改进的粒子群算法在太阳能光伏发电资料同化中的应用研究  

Research on data assimilation in solar photovoltaics power generation based on improved PSO algorithm

作　　者：李君妍 童亚拉[3] LI Junyan;TONG Yala(School of Computer Science,Hubei University of Education,Wuhan 430205,China;Hubei Co-Innovation Center of Basic Education Information Technology Services,Wuhan 430205,China;School of Science,Hubei University of Technology,Wuhan 430068,China)

机构地区：[1]湖北第二师范学院计算机学院,武汉430205 [2]基础教育信息技术服务湖北省协同创新中心,武汉430205 [3]湖北工业大学理学院,武汉430068

出　　处：《华中师范大学学报（自然科学版）》2021年第4期567-572,共6页Journal of Central China Normal University：Natural Sciences

基　　金：湖北省教育厅教学科研项目(2016294,2017320);湖北省教育厅科学技术研究计划指导性项目(B2020174);大学生创新创业训练计划项目(S202010500055)。

摘　　要：资料同化是目前太阳能光伏发电预测研究的一个关键和难点.近年来,遗传算法和粒子群算法等智能优化算法被引入到四维变分同化中.针对基于分子运动论的粒子群算法(MPSO)在处理大量数据时速度慢的不足,该文提出了并行分子运动论粒子群算法(PMPSO),并行计算的基本思想是将粒子群分成N个子集,每个子集交给一个线程控制,同时进行粒子迭代运算,以提高算法处理速度;每一子集中的头号精英粒子,将数据传递给公共部分在每次迭代完后,然后进入下一次迭代,其目的是让每个子集间进行信息交流以增加多样性.将其应用到资料同化中,与动态权重粒子群算法(PSOCIWAC)和时变双重压缩因子粒子群算法(PSOTVCF)在精度、时间上进行比较,实验结果表明:在收敛精度上,PMPSO方法在PSOCIWAC和PSOTVCF方法的基础上分别提高了10000倍和100倍,在时间上也具有很大的优越性.Data assimilation is a key and difficult point in the research of solar photovoltaic power generation prediction.Intelligent optimization algorithms such as genetic algorithm and particle swarm optimization algorithm are introduced into the four-dimensional variational assimilation.Aimed to slow speed of Particle Swarm Optimization algorithm based on Molecular Motion Theory(MPSO)when dealing with problems with large amounts of data,in this paper,a Parallel Modified Particle Swarm Optimization(PMPSO)is proposed,using parallel computing to shorten running time.The basic idea of parallel computing is to divide the particle swarm into N subsets,with each subset given to a thread for control,and iteration operation is carried out at the same time to improve the processing speed of the algorithm.After each iteration,the data of the elite particles in each subset will be transferred to the public part,and then the next iteration will be carried out to make the information exchange among each subset to increase the diversity.Results are applied to data assimilation in numerical weather forecasting,and compared with MPSO,Particle Swarm Optimization with Dynamic Inertia Weight and Acceleration Factor(PSOCIWAC)and Particle Swarm Optimization with Time Varying Constrict Factor(PSOTVCF)in accuracy and time,the experimental results showed that based on the PSOCIWAC and PSOTVCF methods,the convergence accuracy of PMPSO method is improved by 10000 and 100 times,respectively and it also have great advantages in time.

关 键 词：太阳能光伏发电 变分资料同化 分子运动PSO算法 并行算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]