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Reactive Power Optimization Control Method for Distribution Network with Hydropower Based on Improved Discrete Particle Swarm Optimization Algorithm

delete2025-08-17
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OA
AI
刘涛 (Tao Liu)
B
Bin Jia
S
Shuangxiang Luo
X
Xiangcong Kong
Z
Zhou Yong
H
Hongbo Zou *
DOI:10.3390/pr13082455delete
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Abstract

Abstract

En 中文
With the rapid development of renewable energy, the proportion of small hydropower as a clean energy in the distribution network (DN) is increasing. However, the randomness and intermittence of small hydropower has brought new challenges to the operation of DN; especially, the problems of increasing network loss and reactive voltage exceeding the limit have become increasingly prominent. Aiming at the above problems, this paper proposes a reactive power optimization control method for DN with hydropower based on an improved discrete particle swarm optimization (PSO) algorithm. Firstly, this paper analyzes the specific characteristics of small hydropower and establishes its mathematical model. Secondly, considering the constraints of bus voltage and generator RP output, an extended minimum objective function for system power loss is established, with bus voltage violation serving as the penalty function. Then, in order to solve the following problems: that the traditional discrete PSO algorithm is easy to fall into local optimization and slow convergence, this paper proposes an improved discrete PSO algorithm, which improves the global search ability and convergence speed by introducing adaptive inertia weight. Finally, based on the IEEE-33 buses distribution system as an example, the simulation analysis shows that compared with GA optimization, the line loss can be reduced by 3.4% in the wet season and 13.6% in the dry season. Therefore, the proposed method can effectively reduce the network loss and improve the voltage quality, which verifies the effectiveness and superiority of the proposed method.
Keywords:
small hydropower
reactive power optimization
distribution network
improved discrete particle swarm optimization
power loss reduction

Journal

Processes cover
Processes
IF:
2.8
Papers:
6.7K
Citations:
3.7W

Organization

C
china three gorges university
Scholars:
1.0W
Papers: 6.0K
Citations: 114