• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2016, Vol. 37 ›› Issue (6): 86-95.doi: 10.3969/j.issn.1000-7229.2016.06.013

• 输配电技术 • 上一篇    下一篇

考虑低电压穿越的风电场双机聚合模型

高峰1,黄鸣宇1,乔颖2,阮佳阳2   

  1. 1. 国网宁夏电力公司电力科学研究院,银川市  750002;2.电力系统国家重点实验室(清华大学电机系),北京市  100084
  • 出版日期:2016-06-01
  • 作者简介:高峰(1982),男,博士,高级工程师,从事电力系统规划和电力系统分析方面的研究工作; 黄鸣宇(1980),男,硕士,高级工程师,从事电力系统自动化及智能电网工程技术方面的研究工作; 乔颖(1981),女,博士,副教授,研究方向为新能源、分布式发电和电力系统安全与控制; 阮佳阳(1987),男,博士研究生,研究方向为新能源发电机、电站建模和电力系统动态稳定。
  • 基金资助:

    国网宁夏电力公司科技项目(SGNXDk00BGQ71400076)

A Dual-Machine Aggregation Model of Wind Farm Considering LVRT

GAO Feng 1, HUANG Mingyu 1, QIAO Ying2, RUAN Jiayang 2   

  1. 1. State Grid Ningxia Electric Power Research Institute, Yinchuan 750002, China;
    2.State Key Lab of Power Systems, Department of Electric Engineering, Tsinghua University, Beijing 100084, China
  • Online:2016-06-01

摘要:

场内风速分布不均、集电线路分布不匀等因素造成各发电机间继电保护状态和外特性的差异,使得常规单机聚合模型难以准确反映真实风电场的故障穿越行为。为此,基于逆向建模方法与宏观特征参数,提出了对双馈异步机组(doubly-fed induction generator,DFIG)风电场具有更强适应的双机聚合模型。首先,分析了过流短接保护对风电场外特性指标的影响。其次,考虑到DFIG的功率源特性,低电压穿越中对其转子侧Crowbar的描述决定了是否能精确模拟风电场的功率调制响应,而短路电流水平又决定了Crowbar是否动作,是引起发电机间调性不同的最主要因素。基于该不同调性对故障过程中的DFIG进行分类,在双机等值模型的基础上实现了对风电场内分布行为的描述,并可根据具体风电场参数和风资源特性主动调节宏观参数组,从而平滑设定影响外特性的场内分布因素水平。最后,为提高该模型的实用性,还提出了一套参数辨识策略,依据故障深度提取出能体现风电场于该次扰动中最大的可能性响应的宏观参数组。多机系统仿真验证了单机等值存在的问题以及双机等值模型的性能。所提方法可考虑风电场自身的风资源特性,同时有效提高对风电场功率响应、相邻同步机功角稳定和负荷电压稳定行为的模拟精度。

关键词: 双机聚合模型, 暂态稳定, Crowbar效应, 低电压穿越, 风速分布

Abstract:

Due to differences of the relay protection status and external characteristics among generators derived from distribution of the wind speed and collection network, the conventional single-machine aggregation model cannot offer high accuracy of fault ride-through behaviors of real wind farms in all scenarios. This paper proposes a dual-machine model that is more applicable for doubly-fed induction generator (DFIG) wind farms, based on a reverse modeling method and the delicately-designed macroscopic parameters. First, we analyze the effect of over-current protection on controllability of the wind farm. Considering the power-source nature of DFIGs, the Crowbar dynamic during a large disturbance has a great impact on accuracy of the simulated power response, whereas the peak current level decides whether Crowbar is activated. Thus the current level proves to be the critical factor that generates incoherency among DFIGs, based on which the generators can be grouped. Naturally, description of the incoherency can be implemented by a dual-machine model, and its macroscopic parameters can be adjusted according to control parameters and the wind resources, so as to smoothly set the level of distribution factors that produce incoherency. In order to improve practicability of the proposed model, a reliable parameter-identification procedure is presented, which extracts macroscopic parameters reflecting power responses with the maximum probability. Simulation verifies drawbacks of the single-machine aggregation model and performances of the novel model. With the ability to consider features of wind resources, the proposed model remarkably improves accuracy of wind farms' power modulation behaviors, adjacent synchronous generators' power-angle dynamics, and the motor-type loads' voltage dynamics.

Key words: dual-machine aggregation model, transient stability, Crowbar effects, low voltage ride through, wind-speed distribution

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