With large proportion and high permeability of wind power integrated into the grid, the lack of inertia of the traditional wind turbine leads to weakening the system regulation capacity. The introduction of virtual inertia control can improve the inertia and frequency level of the system to a certain extent. However, when large-scale of wind turbines containing virtual inertia control are connected to the grid, they are inevitably electromechanically coupled with other synchronous machines. Furthermore, the power angle attenuation characteristic of the synchronous generator could be deteriorated, which poses a serious threat to the safe and stable operation of power grid. Based on the stochastic dynamic model of wind power integrated system, the project is aimed to propose a decoupling analysis method, analyze the influence of control links on oscillation mode, and explore the network system oscillation mechanism. Through analysis of energy spectrum, the project is intended to reveal the transmission characteristics of the energy flow and realize the online location of oscillation source on the system level. Through the establishment of the transfer function of the energy microelement in the internal control system of the wind turbine, the mapping relationship between the control parameters and the energy microelement of the generator terminal is analyzed to realize online identification of key factors on the equipment level. On this basis, the stochastic stability index is established by means of energy probability analysis. With the aim of optimal stochastic stability index, the project constructs the optimal adjustment model of system parameters, investigates corresponding online adjustment strategy, and develops a prototype concentrating on oscillation source tracking and parameter adjustment. The outcome of the project is to ensure the angle stability of power system and provide frequency support. The ultimate goal of the project is to enhance the safe and stable capability of large-scale wind power integrated system with virtual inertia.
大比例高渗透率的风电接入电网后,其自身惯性的缺失将导致系统调节能力弱化。虚拟惯量的引入虽可在一定程度上改善系统的惯量和频率特性,然而,此类风机大规模并网,将不可避免地与其他同步机产生机电耦合,甚至可能恶化同步机间功角衰减特性,严重威胁电网安全稳定运行。为此,本项目以构建风电并网系统随机动力学模型为突破口,提出解耦分析方法,剖析各控制环节对振荡模式影响,探寻并网系统振荡机理;通过能量频谱分析,揭示能量流传变特性,实现系统级振荡源在线定位;通过建立风机内部控制系统中能量微元的传递函数,剖析传递函数中控制参数与机端能量微元之间的映射关系,实现设备级关键因素在线辨识;在此基础上,借助能量概率分析,建立随机稳定度指标,并以该指标最优为目标,构建系统参数优化模型,制定相应的在线调整策略,研发振荡源追踪及参数调整样机。在提供频率支撑的同时,保障系统功角稳定,提升含虚拟惯量的风电并网系统安全稳定运行能力。
大比例高渗透率的风电接入电网后,其自身惯性的缺失将导致系统调节能力弱化。虚拟惯量的引入虽可在一定程度上改善系统的惯量和频率特性,然而,此类风机大规模并网,将不可避免地与其他同步机产生机电耦合,甚至可能恶化同步机间功角衰减特性,严重威胁电网安全稳定运行。为此,本项目以构建风电并网系统动态能量模型为突破口,基于时间常数分析,构建了含虚拟惯量的大规模风电并网系统降阶模型,并在此基础上,推导了计及虚拟惯量、锁相环等控制环节的单机动态能量函数;进一步,考虑风场内多台机组控制参数、运行状态等因素差异的影响,建立了机电暂态时间尺度下的风电场并网系统详细动态能量模型。结合耗散能量在单机控制环节中以及场级机组间的流通路径,揭示了风电并网系统模型中各环节之间的耦合关联关系,剖析了各控制环节对振荡模式影响,阐明了风电并网系统振荡产生的机理。在机理分析基础上,追踪系统级振荡源,求取网侧关键线路及源端的耗散能量,并描绘其能量频谱,通过构造各机组端口能量频谱相似度函数,追溯主导模态下的系统级振荡源。在设备级关键因素辨识方面,建立各控制环节动态能量函数并探寻其在控制系统中的传导路径,描绘能量在控制环节中的因果传导过程,追踪关键控制环节,并据此辨识设备级关键影响因素。在理论分析基础上,计及不确定性因素影响,利用鲁棒随机稳定判据,设计含虚拟惯量的风电并网系统随机稳定分析方法,并基于耗散能量与临界势能之间的关联关系,构建大规模风电并网系统能量稳定域,实现系统稳定性的在线评估。进一步,结合能量传导路径,在关键控制环节中设计能量补偿支路,兼顾频率响应需求,构建多支路能量补偿及参数优化方案,在提供频率支撑的同时,保障系统功角稳定,提升含虚拟惯量的风电并网系统安全稳定运行能力。
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数据更新时间:2023-05-31
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