摘要
为了提高新能源发电系统的稳定性与经济性,降低混合储能系统运行周期成本,基于改进型粒子群算法对混合储能配置策略进行优化。首先对铅酸蓄电池与超级电容器组成的混合系统建立全生命周期成本数学模型,以最小成本为目标函数,系统缺电率等性能指标为约束条件,对系统周期最小成本进行优化;其次引入自适应权重和加速因子优化粒子群;基于对全生命周期成本最小研究的不足,提出将全生命周期成本与系统缺电率优化策略相结合,用多目标粒子群求解最优帕累托解集;最后对算例进行仿真与求解。实验结果表明,该方法不仅加快寻优收敛性,减少最小费用成本,而且多目标可以满足不同情况的需求。
In order to advance the stability and economical efficiency of the new energy resources generating system and decrease the costing of the running cycle the hybrid energy storage system,the hybrid energy storage configuration strategy was optimized based on the improved particle swarm optimization algorithm.Primarily,A mathematical model of cycle cost is built for a hybrid system comprised of lead-acid batteries and supercapacitors.The minimum cycle cost of the system is optimized by spending the least cost as the objective function and the system power deficit rate and other performance index as constraints;In the second place,the self-adapting weight and acceleration factor are introduced to optimize particle swarm optimization;Based on the inadequacy of the research on minimizing the total life cycle cost,a multi-objective particle swarm optimization is proposed to solve the optimal Pareto solution set by integrating the whole life cycle cost with the system power deficit rate optimization strategy;Finally,an example is simulated and solved.The experimental results show that this method not only accelerates the convergence of optimization and reduces the minimum cost,but also meets the needs of different situations with multiple objectives.
作者
王海东
胡佳瑞
刘川帅
郭一娜
WANG Hai-dong;HU Jia-rui;LIU Chuan-shuai;GUO Yi-na(College of Electronics and Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)
出处
《太原科技大学学报》
2025年第6期529-534,542,共7页
Journal of Taiyuan University of Science and Technology
基金
国家自然科学基金(62271341)
山西省科技创新人才团队(202204051001018)。
关键词
容量配置优化
改进型粒子群
多目标粒子群
capacity allocation optimization
improved particle swarm optimization
multi-objective particle swarm optimization
