等微增率复合遗传算法在负荷分配中的应用

Application of Composite Genetic Algorithm with Equal Micro-increment Rate in Load Distribution

以大型火电厂为对象,研究厂级机组负荷优化分配问题。将基于经典数学规划理论的等微增率法和智能遗传算法两者结合,提出了一种名为等微增率复合遗传算法的新型改进算法。改进的算法利用等微增率法确定最佳分配方案的大致范围,通过缩小遗传算法中初代种群选取范围的方法提高算法收敛速度和寻优准确性,体现了禁忌搜索的算法思想。通过对等微增率法、传统遗传算法、改进算法三者的性能分析比较,结果表明:3种算法结果基本一致,形成相互验证,均可准确计算厂级负荷分配问题;改进后的等微增率复合遗传算法,相较于传统遗传算法有更好的收敛性能,且不易陷入局部最优。

This paper took large-scale thermal power plants as the object to study the problem of optimal load distribution of plant-level units.Combining the micro-increment rate method based on classical mathematical programming theory with intelligent genetic algorithm,a new improved algorithm called composite genetic algorithm with equal micro-increasing rate was proposed.The improved algorithm uses the micro-increment rate method to determine the approximate range of the optimal allocation scheme.By narrowing the selection method of the primary population in the genetic algorithm,the convergence speed and optimization accuracy of the algorithm are improved,and the algorithm idea of tabu search is embodied.Through the performance analysis of equal micro-increasing rate method,traditional genetic algorithm and improved algorithm,the results show that the results of the three algorithms are basically the same,and mutual verification is formed,which can accurately calculate the plant-level load distribution problem;the composite genetic algorithm with equal micro-increasing rate has better convergence performance than the traditional genetic algorithm and is not easy to fall into local optimum.