一种考虑风电场并网的电力系统在线同调识别策略  

An Online Coherency Identification Strategy for Power System Considering Wind Farm Integration

作　　者：刘扬[1] 唐飞[1] 施浩波 刘涤尘[1] 张立波[3] 刘佳乐[1] 王飞飞 LIU Yang;TANG Fei;SHI Haobo;LIU Dichen;ZHANG Libo;LIU Jiale;WANG Feifei(School of Electrical Engineering,Wuhan University,Wuhan 430072,Hubei Province,China;China Electric Power Research Institute,Haidian District,Beijing 100192,China;Key Laboratory of Control of Power Transmission and Conversion (Shanghai Jiao Tong University),Ministry of Education,Minhang District,Shanghai 200240,China)

机构地区：[1]武汉大学电气工程学院,湖北省武汉市430072 [2]中国电力科学研究院有限公司,北京市海淀区100192 [3]电力传输与功率变换控制教育部重点实验室(上海交通大学),上海市闵行区200240

出　　处：《电网技术》2019年第4期1236-1244,共9页Power System Technology

基　　金：国家电网公司科技项目(考虑第三道防线的规划电网多级网架结构优化方法研究)~~

摘　　要：现有的大电网同调机组分群策略,大都仅针对功角轨迹之间的距离进行研究,忽略了风电场并网对电力系统固有振荡模式的影响。针对上述存在的同调分群不准确问题,提出了一种两阶段高风电渗透率下大电网受扰机群同调分群策略。在第1阶段,通过修正系统的收缩导纳矩阵将风功率以电流的形式进行等值,并与其电气距离最近的同步机组进行联合分析,进而在不同潮流水平和典型工况下,离线计算其等效功角获得含风电场电力系统的改进发电机耦合程度拉普拉斯矩阵,求解其特征向量并得到离线的发电机耦合程度分类结果。在第2阶段,构建电力系统邻接图并将所得分类结果作为邻接图功角权值矩阵的约束,对高风电渗透率下大电网的改进功角拉普拉斯矩阵进行在线修正,通过特征映射算法提取其特征信息,进而通过修正的余弦相似度因子算法在线获得当前的同调分群结果。最后通过IEEE 39节点和118节点系统仿真,验证了所提策略的正确性和有效性。Most of existing coherency identification strategies of generators in large power grid only focuse on the distances between power angle curves, ignoring the influence of wind power integration on the inherent oscillation mode of power system. Aiming at the problem of inaccurate coherency identification, a two-stage coherency identification strategy for large power grid under high wind power penetration is proposed. In the first stage, the wind power is equivalent with form of current by modifying the admittance matrix of the system. The wind generator and the synchronous generator nearest in electrical distance are analyzed together. Then at different power flow levels and under typical operation conditions, the equivalent power angle is calculated off-line so the Laplace matrix of the improved generator coupling degree in wind power system is obtained. The Laplace matrix is used to solve eigenvectors and get off-line classification results of generator coupling degree. In the second stage, an adjacency graph of power system is constructed. The obtained classification results are taken as the constraints of the power angle weight matrix of the adjacency graph for online modification of improved power angle Laplace matrix for large power grid under high wind power penetration. The feature information is extracted with feature mapping algorithm, and then the current coherency identification results are obtained with the modified cosine similarity factor algorithm. Finally,correctness and effectiveness of the proposed method are verified with simulation in IEEE 39-bus system and 118-bus system.

关 键 词：在线同调识别 含风电场电力系统 拉普拉斯特征映射 半监督算法 修正的余弦相似度因子 

分 类 号：TM721[电气工程—电力系统及自动化]