基于改进人工蜂鸟算法的主动配电网无功优化
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TM727

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国家自然科学基金资助面上项目(52377185)


Study on Reactive Power Optimization in Active Distribution Networks Based on an Improved Artificial Hummingbird Algorithm
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    摘要:

    随着众多分布式电源并入电网,主动配电网在应对分布式电源输出功率的不稳定性和协调配电网内多样化的无功补偿设备方面,正面临着严峻挑战。对于当前配电网中出现的电压偏移量过大、网损过高的问题,引入了一种基于PV曲线上支解与鞍点电压差值的新型电压稳定性指标,构建了旨在得到最低网络损耗、最小化电压偏移量以及提升电压稳定性的多目标函数优化模型。通过改进人工蜂鸟算法来求解上述模型,为提高算法的性能,引入了Tent混沌映射方法使种群分布更加均匀和引入变异操作避免算法陷入局部最优。在IEEE-33节点系统中进行仿真验证,结果表明,相较于传统算法,采用改进后的人工蜂鸟算法对该模型进行优化,能够显著减少电压偏移量并降低有功损耗,从而保障电网的稳定运行。

    Abstract:

    In view of the significant challenges for active distribution networks when addressing the instability of distributed power output and coordinating diverse reactive power compensation devices within the network as numerous distributed power sources are integrated into the grid, a novel voltage stability index has thus been introduced on the basis of the branch decomposition and saddle point voltage difference in the PV curve so as to address the issues of excessive voltage deviation and high network losses in the current distribution network. By improving the artificial hummingbird algorithm to solve the above-mentioned model, in order to enhance the performance of the algorithm, Tent chaotic mapping method is introduced to realize a more uniform population distribution, with mutation operation introduced to avoid the algorithm from getting trapped in local optima. With a simulation validation conducted in the IEEE-33 system, the results demonstrate that compared to traditional algorithms, an optimization of the model with the improved artificial hummingbird algorithm significantly reduces voltage deviation and active power losses, thereby ensuring stable operation of the power grid.

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陈泽文,宁志毫,曾进辉,周武定.基于改进人工蜂鸟算法的主动配电网无功优化[J].湖南工业大学学报,2026,40(3):24-32.

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  • 在线发布日期: 2026-03-27
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