基于粒子群算法的空间太阳能热动力系统优化设计

OPTIMIZATION DESIGN OF SOLAR ENERGY DYNAMIC POWER SYSTEM IN SPACE STATION BASED ON PARTICLE SWARM ALGORITHMS

太阳能热动力系统是空间站的重要组成部分。为有效降低太阳能发电系统的发射质量,在分析空间太阳能热动力系统的工作原理、粒子群算法的原理及实现的基础上,采用粒子群算法对太阳能热动力系统的发射质量进行了优化仿真设计。在保证压缩机的进口压力、压缩机的进口温度、压缩机的压缩系数、换热管的数目、换热管的直径、回热器的回热度、循环工质流道高度、热管直径、热管长度及能量转换单元的转速等独立变量满足系统要求的前提下,使得发射质量最小,从而有效地节约发射、管理和后续支持费用。将粒子群算法的优化结果通过遗传变异修正后,其结果要好于基本粒子群算法和遗传算法结果。

Solar energy dynamic power system plays a very important role in space station. Based on particle swarm algorithms and working principle of the system, optimization simulation designs are made in order to minimize the launching mass of the system. Under the condition that all independent variables including import pressure, temperature and compression coefficient of compressor, numbers and diameter of heat exchangers, regenerating temperature of regenerator, height of recycling refrigeran, diameter and length of heat exchangers and rotating speed of energy converting unit satisfy the requirements of the whole system, the launching mass is minimized. The simulation results are improved by genetic modification and the improved results are better than those calculated by particle swarm algorithms and genetic algorithms.