Open AccessResearch on Chain Fault Prevention Model Considering Voltage Stability
Author(s) -
Huiqiong Deng,
Xinyun Chen
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2179/1/012004
Subject(s) - tripping , fault (geology) , control theory (sociology) , reliability engineering , computer science , electric power system , grid , stability (learning theory) , node (physics) , particle swarm optimization , power (physics) , power grid , index (typography) , voltage , control (management) , engineering , electrical engineering , mathematics , circuit breaker , algorithm , artificial intelligence , physics , geometry , structural engineering , quantum mechanics , machine learning , seismology , world wide web , geology
In this paper, we aim to prevent and control the chain tripping phenomenon in the pre-chain fault stage of the power grid, and use the L index and node injection power as the safety index to indicate the voltage stability of the power grid and the safety level of the current operation state of the power grid by adjusting the power output of the generating units. Based on this index and considering the various constraints of the grid, a preventive model is given to make the grid have the highest possible safety level against chain tripping and at the same time improve the voltage stability. In this paper, the prevention model is established based on the particle swarm algorithm, and the simulation results prove the feasibility and effectiveness of the proposed prevention model on the IEEE39 node system.