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

doi:10.11930/j.issn.1004-9649.202404131

Abstract

Abstract:

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.

Key words: new energy integration, oscillation risk assessment, worst operating condition search, metaheuristic algorithm

Linguang WANG, Xutao LI, Yong REN, Xiaorong XIE. A Searching Method for the Worst Operating Condition of Oscillatory Stability in New Energy Systems Based on Metaheuristic Algorithm[J]. Electric Power, 2025, 58(3): 65-72.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202404131

https://www.electricpower.com.cn/EN/Y2025/V58/I3/65

Figures/Tables 8

Fig.1 The search process for worst operating condition in oscillation stability based on PSO

Fig.2 Large-scale wind integration system

Fig.3 Iteration process in PSO

Fig.4 Logarithmic derivative curve when P is 0.100 p.u.

Fig.5 Logarithmic derivative curve when P is 0.434 p.u.

Fig.6 Logarithmic derivative curve when P is 1.000 p.u.

Fig.7 Output current waveform of the wind farm

Fig.8 Wind farm output current sub-/ super- synchronous band spectrum

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