应用自适应遗传算法的电动汽车充放电协同调度

doi:10.13229/j.cnki.jdxbgxb20211200

摘要/Abstract

摘要：

针对当前方法对电动汽车充放电协同调度存在调度时间长、调度的精准度低以及功率能耗大的问题，提出了应用自适应遗传算法的电动汽车充放电协同调度方法。首先，通过对电动汽车的充电预测，合理规划电动汽车的充电设施，并以此为基础，提出了相关约束条件，建立了电动汽车的充放电协同调度模型；然后，通过自适应遗传粒子群算法对模型进行了求解；最后，通过计算结果，完成了电动汽车的充放电协同调度。实验结果表明：本文方法在进行电动汽车充放电协同调度时，调度时长短、精准度高且所需的功率能耗小。

关键词: 自适应遗传算法, 粒子群算法, 电动汽车, 充放电, 协同调度, 调度模型, 充电方式

Abstract:

Aiming at the problems of long scheduling time， low scheduling accuracy， and large power consumption in the current method for electric vehicle charging and discharging coordinated scheduling， a method for electric vehicle charging and discharging coordinated deployment using adaptive genetic algorithm is proposed. Firstly, through the charging prediction of electric vehicles, the charging facilities of electric vehicles are reasonably planned, and on this basis, the relevant constraints are put forward to establish the charging and discharging cooperative scheduling model of electric vehicles. Then, the model was solved by adaptive genetic particle swarm optimization algorithm.Finally， through the calculation results， the coordinated charging and discharging scheduling of electric vehicles is completed. The experimental results show that the method proposed in this paper has short scheduling time， high accuracy and low power consumption when performing electric vehicle charging and discharging coordinated scheduling.

Key words: adaptive genetic algorithm, particle swarm algorithm, electric vehicle, charging and discharging, collaborative scheduling, scheduling model, charging method

中图分类号:

TM721

李翠玉,胡雅梦,康亚伟,张德良. 应用自适应遗传算法的电动汽车充放电协同调度[J]. 吉林大学学报(工学版), 2022, 52(11): 2508-2513.

Cui-yu LI,Ya-meng HU,Ya-wei KANG,De-liang ZHANG. Coordination scheduling of electric vehicle charge and discharge using adaptive genetic algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(11): 2508-2513.

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参考文献 11

1	张丽, 朱孝勇, 左月飞. 电动汽车用转子永磁型无刷电机与控制系统容错技术综述[J]. 中国电机工程学报, 2019, 39(6): 1792-1802, 1875.
	Zhang Li, Zhu Xiao-yong, Zuo Yue-fei. Overview of fault-tolerant technologies of rotor permanent magnet brushless machine and its control system for electric vehicles[J]. Proceedings of the CSEE, 2019, 39(6): 1792-1802, 1875.
2	齐鹏远, 刘伟杰, 马伟民. 光伏系统中储能电源充放电特性应用分析[J]. 功能材料, 2019, 50(1): 1110-1113.
	' Qi Peng-yuan, Liu Wei-jie, Ma Wei-min. Application analysis of charging and discharging for battery in photovoltaic system[J]. Journal of Functional Materials, 2019, 50(1): 1110-1113.
3	张怡冰, 刘其辉, 洪晨威, 等. 基于模糊控制的区域电动汽车入网充放电调度策略[J]. 电力自动化设备, 2019, 39(7): 147-153.
	Zhang Yi-bing, Liu Qi-hui, Hong Chen-wei, et al.Charging and discharging dispatch strategy of regional V2G based on fuzzy control[J]. Electric Power Automation Equipment, 2019, 39(7): 147-153.
4	于娜, 于飞, 黄大为, 等. 基于多代理系统的电动汽车充放电分布式协同调度策略[J]. 电力系统保护与控制, 2019, 47(5): 1-9.
	Yu Na, Yu Fei, Huang Da-wei, et al. Multi-agent system based charging and discharging of electric vehicles distributed coordination dispatch strategy[J]. Power System Protection and Control, 2019, 47(5): 1-9.
5	冯建鑫, 王强, 王雅雷, 等. 基于改进量子遗传算法的超声电机模糊PID控制[J]. 吉林大学学报: 工学版, 2021, 51(6): 1990-1996.
	Feng Jian-xin, Wang Qiang, Wang Ya-lei, et al. Fuzzy PID control of ultrasonic motor based on improved quantum genetic algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 1990-1996.
6	王聪, 马彦, 王国光. 电动汽车充电站内的实时最优功率分配[J]. 吉林大学学报: 工学版, 2021, 51(4): 1490-1495.
	Wang Cong, Ma Yan, Wang Guo-guang, et al.Real-time optimal power allocation inside electric-vehicle charging stations[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(4): 1490-1495.
7	袁臣虎,李海杰,王岁,等.锂电池四阶段智能充电方法的研究[J].电源技术, 2019, 43(3): 402-404, 414.
	Yuan Chen-hu, Li Hai-jie, Wang Sui, et al. Research of four-stage intelligent charging way for lithium battery[J]. Chinese Journal of Power Sources, 2019, 43(3): 402-404, 414.
8	张厚升, 李震梅, 边敦新, 等. 电动汽车用三相开绕组永磁同步电机的控制及容错运行[J]. 吉林大学学报: 工学版, 2020, 50(3): 784-795.
	Zhang Hou-sheng, Li Zhen-mei, Bian Dun-xin, et al. Control and fault-tolerant operation of TPOW-PMSM for electric vehicle[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(3): 784-795.
9	陈恒安, 管霖, 卢操, 等. 新能源发电为主电源的独立微网多目标优化调度模型和算法[J]. 电网技术, 2020, 44(2): 664-674.
	Chen Heng-an, Guan Lin, Lu Cao, et al. Multi-objective optimal dispatch model and its algorithm in isolated microgrid with renewable energy generation as main power supply[J]. Power System Technology, 2020, 44(2): 664-674.
10	朱子轩, 鲁工圆, 何必胜, 等. 单线铁路网络列车运行智能调度仿真研究[J]. 计算机仿真, 2019, 36(5): 194-201.
	Zhu Zi-xuan, Lu Gong-yuan, He Bi-sheng, et al.Simulation research on intelligent dispatching of train operation on single-track railway network[J]. Computer Simulation, 2019, 36(5): 194-201.
11	徐红涛, 陈春波, 郑宏伟, 等. 基于相关分析和自适应遗传算法的盐渍化建模变量和参数优选[J]. 地球信息科学学报, 2020, 22(7): 1497-1509.
	Xu Hong-tao, Chen Chun-bo, Zheng Hong-wei, et al. Correlation analysis and adaptive genetic algorithm based feature subset and modelparameter optimization in salinization monitoring[J]. Journal of Geo-information Science, 2020, 22(7): 1497-1509.

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