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基于风电参与的含能量备用与虚拟惯量的频率约束调度
Frequency Constrained Dispatch With Energy Reserve and Virtual Inertia From Wind Turbines
| 作者 | Boyou Jiang · Chuangxin Guo · Zhe Chen |
| 期刊 | IEEE Transactions on Sustainable Energy |
| 出版日期 | 2025年1月 |
| 技术分类 | 风电变流技术 |
| 技术标签 | 储能系统 调峰调频 多物理场耦合 深度学习 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 风力发电机 能量储备 虚拟惯量 频率约束调度 随机优化模型 |
语言:
中文摘要
随着风电渗透率提高和常规机组逐步退役,风电机组(WTs)在提供稳态能量备用(ER)和频率支撑方面潜力显著。本文提出一种计及风电能量备用与虚拟惯量的频率约束调度新框架。建立了WT的ER与虚拟惯量模型,分别利用减载运行和转子动能作为能量来源;推导了考虑WT在频率谷值退出惯量响应的系统频率响应与机组功率动态;构建了以WT调频参数和转子转速为决策变量的随机优化频率约束调度模型,充分反映机械-电气耦合及暂态-稳态过程交互;采用凸包松弛、近似及深度神经网络将非线性模型转化为混合整数二阶锥规划模型。IEEE 118节点系统算例验证了所提模型与方法的有效性。
English Abstract
With the increasing penetration of wind power and gradual retirement of conventional generating units (CGUs), wind turbines (WTs) become promising resources to provide steady-state energy reserve (ER) and frequency support for the grid to facilitate supply-demand balance and frequency security. In this regard, a novel frequency constrained dispatch framework with ER and virtual inertia from WTs is proposed. Firstly, this paper establishes the WT model with both ER and virtual inertia, whose energy sources are WT's deloading and rotor kinetic energy, respectively. Secondly, the system frequency response and CGUs' power response are derived while considering WTs exiting inertia response at frequency nadir. Then, this paper develops a stochastic-optimization-based frequency constrained dispatch model, where both WTs' frequency regulation parameters and rotor speeds are decision variables, so that the coupling between WT's mechanical and electrical parts and the coupling between system's transient dynamics and steady-state operation can be fully reflected. Finally, convex hull relaxation, convex hull approximation and deep neural networks are used to transform the original nonlinear model into a mixed-integer second-order cone programming model. Case studies on the 118-bus system verify the effectiveness of the proposed models and methods.
S
SunView 深度解读
该研究对阳光电源ST系列储能变流器和大型储能系统的频率调节策略具有重要参考价值。文中提出的风电虚拟惯量与能量备用协调控制框架,可迁移应用于储能系统的GFM控制,优化PowerTitan等大型储能产品的一次调频性能。特别是文中基于深度神经网络的非线性模型简化方法,有助于提升储能VSG控制的实时性能。研究成果可用于完善阳光储能产品的电网支撑功能,提高系统在高可再生能源渗透率场景下的频率调节能力。建议在ST系列新产品中融入类似的多时间尺度协调控制策略,增强产品竞争力。