1.上海电力大学 海上风电研究院,上海 200090
2.上海电力大学 人工智能学部,上海 200090
杨昕荧(2001),女,硕士研究生,研究方向为海上风电并网运行控制技术。
苏向敬(1984),男,博士,光明学者特聘教授,研究方向为海上风电大数据技术、主动配电网优化规划运行。
收稿:2026-01-29,
修回:2026-03-29,
纸质出版:2026-09-25
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杨昕荧,苏向敬,于帅等.考虑台风影响的海上风电柔直并网系统短期可靠性评估[J].浙江电力,2026,45(09):24-35.
YANG Xinying,SU Xiangjing,YU Shuai,et al.Short-term reliability assessment for VSC-HVDC systems integrating offshore wind power under typhoon impacts[J].ZHEJIANG ELECTRIC POWER,2026,45(09):24-35.
杨昕荧,苏向敬,于帅等.考虑台风影响的海上风电柔直并网系统短期可靠性评估[J].浙江电力,2026,45(09):24-35. DOI: 10.19585/j.zjdl.202609003.
YANG Xinying,SU Xiangjing,YU Shuai,et al.Short-term reliability assessment for VSC-HVDC systems integrating offshore wind power under typhoon impacts[J].ZHEJIANG ELECTRIC POWER,2026,45(09):24-35. DOI: 10.19585/j.zjdl.202609003.
针对海上风电柔直并网系统面临的台风威胁及实时评估需求,提出一种综合考虑外部台风天气与内部设备状态的短期可靠性评估框架。首先,建立计及台风演变的风电场时变故障率与出力模型,确定并网系统的动态功率边界;其次,构建涵盖升压站、海缆及MMC(模块化多电平换流器)的系统级整体模型,以克服局部建模忽略故障联动的缺陷;再次,为缓解高可靠性并网系统短期评估中低概率故障状态难以抽取所带来的计算瓶颈,引入交叉熵重要性抽样加速序贯蒙特卡罗求解。最后,算例分析表明,所提模型能合理量化台风与设备状态对系统可靠性的影响,在保证评估精度的同时,计算效率较传统方法显著提升。
To address the challenges posed by typhoon impacts and the need for real-time reliability assessment for voltage source converter based high voltage direct current (VSC-HVDC) systems integrating offshore wind power, this paper proposes a short-term reliability assessment framework that jointly considers external typhoon conditions and internal equipment states. First, a time-varying failure rate and power output model for wind farms considering typhoon evolution is developed to determine the dynamic operating boundaries of the VSC-HVDC systems. Then, a system-level holistic model incorporating step-up substations, submarine cables, and modular multilevel converters (MMCs) is established to capture the coupled failure mechanisms that cannot be represented by component-level models. Furthermore, to alleviate the computational bottleneck arising from the difficulty of sampling low-probability fault states in short-term assessments of highly reliable systems, a cross-entropy-based importance sampling method is integrated with sequential Monte Carlo simulation. Case studies demonstrate that the proposed framework effectively quantifies the impacts of typhoon conditions and equipment states on system reliability while significantly improving computational efficiency over conventional methods without sacrificing assessment accuracy.
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