학술논문
基于改进GSA算法的多能源移动电源车优化配置 / Optimal Configuration of Multi-energy Mobile Power Vehicles Based on Improved GSA Algorithm
Document Type
Academic Journal
Author
Source
计算机与现代化 / Computer and Modernization. (12):105-111
Subject
Language
Chinese
ISSN
1006-2475
Abstract
传统能源供给模式很难覆盖高原高寒地区的能源孤岛,而多能源移动电源车因其机动灵活、环境适应性强的特点成为较好的解决手段.现有多能源移动电源车尚缺乏针对高原高寒独特背景下的应用研究,且当前研究中的多能源配置算法存在收敛速度慢、易陷入局部最优等问题.本文提出一种基于改进型万有引力算法的多能源配置算法,以多能源移动电源车年经济成本为目标,在万有引力算法的基础上,引入粒子群算法的思想,将个体历史最优和全局最优位置赋权,引入粒子群速度迭代计算,提高粒子群收敛的速度和方向性.依据西藏某地区实际应用算例,该算法在收敛速度和全局搜索能力的优越性得到验证.结果表明,本文设计的移动电源车多能源配置具有更好的经济性,可为高原高寒地区多能源移动电源车的优化配置提供设计依据.
The traditional energy supply mode is difficult to cover the energy islands in the plateau and cold regions,and the multi-energy mobile power vehicle has become a better solution because of its flexible mobility and strong environmental adapt-ability.The existing multi-energy mobile power vehicles still lack application research for the unique background of plateau and cold,existing multi-energy allocation algorithms have some problems such as slow convergence speed and easy to fall into local optimality.A multi-energy configuration algorithm is proposed on the basis of the improved universal gravitational search algo-rithm in this work.In order to decrease the annual economic cost of multi-energy mobile power vehicles,the particle swarm opti-mization algorithm is introduced in this modified algorithm on the basis of the universal gravitational algorithm.Meanwhile,the individual historical optimal and global optimal position assignment values are introduced for particle swarm velocity iteration cal-culation,thus improving the speed and directionality of particle swarm convergence.The superiority of the algorithm in conver-gence speed and global search capability is verified by practical application cases in the Somewhere region of Tibet.The results show that the multi-energy configuration strategy of mobile power vehicles designed based on the proposed algorithm has better economy and can provide a design basis for the optimal configuration of multi-energy mobile power vehicles in highland alpine areas.
The traditional energy supply mode is difficult to cover the energy islands in the plateau and cold regions,and the multi-energy mobile power vehicle has become a better solution because of its flexible mobility and strong environmental adapt-ability.The existing multi-energy mobile power vehicles still lack application research for the unique background of plateau and cold,existing multi-energy allocation algorithms have some problems such as slow convergence speed and easy to fall into local optimality.A multi-energy configuration algorithm is proposed on the basis of the improved universal gravitational search algo-rithm in this work.In order to decrease the annual economic cost of multi-energy mobile power vehicles,the particle swarm opti-mization algorithm is introduced in this modified algorithm on the basis of the universal gravitational algorithm.Meanwhile,the individual historical optimal and global optimal position assignment values are introduced for particle swarm velocity iteration cal-culation,thus improving the speed and directionality of particle swarm convergence.The superiority of the algorithm in conver-gence speed and global search capability is verified by practical application cases in the Somewhere region of Tibet.The results show that the multi-energy configuration strategy of mobile power vehicles designed based on the proposed algorithm has better economy and can provide a design basis for the optimal configuration of multi-energy mobile power vehicles in highland alpine areas.