AI 中文总结
本研究针对深海多空间风-光-潮汐电站集电系统，构建全生命周期优化模型，提出自适应分段线性化方法简化求解，验证了多能互补及电缆配置的经济性，为相关规划提供实用框架。
AI 中文摘要
本文开发了深海同址能源农场（CEF）集电系统（CS）的全生命周期优化模型，其中同址能源涡轮机（CET）整合了海域各层的风能、光伏（PV）和潮流能资源。该模型捕捉多层海洋空间的互补性、尾流效应和输出变异性，同时适配多种动态海底电缆配置。为提高计算效率，提出了基于CET输出的自适应分段线性化（A-PWL）方法，将原始混合整数二次规划（MIQP）问题转化为混合整数线性规划（MILP）形式，以近似二次运营成本并简化潮流建模。案例研究表明，纳入多能互补可显著提升深海CEF的经济性能；当外部物理风险可忽略时，全悬挂式电缆配置比悬垂式设计更具成本效益；所提线性化方法在实现高精度的同时大幅缩短了求解时间。总体而言，本研究为海上可再生能源系统的高效CS规划提供了实用且可扩展的框架。
英文摘要
This paper develops a life-cycle optimization model for the collector system (CS) of deep-sea co-located energy farms (CEFs), where co-located energy turbines (CETs) integrate wind, photovoltaic (PV), and tidal current resources across sea-area layers. The model captures multi-layer marine-space complementarity, wake effects, and output variability, while accommodating diverse dynamic submarine cable configurations. To improve computational efficiency, the adaptive piecewise linearization (A-PWL) method based on the outputs of CETs is proposed to transform the original mixed-integer quadratic programming (MIQP) problem into a mixed-integer linear programming (MILP) form to approximate quadratic operation costs and simplify absolute power flow modeling. Case studies demonstrate that incorporating multi-energy complementarity significantly enhances the economic performance of deep-sea CEFs. When external physical risks are negligible, the fully-suspended cable configuration proves more cost-effective than the lazy-wave design. The proposed linearization method achieves high accuracy while significantly reducing solution time. Overall, this work provides a practical and scalable framework for efficient CS planning in offshore renewable energy systems.
Comments14 pages, 12 figures, and 6 tables. Accepted by CSEE Journal of Power and Energy Systems in August 2026
