Power quality improvement control strategy based on active disturbance rejection control based on modified particle swarm optimization algorithm

In the context of the energy revolution, which resolutely implements the core elements of the carbon peak and carbon neutrality tasks, the national power system will develop from high carbon to deep low-carbon or even zero carbon. However, due to the grid connection of a large number of distributed power sources such as wind power and photovoltaic and the extensive access of power electronic equipment, the power quality such as voltage fluctuation and reactive power of active distribution network is becoming more and more prominent. Voltage is an important index of safety and economy of distribution system, and its stability is closely related to reactive power. For cutting, distributed power supply in the operation of the power distribution network load and node voltage caused by the volatility of rise/fall beyond the lower limit of problem,this paper proposes a self immunity (active disturbance rejection control, ADRC) double loop control of the distribution network reactive power control strategy. In view of the fast reactive power regulation ability of the energy storage system and the good performance of the active disturbance rejection control, this paper designs a reactive power support double loop controller based on the lithium battery energy storage system model, combines the ADRC with the voltage and current double closed-loop control, and optimizes the parameters of the ADRC by improving the particle swarm optimization algorithm, so that the voltage at the junction point is kept stable in the limit range. Simulation results show that the strategy is feasible.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10991805
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00

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Power quality improvement control strategy based on active disturbance rejection control based on modified particle swarm optimization algorithm

Dawei Hu, Jingwei Han, Hengyu Liu, Zhi Zhang et al.
Power Systems and Renewable Energy
article

Power quality improvement control strategy based on active disturbance rejection control based on modified particle swarm optimization algorithm

Dawei Hu, Jingwei Han, Hengyu Liu, Zhi Zhang, Shida She, Peng Yu, Zhenyang Zhao, Jiazheng Sun
article en

Abstract

In the context of the energy revolution, which resolutely implements the core elements of the carbon peak and carbon neutrality tasks, the national power system will develop from high carbon to deep low-carbon or even zero carbon. However, due to the grid connection of a large number of distributed power sources such as wind power and photovoltaic and the extensive access of power electronic equipment, the power quality such as voltage fluctuation and reactive power of active distribution network is becoming more and more prominent. Voltage is an important index of safety and economy of distribution system, and its stability is closely related to reactive power. For cutting, distributed power supply in the operation of the power distribution network load and node voltage caused by the volatility of rise/fall beyond the lower limit of problem,this paper proposes a self immunity (active disturbance rejection control, ADRC) double loop control of the distribution network reactive power control strategy. In view of the fast reactive power regulation ability of the energy storage system and the good performance of the active disturbance rejection control, this paper designs a reactive power support double loop controller based on the lithium battery energy storage system model, combines the ADRC with the voltage and current double closed-loop control, and optimizes the parameters of the ADRC by improving the particle swarm optimization algorithm, so that the voltage at the junction point is kept stable in the limit range. Simulation results show that the strategy is feasible.

Shenyang University of Technology (CN), Shanghai Electric (China) (CN)
Science and Technology Project of State Grid
Affordable and clean energy
Openalex Percentile: Top 63%
Power Systems and Renewable Energy
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