基于改进粒子群算法的气化配煤模型求解

针对目前我国煤质差异较大,单煤煤质与炉型无法稳定匹配这一现象,提出配煤优化方案,选用PSO算法建立配煤模型。并且对原始PSO算法存在收敛速度慢、易陷入局部最优等问题,结合实际配煤优化问题的特点对算法进行改进,将改进后的PSO算法与原始算法进行对比实验,结果表明优化后的PSO算法在保证配煤合理的前提下,整体性能明显优于原始算法。

Solution of Gasification Coal Blending Model Based on Improved Particle Swarm Optimization

In view of the current large difference in coal quality in China, the single coal coal quality and furnace type cannot be stably matched, a coal blending optimization scheme is proposed, and a coal blending model is established using PSO algorithm. And the original PSO algorithm has problems such as slow convergence speed and easy to fall into local optimization. The algorithm is improved according to the characteristics of the actual coal blending optimization problem. The improved PSO algorithm is compared with the original algorithm. The results show that the optimized PSO algorithm on the premise of ensuring reasonable coal blending, the overall performance is significantly better than the original algorithm.