Madaram Vikramgoud, Biswas Pabitra Kumar, Sain Chiranjit, Thanikanti Sudhakar Babu, Selvarajan Shitharth
Department of Electrical and Electronics Engineering, National Institute of Technology Mizoram, Aizwal, 796012, India.
Electrical Engineering Department, Ghani Khan Choudhury Institute of Engineering &Technology, Malda, West Bengal, India.
Sci Rep. 2024 Sep 18;14(1):21795. doi: 10.1038/s41598-024-72428-6.
In this work, a new kind of charge scheduling algorithm is proposed by utilizing the War Strategy Optimization (WSO) algorithm. The strategies used in the war such as attack, defense, assigning soldiers to take positions are the inspiration to this algorithm. The proposed WSO algorithm is validated in a constructed geographic area which consists of Six starting/destination points, sixteen nodes, and twelve charging stations. In terms of waiting time and charging cost, the experimental results show that the WSO method much improves over current methods. The average waiting time and average charging cost of EVs are validated in MATLAB, with different considerations such as different number of EVs varied from 25 to 100, and different number of charging piles varied from 1 to 4. The WSO algorithm specifically lowered charging costs by up to 13.67% compared to the same and waiting time by up to 83.25% relative to the First Come First Serve algorithm. Comparatively to the Chaotic Harris Hawk Optimization and Harris Hawk Optimization algorithms, the WSO method demonstrated declines in waiting time by 11.17% and 39.09%, respectively, and declines in charging costs by 3.61% and 12.45%, respectively. Especially in situations with limited charging infrastructure, these findings show that the WSO algorithm may improve the efficiency and cost-effectiveness of EV charging management systems. For real-world EV charging management systems, the method's capacity to efficiently allocate EVs among charging stations, lower waiting times, and lower charging costs makes it a potential solution.
在这项工作中,通过利用战争策略优化(WSO)算法提出了一种新型的充电调度算法。战争中使用的策略,如攻击、防御、分配士兵占据阵地等,为该算法提供了灵感。所提出的WSO算法在一个构建的地理区域中进行了验证,该区域由六个起始/目的地点、十六个节点和十二个充电站组成。在等待时间和充电成本方面,实验结果表明,WSO方法比当前方法有很大改进。在MATLAB中验证了电动汽车的平均等待时间和平均充电成本,考虑了不同的因素,如电动汽车数量从25辆变化到100辆,充电桩数量从1个变化到4个。与相同算法相比,WSO算法的充电成本降低了高达13.67%,与先来先服务算法相比,等待时间降低了高达83.25%。与混沌哈里斯鹰优化算法和哈里斯鹰优化算法相比,WSO方法的等待时间分别下降了11.17%和39.09%,充电成本分别下降了3.61%和12.45%。特别是在充电基础设施有限的情况下,这些结果表明,WSO算法可以提高电动汽车充电管理系统的效率和成本效益。对于现实世界的电动汽车充电管理系统,该方法能够在充电站之间高效分配电动汽车、减少等待时间并降低充电成本,使其成为一种潜在的解决方案。