基于元启发式算法的新能源电力系统振荡稳定性最差工况搜索方法  

A Searching Method for the Worst Operating Condition of Oscillatory Stability in New Energy Systems Based on Metaheuristic Algorithm

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作  者:汪林光 李旭涛 任勇 谢小荣[1] WANG Linguang;LI Xutao;REN Yong;XIE Xiaorong(State Key Laboratory of Power System Operation and Control(Tsinghua University),Beijing 100084,China;Electric Power Research Institute,State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750002,China)

机构地区:[1]新型电力系统运行与控制全国重点实验室(清华大学),北京100084 [2]国网宁夏电力有限公司电力科学研究院,宁夏银川750002

出  处:《中国电力》2025年第3期65-72,共8页Electric Power

基  金:国网宁夏电力有限公司科技项目(高占比新能源电力系统宽频振荡风险评估技术研究及应用,5229DK230001)。

摘  要:随着新能源的广泛接入,由电力电子设备与电网间相互作用引发的振荡问题日益凸显。在电力系统运行规划过程中,需要对恶劣工况下系统振荡风险展开评估。因而如何找到最恶劣工况,成为亟待解决的关键问题。提出了一种基于元启发式算法的新能源电力系统振荡稳定性最差工况搜索方法。根据所研究的系统选择工况变量,采用对数导数法构建振荡稳定性分析函数,选择元启发式算法并辨识系统振荡最差工况,最后,根据系统振荡最差工况分析系统振荡风险。将该方法应用于某实际大规模风电接入系统,计算得到该系统的振荡最差工况并评估了系统振荡风险。With the massive integration of new energy,the oscillation problem caused by the interaction between power electronics devices and the grid is becoming prominent.In the planning and operation stage of power system,it is necessary to assess the risk of system oscillation and analyze this risk under severe operating conditions.Therefore,how to search the worst operating conditions has become a key problem to solve.In this paper,an oscillatory worst condition search method is proposed based on metaheuristic algorithm.In this method,the operating condition variables are first selected in according with the system.Then,an oscillation stability analysis function is constructed based on logarithmic derivative method.After that,metaheuristic algorithm is selected to identify the worst operating condition of oscillatory stability.Finally,the risk of system oscillation is analyzed according to the worst operating condition.This method is applied to an actual large-scale wind power integration system,resulting in the worst operating condition is calculated and the risk of system oscillation is evaluated.

关 键 词:新能源并网 振荡风险评估 最差工况搜索 元启发式算法 

分 类 号:TM7[电气工程—电力系统及自动化]

 

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