Logic Optimization of Single Terminal Protection in Flexible DC Power System Based on Improved Multi-Objective Particle Swarm Optimization Algorithm

The optimization of single terminal protection logic is an indispensable step to ensure the normal operation of a flexible DC power grid, but the optimization process is vulnerable to the interference of uneven voltage, strong magnetic field, power grid fault and other problems. In order to solve th...

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Bibliographic Details
Published in:2024 11th International Forum on Electrical Engineering and Automation (IFEEA) pp. 304 - 308
Main Authors: Gao, Mingliang, Xie, Linwei, Xiao, Li, Guo, Xiao, Zhang, Lianchao
Format: Conference Proceeding
Language:English
Published: IEEE 22.11.2024
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Summary:The optimization of single terminal protection logic is an indispensable step to ensure the normal operation of a flexible DC power grid, but the optimization process is vulnerable to the interference of uneven voltage, strong magnetic field, power grid fault and other problems. In order to solve the above problems, a single terminal protection logic optimization method for a flexible DC power grid based on an improved multi-objective particle swarm optimization algorithm is proposed. This method first uses the shortest path method to find the fault points in the power grid and isolate them to avoid the impact of fault points on the optimization process. Secondly, zero sequence current is injected into the power grid to suppress unstable voltage and ensure that the power grid is in a three-phase balanced state. Finally, the optimization model of the single terminal protection logic of the power grid is constructed, and the improved multi-objective particle swarm optimization algorithm is used to solve the model, output the optimal solution set, and complete the optimization of the single terminal protection logic of the flexible dc power grid. The experimental results show that the proposed method has a fast convergence speed and a good optimization effect.
DOI:10.1109/IFEEA64237.2024.10878787