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1.电网安全全国重点实验室(中国电力科学研究院有限公司),北京市100192
2.国网吉林省电力有限公司电力科学研究院,吉林省长春市 130021
Received:02 January 2025,
Revised:2025-04-27,
Published Online:19 May 2025,
Published:25 September 2025
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吕思琦,孙华东,宋瑞华等.面向电网等值的汇集站下直驱风电场群频域聚合建模方法[J].电力系统自动化,2025,49(18):106-116.
LYU Siqi,SUN Huadong,SONG Ruihua,et al.Frequency-domain Aggregation Modeling Method for Direct-drive Wind Farm Clusters Connected to Collection Station Oriented to Power Grid Equivalence[J].Automation of Electric Power Systems,2025,49(18):106-116.
吕思琦,孙华东,宋瑞华等.面向电网等值的汇集站下直驱风电场群频域聚合建模方法[J].电力系统自动化,2025,49(18):106-116. DOI: 10.7500/AEPS20250102004.
LYU Siqi,SUN Huadong,SONG Ruihua,et al.Frequency-domain Aggregation Modeling Method for Direct-drive Wind Farm Clusters Connected to Collection Station Oriented to Power Grid Equivalence[J].Automation of Electric Power Systems,2025,49(18):106-116. DOI: 10.7500/AEPS20250102004.
新能源次/超同步振荡问题一般被视为一个局部电网的系统稳定问题。为兼顾分析精度和仿真效率,需建立规模适当的网络模型和新能源等值模型。为此,提出了一种面向电网等值的汇集站下直驱风电场群频域聚合建模方法。首先,提出用于量化风电场间动态耦合强度的改进相对增益矩阵(RGA)方法,通过解耦分析构建电网中与待研场站强耦合的风电场集合;其次,引入五点数值差分公式计算阻抗灵敏度,通过分析控制参数对全功率变流器型设备阻抗的影响,选择汇集站下直驱风电场群并网振荡特性的主导因素作为聚类对象;然后,采用人工鱼群算法(AFSA)对近邻传播(AP)算法中的偏向参数寻优,以获得AP算法的聚类数目,进而确定风电场聚类集合及聚合模型参数;最后,以实际电网作为算例,验证了聚合建模方法在次/超同步振荡特性分析中的有效性。
The sub-/super-synchronous oscillation of renewable energy is generally regarded as system stability issue of a local power grid. In order to balance the analysis accuracy and simulation efficiency
it is necessary to establish a network model and renewable energy equivalent model with an appropriate scale. To this end
a frequency-domain aggregation modeling method for direct-drive wind farm clusters connected to collection station oriented to power grid equivalence is proposed. Firstly
an improved relative gain array (RGA) method is proposed to quantify the dynamic coupling strength among wind farms. Through decoupling analysis
the wind farm set strongly coupled with the stations to be studied in the power grid is constructed. Secondly
the five-point numerical difference formulas are introduced to calculate the impedance sensitivity. By analyzing the influence of control parameters on the impedance of full-power converter equipment
the dominant factors of the grid-connected oscillation characteristics of direct-drive wind farm clusters are selected as the clustering objects. Thirdly
the artificial fish swarm algorithm (AFSA) is adopted to optimize the bias parameters in the affinity propagation (AP) algorithm so as to obtain the clustering number of the AP algorithm
and then determine the wind farm clustering set and the aggregation model parameters. Finally
taking an actual power grid as a case
the effectiveness of the aggregation modeling method in the analysis of sub-/super-synchronous oscillation characteristics is verified.
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