Automation of Electric Power SystemsVol. 39, Issue 16, Pages: 23-28(2015)
作者机构:
沈阳工业大学电气工程学院,辽宁省,沈阳市,110870
作者简介:
基金信息:
DOI:
CLC:
Published:2015
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CUI Jia. [J]. Automation of electric power systems, 2015, 39(16): 23-28.
DOI:
CUI Jia. [J]. Automation of electric power systems, 2015, 39(16): 23-28.DOI:
基于单机最优功率曲线拟合的多场景风电功率预测方法
摘要
风的时变和间歇性制约风电与负荷的实时能量平衡
准确的功率预测有助于风能成为可调度能源。针对风电不确定性问题
提出了基于单机最优功率曲线拟合的多计算流体力学(CFD)场景风电功率预测方法。首先
离散求解大气物理运动方程
并建立能反映风电场流体分布的CFD加速比矩阵。其次
针对风轮旋转尾流效应
提出了参考风轮推力系数的自由与带有激盘模型流场的变权重CFD组合预测。最后
提出了一种利用经过尾流修正风电机组自身风速计数据的迭代风电功率曲线拟合方法
以贡献率为判断指标
迭代剔除坏点并拟合单机最优功率曲线。实际算例结果证明所提方法可以有效提高功率曲线拟合和预测精确度。
Abstract
Due to the wind power time-varying and intermittent characteristics
it is difficult to achieve real time energy balance in a power system. Hence
accurate and stable power forecast will make wind energy a schedulable energy. To deal with wind power uncertainties
a multi-scenario power forecasting method based on the optimal fitting wind power curve for single turbine is proposed. Firstly
atmospheric movement model is discretized using computational fluid dynamics (CFD) speedup matrix
which can reflect wind flow distribution accurately. Secondly
a new variable-weight CFD wind forecast combination method for each wind turbine is put forward considering rotor thrust coefficient of free flow field and wakes of actuator disc. Finally
a new site-specific optimal power curve fitting method is developed based on historical data of wind speed and power measured by wind turbine’s anemometers. The contribution rate is the basis of eliminating illegal points by use of iterative algorithm. The engineering applications show that the proposed method can effectively improve the accuracy of wind power curve fitting and forecasting.