基于测量-关联-预测的大规模风电场风能资源动态评估研究

Wind energy resources are in great uncertainty due to the randomness of wind speed and spatial distribution of non-uniformity. A series of non-stationary wind data around the regional wind farm is chosen to be the object of study in this research project. A combined model and algorithm of regional wind energy resource assessment based on the measurement-correlation-Predict(MCP) will be developed based on the dynamic equivalent model of wind farm in multiple time scales. Concept of wind power potential(WPP) will be proposed as a measure of wind power generation capability of wind farms. Research into the basic law of regional wind energy resource assessment will be carried out with the change of the joint distribution of wind speed and wind direction. Spatial correlation coefficient matrix will be established to characterize the spatial and temporal characteristics of wind speeds between regional weather station and targeted wind farms. Thus, transformation procedure from wind speed to wind energy resources can be simulated by mathematical representation. Research reveals the basic law of wind energy resources over temporal/spatial variation. Calculation method is proposed to estimate the wind resource and analyze the uncertainty of the error. Possible scope of wind energy resource in a regional wind farm will be given as well. Basic Law of combination of wind power prediction and wind energy resource assessment will be explored in this project. This significantly turns uncertainty of wind power into predictability to some extent, thus helps to effectively reduce the wind farm’s randomness and negative impact on power grids. Research results will provide theoretical basis for large-scale wind power system planning, design and operation scheduling.

由于风速资源的随机性和空间分布的不均匀性, 造成风能资源具有极大的不确定性。本项目拟以区域风电场非平稳风电数据序列为研究对象，在建立区域风电场多时间尺度动态等值模型的基础上，研究建立基于测量-关联-预测（MCP）的区域风电场风能资源评估精细化的组合模型及算法；提出风能势概念作为衡量风电场发电能力的指标，研究风电场风能资源随风速风向的联合分布变化的基本规律；建立空间相关系数矩阵来表征区域性风电场气象站和目标风电场风速之间的时空关联特性，运用数学表征来模拟风速向风能资源的转化过程，揭示基于空间相关性的风能资源随时间/空间变化的基本规律，给出风电场风能资源估算方法，对误差作不确定性分析，给出风电场风能资源可能变化的范围，探索将风力发电功率预测和风能资源评估相结合的基本规律，可将风电的不确定性转化为量化的可预测性，降低风电对电网运行的影响，研究成果将为大规模风电系统规划、设计和运行提供理论依据。

随着风电的大规模发展，对风电场风能资源进行动态精细化的评估是建设风电场前期一项基础而重要工作。由于风速资源的随机性和空间分布的不均匀性, 造成风能资源具有极大的不确定性。本项目以区域风电场非平稳风电数据序列为研究对象，在建立区域风电场多时间尺度动态等值模型的基础上，研究建立基于测量-关联-预测（MCP）的区域风电场风能资源评估精细化的组合模型及算法；提出风能势概念作为衡量风电场发电能力的指标，研究风电场风能资源随风速风向的联合分布变化的基本规律；建立空间相关系数矩阵来表征区域性风电场气象站和目标风电场风速之间的时空关联特性，运用数学表征来模拟风速向风能资源的转化过程，揭示基于空间相关性的风能资源随时间/空间变化的基本规律，给出风电场风能资源估算方法，对误差作不确定性分析，给出风电场风能资源可能变化的范围，探索将风力发电功率预测和风能资源评估相结合的基本规律，可将风电的不确定性转化为量化的可预测性，降低风电对电网运行的影响，研究成果将为大规模风电系统规划、设计和运行提供理论依据。

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