitch angle estimation with a fractional-order controller, optimized using the Osprey algorithm. The proposed methodology dynamically adjusts the pitch angle of wind turbine blades to maintain an optimal tip-speed ratio, maximizing power generation while minimizing blade stall and drag effects. This control mechanism enhances generation stability and facilitates the seamless integration of offshore wind energy into hybrid power grids. Utilizing pitch angle estimated control strategy, system performance got improved from 260.06 to 37.51. The results underscore the effectiveness of the proposed strategy in improving the overall efficiency, reliability, and resilience of offshore wind-enriched networks, offering scalable solutions to address the integration challenges of offshore wind farms. By optimizing power generation and grid stability, this study contributes to the development of more sustainable and robust energy infrastructures, supporting the global transition to a greener energy future.