Increasing penetration of offshore renewable energy has highlighted the challenges posed by strong intermittency, output uncertainty, and insufficient utilization of marine energy resources. To address these issues, this study investigates an offshore multi-energy coupling system integrating wind, photovoltaic, tidal, and wave energy with flexible loads such as seawater desalination and hydrogen production. A coordinated two-stage optimization framework is proposed. In the planning stage, a joint operation–planning capacity configuration model is formulated to minimize the annualized system cost while determining the optimal sizes of generation units and energy storage. In the operational stage, a multi-time-scale rolling scheduling model combining day-ahead and intra-day optimization is developed to dynamically mitigate renewable output fluctuations and enhance system flexibility. Case studies verify that the proposed framework significantly improves renewable energy utilization, reducing the curtailment rate to 0.7%, while achieving stable and cost-effective operation. The results demonstrate the effectiveness of coordinated planning and rolling scheduling for future offshore integrated energy systems.

The horizontal-axis tidal turbine is a representative device for harnessing ocean tidal energy, and the structural optimization of its blades is crucial for enhancing the power capture efficiency. In this work, the twist and chord distributions of the blade are determined using an improved Blade Element Momentum (BEM) approach, in which tip and hub loss factors are employed to enhance the modeling accuracy, and these results are employed to construct a parametric model of the original rotor. Due to its simplified assumptions and inability to capture three-dimensional flow effects, computational fluid dynamics (CFD) simulations were carried out to evaluate the hydrodynamic performance and flow analysis of the designed rotor. Further, the orthogonal test method was used to optimize the hydraulic performance of the rotor. Three optimization parameters, namely hub diameter, airfoil type, and maximum airfoil thickness, were set with three levels. Based on the orthogonal design scheme, nine rotor configurations were generated, and their energy capture characteristics and flow fields were subsequently evaluated through numerical simulations. The analysis indicates that the choice of airfoil exerts the strongest impact on the rotor’s energy capture efficiency, while the influences of maximum airfoil thickness and hub diameter follow in descending order. Consequently, the optimized rotor adopts a NACA63-415 airfoil with a reduced maximum thickness of 0.9 T₀ and an intermediate hub diameter of 15%R, achieving a power coefficient of 0.445 at the design tip-speed ratio of 4, corresponding to a 3.08% improvement compared with the original design. Flow field analysis demonstrates that the optimized geometry promotes a more uniform spanwise pressure distribution and effectively suppresses flow separation, thereby enhancing the overall hydrodynamic efficiency.

The high-penetration integration of offshore renewable energy introduces significant challenges, including high volatility, randomness, and insufficient energy accommodation, which place higher demands on the planning and operation of offshore integrated energy systems. To address these issues, this paper proposes an offshore multi-energy coupled DC microgrid system integrating wind, photovoltaic, tidal current, and wave energy, together with flexible loads such as seawater desalination and power-to-hydrogen. A hybrid forecasting model based on EMD-PCA-LSTM is developed to improve prediction accuracy under uncertain conditions. On this basis, a two-stage optimization framework considering both economic efficiency and operational risk is established. At the planning level, a joint operation–planning model incorporating Conditional Value-at-Risk (CVaR) is formulated to determine the optimal capacity configuration by minimizing the total annualized cost and risk cost. At the operational level, a multi-time-scale rolling optimization model is constructed to enhance system adaptability under renewable fluctuations. Case study results demonstrate that the proposed method significantly improves renewable energy accommodation, reduces the curtailment rate to 0.7%, and effectively balances economic performance and operational stability. The proposed framework provides a practical and efficient approach for capacity allocation and optimal operation of offshore multi-energy coupled systems.