基于自适应PSO算法的机组优化组合研究  

An Adaptive Particle Swarm Optimization Algorithm for Solving Unit Commitment

作　　者：蒋秀洁[1] 袁兆强[1] 黄景光[1] 

机构地区：[1]三峡大学电气信息学院,湖北宜昌443002

出　　处：《三峡大学学报（自然科学版）》2005年第2期115-118,共4页Journal of China Three Gorges University：Natural Sciences

摘　　要：提出了解决电力系统机组优化组合问题的一种新的方法——自适应粒子群优化算法(APSO).PSO算法能解决许多遗传算法能解决的优化问题,但却只需要一些简单的参数就可稳定收敛得到高质量的解.将该算法应用到IEEE10机系统中,结果表明该算法用于求解机组优化组合是有效可行的.This paper proposes a new approach to solve the optimization of unit commitment using an adaptive particle swarm optimization algorithm .In practice, the unit commitment problem is quit difficult to obtain the best globe solution in theory due to its inherent higher-dimensional, multi-phases, nonconlex, a large set of operating constraints and nonlinear mixed integer programming problem in mathematics. The PSO method can be used to solve many optimization problems of the same kind as GA and SA methods; and it can generate high-quality solutions with stable convergence, requiring only some concise parameters. The feasibility of the proposed method is demonstrated for 10 unit systems, and the test results show that it is indeed efficient and reliable.

关 键 词：PSO算法 自适应 组合研究 粒子群优化算法 机组优化组合 优化问题 遗传算法 组合问题 电力系统 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP273.2[自动化与计算机技术—计算机科学与技术]