基于自适应蚁群算法的岛礁混合发电系统电源容量优化方法
Optimization method for island and reef hybrid power generation systems'power capacity based on adaptive ant colony algorithm
李维波 1彭智明 1张浩 1张茂杰 1方华亮2
作者信息
- 1. 武汉理工大学 自动化学院,湖北 武汉 430070
- 2. 武汉大学 电气与自动化学院,湖北 武汉 430072
- 折叠
摘要
[目的]针对岛礁混合发电系统电源容量配置存在的问题,提出一种基于自适应蚁群算法(ACA)的优化方法.[方法]采用自适应蚁群算法作为核心优化工具,对岛礁混合发电系统的电源容量进行配置.通过采用自适应蚁群算法模拟蚁群寻食过程,在搜索空间中以可再生能源发电量作为信息素,通过全局搜索找到最优解,实现对可再生能源的充分利用.并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.[结果]算法仿真结果表明,相较于改进灰狼算法和人工蜂群算法,自适应蚁群算法能够有效降低微电网混合发电系统的运行成本和对环境的污染,确保供电稳定性.[结论]所做研究能够有效增加微电网混合发电系统的供电稳定性,减少运行成本与环境污染,从而实现对能源的高效利用.
Abstract
[Objectives]Aiming to address the existing challenges in the power capacity configuration of is-land and reef hybrid power generation systems,this paper proposes an optimization method based on the ad-aptive ant colony algorithm(ACA).[Methods]An ACA is used as the core optimization tool to configure the power capacity of an island and reef hybrid power generation system.The process of ants foraging is simu-lated by employing the ACA and using the power generation of renewable energy as dynamic pheromones in the search space.The optimal solution is then found through global search,achieving the full utilization of re-newable energy.Taking Wai Lingding Island as the target island,a'wind-solar-diesel-storage'microgrid hy-brid power generation system model is constructed,and the ACA is used to optimize its capacity configura-tion.[Results]The simulation results of the algorithm indicate that,compared to the improved Grey Wolf algorithm and Artificial Bee Colony algorithm,the ACA can effectively reduce the operational costs and envir-onmental pollution of the microgrid hybrid power generation system,while ensuring the stability of the power supply.[Conclusions]The results of this study can effectively increase the power supply stability of the micro grid hybrid power generation system,reduce operating costs and environmental pollution,and thus achieve ef-ficient utilization of energy resources.
关键词
混合发电系统/自适应蚁群算法/容量配置/动态信息素/经济性Key words
hybrid power generation system/adaptive ant colony algorithm(ACA)/capacity configuration/dynamic pheromone/economy引用本文复制引用
基金项目
国家重点研发计划(2020YFB1506802)
出版年
2024
国家科技期刊平台
NSTL
万方数据