Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于改进蜻蜓算法的混合储能容量优化配置

来源:电工电气发布时间:2024-08-30 15:30 浏览次数:21

基于改进蜻蜓算法的混合储能容量优化配置

黄礼灿,秦斌
(湖南工业大学 电气与信息工程学院,湖南 株洲 412007)
 
    摘 要:针对传统方法在风光储能系统容量优化配置过程中求解精度较低、效率较慢等问题,提出一种改进蜻蜓算法(IDA)。通过采用 Logistic 混沌初始化和非线性惯性权重两种策略对原始蜻蜓算法进行改进,使算法能够在初始化阶段分布更均匀,全局搜索和局部开发更加协调,同时更快锁定最优解区域;构建混合储能系统容量优化模型,以储能装置的生命周期费用作为目标函数,并考虑负荷缺电率、储能系统能量等约束条件。使用 MATLAB 软件对算例进行仿真分析,通过 3 种算法的仿真结果对比发现,采用改进蜻蜓算法蓄电池个数有所减少,全生命周期费用也相对降低,有较好的经济适用性。
    关键词: 混合储能;容量配置;改进蜻蜓算法;混沌初始化;蓄电池;全生命周期费用
    中图分类号:TM734 ;TM912     文献标识码:A     文章编号:1007-3175(2024)08-0001-07
 
Optimal Configuration of Hybrid Energy Storage Capacity Based on
Improved Dragonfly Algorithm
 
HUANG Li-can, QIN Bin
(College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China)
 
    Abstract: Aiming at the problems of lower solution accuracy and slower efficiency of traditional methods in the process of capacity optimization and configuration of wind energy storage system, an improved dragonfly algorithm (IDA) is proposed. The original dragonfly algorithm is improved by adopting two strategies: Logistic chaotic initialization and nonlinear inertia weights, so that the algorithm can be more uniformly distributed in the initialization stage, the global search and local development can be more coordinated and lock the optimal solution region more quickly at the sametime, constructing the capacity optimization model of the hybrid energy storage system, taking the life-cycle cost of the storage device as the objective function and considering load power shortage rate, energy storage system and other constraints. Finally, this paper uses MATLAB software to simulate and analyze the algorithm, the simulation results of the three algorithms are compared and found, using the improved dragonfly algorithm, the number of storage batteries is reduced, the cost of full life-cycle is also relatively reduced and it has better economic applicability.
    Key words: hybrid energy storage; capacity configuration; improved dragonfly algorithm; chaotic initialization; storage battery; full life-cycle cost
 
参考文献
[1] 荆涛,陈庚,王子豪,等. 风光互补发电耦合氢储能系统研究综述[J]. 中国电力,2022,55(1) :75-83.
[2] 亚夏尔·吐尔洪, 王小云, 常清, 等. 基于改进 NSGA-Ⅲ 的微电网储能多目标优化配置[J]. 电工电气,2024(3) :21-28.
[3] 曾志辉,刘云鹏,韦延方,等. 基于改进蝙蝠算法的混合储能系统容量优化配置[J] . 河南理工大学学报(自然科学版),2023,42(5) :130-136.
[4] 王欣,谭永怡,秦斌. 改进 MOGOA 及其在风储容量优化配置中的应用[J] . 电力科学与技术学报,2024,39(2) :159-169.
[5] 周天沛,孙伟. 风光互补发电系统混合储能单元的容量优化设计[J] . 太阳能学报,2015,36(3) :756-762.
[6] 陈天,蔡泽祥,谢鹏,等. 基于改进微分进化算法的风光互补系统发电容量优化配置[J]. 电力科学与技术学报,2017,32(3) :22-28.
[7] 张冲,荣娜. 基于改进粒子群算法的新能源侧储能容量配置[J] . 电网与清洁能源,2022,38(10) :98-105.
[8] 陈明,张靠社. 基于改进布谷鸟算法的风光储联合供电系统储能容量优化配置研究[J] . 电网与清洁能源,2016,32(8) :141-146.
[9] 张子恒,吴定会,杨朝辉,等. 基于改进差分进化算法的微网容量优化配置[J] . 控制工程,2023,30(1) :90-97.
[10] MIRJALILI S.Dragonfly algorithm:A new metaheuristic optimization technique for solving single-objective,discrete,and multi-objective problems[J].Neural Computing and Applications,2016,27(4) :1053-1073.
[11] 吴忠强,赵德隆,王云青,等. 基于改进蜻蜓算法的蓄电池参数辨识[J] . 电机与控制学报,2020,24(12) :152-160.
[12] 李茂林,王勇杰,介丹. 基于多种群蜻蜓算法的四旋翼自抗扰姿态优化控制[J] . 计算机应用与软件,2022,39(12) :328-334.
[13] 王波,王浩,杜晓昕,等. 基于亚群和差分进化的混合蜻蜓算法[J] . 计算机应用,2023,43(9) :2868-2876.
[14] 薛飞,马鑫,田蓓,等. 基于改进蜻蜓算法的光伏全局最大功率追踪[J].中国电力,2022,55(2) :131-137.
[15] 马丙泰,刘海涛,张匡翼,等. 基于学习因子异步变化 CPSO 混合储能容量优化配置[J]. 自动化与仪器仪表,2022(7) :125-130.
[16] 唐浩,杨国华,王鹏珍,等. 基于改进粒子群算法的风光蓄互补发电系统容量优化[J] . 电测与仪表,2017,54(16) :50-55.