大规模风电并网对电力系统概率稳定性影响及有效控制措施研究

Power system stability level is decreased by bulk wind power integration. By assuming the wind farms as stochastic power and ignoring their dynamic control characteristics, the operational transient risk of wind power system can not be exactly quantified. With different initial states, failure modes, and time scales, the control measures, equivalence models, and corresponding stability problems are different. The wind turbine generators can not be aggregated with the coherency method for the rotor speed. The probabilistic small-disturbance stability are dependent on the initial operation point. Unexpected outage and emergency control change the number of the state variables, and add difficulty to the probabilistic stability evaluation...Including the uncertainty of initial states, failure modes, control strategies, topology constructions, and time scales, the probabilistic dynamic equivalence model is proposed for wind farms based on mathematical model aggregation and oscillation mode reduction. The dependence of probabilistic small-disturbance stability of on the initial operation points is studied. The sensitivities of the damping and oscillating characteristics to the configuration parameters and control parameters are quantified. The probabilistic transient stability algorithm is described by multi-variable energy function and stochastic differential equations. The adaptive preventive and emergency control measures are studied. The probabilistic transient stability evaluation algorithm and indices are proposed. The instability risk is decomposed to the wind-turbine generators, the synchronous generators, and the transmission system, and the enhancement measures to improve the probabilistic stability of wind power systems are proposed.

大规模风电并网降低了电力系统稳定性。将风电简化为随机功率，忽略动态控制特性，不能准确反映风电系统暂态运行风险。不同运行场景、故障模式和时间尺度下，风电系统控制策略、等值模型、对应稳定问题不同。风电机组不能采用转速同调方法聚合。风电系统概率小扰动稳定性，随初始运行点变化。大扰动后机组停运和紧急控制，将改变状态变量维数，增加概率稳定分析难度。.计及初始运行点、故障模式、控制策略和拓扑结构不确定性以及时间尺度不同，采用数学模型聚合和振荡模式降阶方法，建立风电场概率动态等值模型。研究风电系统小扰动概率稳定性对运行点的依赖性，量化衰减特性和振荡特性对结构参数和控制参数的灵敏度。建立多参数能量函数和随机微分方程算法，判定风电系统概率暂态稳定性。研究风电系统预防控制和紧急控制的自适应整定算法。建立风电系统概率稳定评估算法和指标体系。将失稳风险分解至风电机组、同步机组和电网，提出改善风电系统概率稳定性的措

风电并网比例逐年增加，影响电力系统安全运行，有可能降低系统稳定性。风电机组结构、功能和控制特性，与传统水电、火电等同步电机不同，且不同类型风电机组间差异也较大。不同运行场景、故障模式和时间尺度下，风电系统控制策略不同。.建立详细风电机组模型，而简化电网特性；或沿用传统电力系统分析算法，而简化表达风电机组，都不难实现，但是很难准确量化风电系统稳定特性和交互影响。采用详细建模后，需要审视风电系统分析控制算法适用性，以及现有结论有效性。.课题研究内容及创新点如下：.1．改进平电压启动算法，提出DFIG潮流算法和无功范围解析表达。证明旋转电机潮流方程对应励磁磁链暂态，因此静态电压稳定降阶雅可比矩阵时不可降阶无功方程。提出L指标对节点负荷和变比灵敏度算法。.2．提出计及定子电压暂态的DFIG小扰动模型，定义DFIG引起低频振荡模式，建立风电系统多步求导特征值灵敏度算法。提出协同穿越所需PMSG台数的解析算法，提出SBR最小阻值解析算法。提出设备长期和短期可靠性灵敏度的解析算法。建立了风电调频和直流线路参与调频的参数设置算法。.3．计及撬棒动作、串联系统可用度算法误差，提出DFIG可靠性模型。针对分层等值建模，提出矩阵描述的改进F&D算法。当短期评估不满足状态合并条件时，提出基于SMP的暂态状态合并算法。提出电力系统可靠性指标对复杂设备底层元件可靠性参数灵敏度的解析算法。.上述研究，拓展了风电系统运行与控制算法，完善了电力系统分析控制理论基础。