LIU Nan, DONG Xiaochong, SONG Yunzhen, et al. Temporal Super-resolution Offshore Wind Energy Resources Assessment Method Based on Flow Matching Model[J]. 2026, 46(18): 6597-6606.
DOI:
LIU Nan, DONG Xiaochong, SONG Yunzhen, et al. Temporal Super-resolution Offshore Wind Energy Resources Assessment Method Based on Flow Matching Model[J]. 2026, 46(18): 6597-6606.DOI: 10.13334/j.0258-8013.pcsee.252015.
Temporal Super-resolution Offshore Wind Energy Resources Assessment Method Based on Flow Matching Model
摘要
海上风电作为清洁能源的重要组成部分发展迅速,但在海上风能资源的开发过程中,受限于海洋气象监测手段不足及地球系统模式(earth system model,ESM)的计算复杂度,实现高时间分辨率、长时间尺度的海上风能资源评估存在挑战。针对该问题,该文提出一种时序流匹配模型,融合历史气象监测数据对ESM模拟数据进行偏差修正与时序分辨率提升。该方法采用微分方程建模低分辨率数据至高分辨率数据的连续变换路径,并拟合概率分布变换过程中的速度场,实现对目标数据分布的建模。算例选用ERA5再分析数据,结合海上气象浮标观测数据开展仿真验证。结果表明,所提方法能有效模拟亚小时级的风速波动特性,且能够刻画风能资源的不确定性,可为海上风能资源评估提供新的技术路径。
Abstract
Offshore wind power
as a key component of clean energy
has experienced rapid development in recent years. However
achieving high-temporal resolution and long-term assessments of offshore wind resources remains challenging due to limitations in marine meteorological monitoring capabilities and the high computational complexity of Earth System Model (ESM). To address this issue
this paper proposes a temporal flow matching model that integrates historical meteorological monitoring data to perform bias correction and temporal resolution enhancement on ESM simulations. The method employs differential equations to model the continuous transformation path from low-resolution to high-resolution data and fits the velocity field during the probability distribution transformation to characterize the target data distribution. Using ERA5 reanalysis data combined with offshore meteorological buoy observations for simulation and validation
the results demonstrate that the proposed method can effectively simulate sub-hourly wind speed fluctuations and capture the uncertainty in wind energy resources. This work provides a novel technical pathway for offshore wind resource assessment.
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Related Author
GE Xiaolin
REN Zixu
FU Yang
ZHANG Yiming
WEI Shurong
LIU Zongye
ZHAO Guoliang
HAN Bin
Related Institution
Engineering Research Center of the Ministry of Education for Offshore Wind Power Technology (Shanghai Electric Power University), Yangpu District
2 China Electric Power Research Institute, Haidian District
1 School of Electrical Engineering and Automation, Hefei University of Technology
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Changping District
College of Electrical Engineering,Shanghai University of Electric Power