微电网
计算机科学
数学优化
光伏系统
遗传算法
粒子群优化
灵活性(工程)
初始化
极限学习机
趋同(经济学)
算法
工程类
数学
人工神经网络
人工智能
机器学习
电气工程
经济
程序设计语言
控制(管理)
统计
经济增长
作者
Yijun Wang,Yuxin Liu,Kexu Zhao,Haotian Deng,Feng Wang,Fang Zhuo
标识
DOI:10.1109/pedg56097.2023.10215118
摘要
"Photovoltaic, Energy storage, Direct current, Flexibility" (PEDF) microgrid, which is an important implementation scheme of the dual-carbon target, the reduction of its overall cost is conducive to its faster promotion of popularization. Therefore, this paper proposes an Improved Whale Optimization Algorithm (IWOA) for PEDF microgrid cost optimization, which can effectively improve the convergence speed of the algorithm as well as reduce the system cost under the consideration of electric vehicle charging load connected to PEDF microgrid. Firstly, the fitness function and related constraints are introduced, then the charging load of EV is predicted using Monte Carlo algorithm. Next, while introducing the traditional Whale Optimization Algorithm (WOA), the population initialization strategy, probability judgment condition, convergence factor and disturbance factor are improved. Finally, IWOA's cost optimization effect under three typical weather scenarios is compared with traditional WOA, Genetic Algorithm and Particle Swarm Optimization Algorithm, which proves IWOA's effectiveness considering improving the convergence speed and reducing system cost.
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