李维波, 彭智明, 张浩, 张茂杰, 方华亮. 基于自适应蚁群算法的岛礁混合发电系统电源容量优化配置分析[J]. 中国舰船研究. DOI: 10.19693/j.issn.1673-3185.03505
引用本文: 李维波, 彭智明, 张浩, 张茂杰, 方华亮. 基于自适应蚁群算法的岛礁混合发电系统电源容量优化配置分析[J]. 中国舰船研究. DOI: 10.19693/j.issn.1673-3185.03505
Optimization and Configuration Analysis of Power Capacity in Island and Reef Hybrid Power Generation System Based on Adaptive Ant Colony Algorithm[J]. Chinese Journal of Ship Research. DOI: 10.19693/j.issn.1673-3185.03505
Citation: Optimization and Configuration Analysis of Power Capacity in Island and Reef Hybrid Power Generation System Based on Adaptive Ant Colony Algorithm[J]. Chinese Journal of Ship Research. DOI: 10.19693/j.issn.1673-3185.03505

基于自适应蚁群算法的岛礁混合发电系统电源容量优化配置分析

Optimization and Configuration Analysis of Power Capacity in Island and Reef Hybrid Power Generation System Based on Adaptive Ant Colony Algorithm

  • 摘要: 【目的】岛礁供电系统的显著特点是含有种类繁多、拓扑复杂的分布式电源,能够脱离主网独立发电运行,避免采用传统的直连主网,有效降低网络损耗、电压波动幅度、铺设难度和维修成本。自适应蚁群算法因其信息素动态响应能力强,具有精准与迅速的全局搜索最优解的能力,不会陷入局部最优。【方法】据此提出基于自适应蚁群算法优化配置岛礁混合发电系统的容量,最大限度利用可再生能源,适应“双碳”政策。【结果】以外伶仃岛为目标岛礁,搭建“风光柴储”微电网混合发电系统模型,采用自适应蚁群算法优化配置其容量。【结论】该算法的仿真结果表明,相较于改进灰狼算法和人工蜂群算法而言,自适应蚁群算法能够有效地降低微电网混合发电系统的运行成本、环境污染,确保供电稳定性。

     

    Abstract: Abstract:Objectives The notable feature of the island power supply system is that it contains a wide variety of distributed power sources with complex topology, which can generate power independently from the main network, avoid the traditional direct connection to the main network, and effectively reduce network loss, voltage fluctuation, laying difficulty and maintenance cost. Because of its strong pheromone dynamic response ability, the adaptive ant colony algorithm has the ability to search the global optimal solution accurately and quickly, and will not fall into the local optimal. Methods Based on this, the capacity of the reef hybrid power generation system is optimized based on adaptive ant colony algorithm to maximize the use of renewable energy and adapt to the "two-carbon" policy. Results Taking Wailingding Island as the target island, a hybrid power generation system model of "Fengfengchai Storage" was built, and its capacity was optimized by adaptive ant colony algorithm. Conclusions The simulation results of this algorithm show that compared with the improved grey Wolf algorithm and artificial bee colony algorithm, the adaptive ant colony algorithm can effectively reduce the operating cost and environmental pollution of the hybrid power generation system of microgrid, and ensure the stability of power supply.

     

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