计及风速风向时空特征和三维混合地形影响的风电场并网系统可靠性评估和优化研究

The power outage event of Texas power system on February 26 indicates that spatial-temporal characteristics of wind speed and direction could create a considerable impact on power system reliability. Moreover, the wind farm are usually across a mixture of terrains, i.e., plains, hills, coasts, etc., which further aggravates the importance of the spatial-temporal characteristics of wind speed and direction..Aimed at the current trend of large-scale and centralized wind energy utilization in China, this project focuses on the problems of spatial-temporal characteristics of wind speed and direction and wind farm mixture terrains in reliability evaluation and optimization. The research is going to be further extended from the applicant’s existing journal papers in the area of reliability evaluation and optimization of wind farm integrated power system..This project reveals the spatial-temporal correlation, gustiness, and stochasticity of wind speed and direction using scale division and feature extraction approach. A wind speed and direction simulation model is established considering these characteristics, providing adequate and accurate wind speed and direction samples for reliability evaluation. With wind farm contour line and GPS coordinates, this project constructs the three-dimensional mixture terrain of wind farm using mesh generation and terrain fitting approach. Such approach enables accurate consideration of three-dimensional mixture terrain’s influence on wind farm power output in reliability evaluation. This project develops an optimization model for levelized reliability benefit and cost of energy considering the temporal value of loss of energy expectation. The optimal planning solution is solved from such model using intelligent optimization algorithms. This project could provide theoretical and technical support for the reliability evaluation and optimization of wind farm integrated power systems.

美国德州电网“2.26”停电事件表明，风速风向时空特征会对电力系统可靠性造成较大影响，而风电场地形常由平原、丘陵、海岸等多类地形混合组成，加剧风速风向时空特征。.项目针对我国风能大规模、集中式开发的现状，聚焦可靠性评估和优化中面临的风速风向时空特征、风电场混合地形等难题，以申请人已取得的风电场并网系统可靠性评估和优化方面论文成果为基础展开研究。.项目通过尺度划分和特征提取方式，揭示风速风向时空相关性、短期持续性和随机性特征，建立计及这些特征的风速风向仿真模型，为可靠性评估提供充足和准确的风速风向样本；根据风电场等高线和GPS坐标，通过网格划分和地形拟合方式，构建三维混合地形风电场，在可靠性评估中准确考虑三维混合地形对风电场出力的影响；计及期望失电量的时间价值，构建单位发电量可靠性效益与成本优化模型，根据智能优化算法求解最优规划方案。项目可为风电场并网系统可靠性评估和优化提供理论和技术支撑。

随着化石能源的加速枯竭和环境问题的日益加剧，风电场等可再生能源电厂在电力系统中的渗透率逐年增大。但风电功率受风况时空特性影响而呈现较高不确定性，为含风能电力系统的可靠性评估和优化提出严峻挑战，其中，发电系统充裕度是电力系统可靠性的重要组成部分。因此，本项目通过研究更精准的风速仿真模型和风速概率分布模型，进而计及风况时空特征。将这些模型嵌入时序Monte Carlo模拟法中，提出计及风况时空特征的含风能发电系统充裕度评估方法，为含风能发电系统的最优规划提供量化决策依据。.为在任意时间步长下仿真风速样本，本项目研究基于互转换Ornstein–Uhlenbeck(OU)过程风速仿真模型，应用OU过程为仿真风速样本设定仿真时间步长，克服实测风速样本对仿真时间步长的制约，应用互转换操作确保仿真风速样本服从与实测风速样本相似的参数型分布，并保留相似的风速自相关特性。将基于互转换OU过程风速仿真模型与时序Monte Carlo模拟法结合，提出仿真时间步长可变的含风能发电系统充裕度评估方法，评估任意仿真时间步长下的期望失电频率、期望失电量和期望失电持续时间指标，揭示仿真时间步长与三类指标间的灵敏度关系，为设定合适仿真时间步长提供依据。为更准确拟合风速概率分布，本项目引入Maxwell(MAX)分布和Power Maxwell(P-MAX)分布用于风速概率分布拟合，并基于最大似然法、矩估计法和最小二乘法求取MAX分布和P-MAX分布参数。为计及风速日特性和季特性，本项目研究两阶段风速仿真模型，第一阶段应用24小时联合风速概率分布计及风速日特性，第二阶段应用最优季度系数计及风速季特性，再提出计及风速日特性和季特性的风速仿真算法。将两阶段风速仿真模型与时序Monte Carlo模拟法结合，提出计及风速日特性和季特性的含风能发电系统季度充裕度评估方法，评估季度期望失电频率、季度期望失电量和季度期望失电持续时间指标，揭示风速季特性对含风能发电系统季度充裕度指标的影响。.通过研究更精确的风速仿真模型和风速概率分布模型，并将其与含风能发电系统充裕度评估结合，将有利于提高含风能发电系统充裕度评估精度，为含风能发电系统的最优规划提供量化决策依据，以较低的经济成本提升发电系统充裕度。

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