摘要
免疫粒子群优化算法(IA-PSO)是将免疫系统的免疫信息处理机制引入粒子群算法(PSO)中,利用其特有的浓度选择机制以及疫苗接种原理,改进了粒子群优化算法的全局寻优能力,提高了收敛速度。在分析梯级水电厂间负荷分配的数学模型和IA-PSO算法特点的基础上,提出了基于IA-PSO算法的负荷优化分配方法,建立了数学模型,给出了具体求解步骤。经实例验证,IA-PSO算法得出的负荷分配方案优于PSO算法的计算结果,且算法后期收敛速度快,从而为梯级水电厂间负荷优化分配问题提供了一条新的求解途径,可应用于更广泛的优化问题。
The immune particle swarm optimal algorithm（IA-PSO）, which is proposed by invdving the immune information processing mechanism into the original particle swarm optimal algorithm, improves the ability of seeking the global excellent result and covergence speed with its especial consistency selection mechanism and bacterin inoculation. Based on analyzing the model of load distribution among cascaded hydropower stations and the traits of IA-PSO, the corresponding mathematical description and the solution procedure by using IA-PSO is presented in this paper. In the case study, IA-PSO can gain superior load distribution scheme to PSO and own faster constringency speed in the evening evolution. Thus, a new and valid method is provided for solving the problem of optimized loading distribution among cascaded hydropower stations, it can be available for extensive optimization application.
出处
《水力发电学报》
EI
CSCD
北大核心
2007年第5期15-20,共6页
Journal of Hydroelectric Engineering
基金
国家自然科学基金项目资助(50579019)
关键词
水电工程
负荷分配
免疫粒子群算法
梯级水电厂
hydropower engineering
loading distribution
immune particle swarm optimization algorithm
cascaded hydropower stations
